CN117496443A - Highway power line fault detection method, device, electronic equipment and medium - Google Patents
Highway power line fault detection method, device, electronic equipment and medium Download PDFInfo
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Abstract
The application relates to the technical field of fault maintenance, in particular to a method, a device, electronic equipment and a medium for detecting a fault of a highway power line, wherein the method comprises the steps of determining hidden danger line partitions from a patrol inspection line model according to hidden danger characteristics; acquiring a field image corresponding to the hidden danger line partition, and determining hidden danger information corresponding to hidden danger features according to the field image; determining initial display interface information of hidden danger features based on hidden danger information; acquiring weather features within a preset time period, and adding hidden danger information and the weather features into a window simulation model for simulation to obtain a simulation image; the method comprises the steps of obtaining a three-dimensional simulation result of a window simulation model in a preset time period, matching the three-dimensional simulation result with hidden danger information, determining a hidden danger change value, adjusting initial interface display information according to the hidden danger change value, obtaining target interface display information, and displaying a simulation image according to the target interface display information. The method and the device can reduce the probability of fault occurrence.
Description
Technical Field
The application relates to the technical field of fault maintenance, in particular to a method, a device, electronic equipment and a medium for detecting a highway power line fault.
Background
The highway power line is an important carrier for power transmission, and the safe and stable operation of the highway power line has a crucial significance for energy safety, and once the power line is damaged or fails, the highway power line can bring great influence to the production and life of surrounding areas, and even serious accidents can be caused. Second, the safety hazards of the highway power lines may develop and become exposed over time, and if periodic inspection and maintenance is not performed, serious faults may develop, for example, degradation or corrosion of the lines may result in serious faults in the absence of inspection.
In the related art, generally, the inspection image is checked to identify hidden danger points contained in the inspection image, and then each hidden danger point is manually overhauled to eliminate possible faults in a highway power line. However, because the probability of occurrence of faults is different due to different hidden trouble points, when a plurality of hidden trouble points need to be overhauled, the corresponding hidden trouble points cannot be timely overhauled in the optimal overhauling period, so that the probability of occurrence of faults can be increased, and further the loss caused by occurrence of faults can be increased.
Disclosure of Invention
In order to reduce the probability of occurrence of faults and further reduce losses caused by occurrence of faults, the application provides a highway power line fault detection method, a highway power line fault detection device, electronic equipment and a highway power line fault detection medium.
In a first aspect, the present application provides a method for detecting a fault in a highway power line, which adopts the following technical scheme:
a highway power line fault detection method comprising:
determining hidden danger line partitions from a patrol line model according to hidden danger characteristics, wherein the patrol line model is a three-dimensional model corresponding to a power line to be detected, and the power line to be detected can be divided into at least one line partition;
acquiring a field image corresponding to the hidden danger line partition, and determining hidden danger information corresponding to the hidden danger feature according to the field image;
determining initial display interface information of the hidden danger characteristics based on the hidden danger information, wherein the initial display interface information comprises an initial display interface size of a window simulation model and an initial display position of the window simulation model in a routing inspection line model, and the window simulation model is a three-dimensional model corresponding to the hidden danger line partition;
acquiring weather features within a preset time period, and adding the hidden danger information and the weather features into the window simulation model for simulation to obtain a simulation image;
The method comprises the steps of obtaining a three-dimensional simulation result of the window simulation model in the preset time period, matching the three-dimensional simulation result with hidden danger information, determining a hidden danger change value, adjusting initial interface display information according to the hidden danger change value to obtain target interface display information, and displaying the simulation image according to the target interface display information.
By adopting the technical scheme, the environment where the power line to be detected is located is supervised through the three-dimensional model corresponding to the power line to be detected, potential hazards possibly existing in the power line are conveniently and timely found, when the potential hazards exist in the power line to be detected, warning signals are not directly generated, but the potential hazards are simulated through the change possibly occurring in a period of time in the future so as to judge the probability that the potential hazards can cause faults, the danger level of the potential hazards is judged, the accuracy in abnormal condition determination is conveniently improved, and the simulation image corresponding to the potential hazards is conveniently displayed through the small window, the importance degree of relevant maintainers is conveniently improved, the corresponding display interface information is conveniently determined according to the influence possibly caused by the potential hazards, so that the relevant maintainers can be conveniently assisted to distinguish different potential hazards, the relevant maintainers can be conveniently and reasonably allocate maintenance resources, the corresponding potential hazards can be conveniently and timely checked in the optimal maintenance period, the probability of faults is conveniently reduced through giving sufficient importance to the potential hazards with high priority and timely treatment, and loss caused by faults is conveniently reduced.
In one possible implementation, the method further includes:
acquiring a route to be detected and a first preset height, and generating a first inspection instruction according to the route to be detected and the first preset height, wherein the first inspection instruction is used for controlling inspection equipment to acquire images of the route to be detected according to the first preset height so as to obtain an initial inspection image;
when the initial inspection image contains preset features, marking the preset features contained in the initial inspection image to obtain marking positions corresponding to each preset feature;
generating a second inspection instruction according to the mark position and the number of each preset feature, wherein the second inspection instruction is used for controlling inspection equipment to acquire images of the route to be detected according to the second inspection instruction, so as to obtain a final inspection image;
and carrying out hidden danger feature recognition on the final inspection image.
By adopting the technical scheme, the inspection route is subjected to image acquisition according to different heights so as to facilitate the improvement of the integrity of the inspection image, and the power consumption rate of the inspection equipment is reduced while the definition of the inspection image is improved due to the fact that the positions of the preset features in the power line to be detected are different and the quantity contained in different stages are also different, and the inspection height of each divided inspection route is determined according to the density of the preset features.
In one possible implementation manner, the generating a second inspection instruction according to the marking position and the number of each preset feature includes:
dividing the route to be detected based on the mark position of each preset feature to obtain at least one divided detection route, and determining the mark density corresponding to each divided detection route;
and determining a second preset height and a stop position corresponding to each divided detection route based on the mark density corresponding to each divided detection route, and generating a second inspection instruction corresponding to each divided detection route based on the second preset height and the stop position corresponding to each divided detection route.
Through adopting above-mentioned technical scheme, because when preset feature quantity is more, the probability that corresponds the region and break down also can increase, through the mark intensity that different divisions detect the route and correspond, confirm every division detect the second of route and predetermine the height, be convenient for promote the adaptation degree of inspection height and division detect the route to be convenient for promote the clear degree of inspection image shooting.
In one possible implementation manner, the dividing the route to be detected based on the marking position of each preset feature includes:
When the patrol image contains an obstacle identifier, historical fault information is acquired, and an influence range and an influence probability corresponding to the obstacle identifier are determined according to the historical fault information;
determining an obstacle influence value of each preset feature according to an influence range corresponding to the obstacle identifier, the influence probability and the mark position of each preset feature in the initial dividing detection route;
determining at least one group of segmentation mark positions according to the obstacle influence value corresponding to each preset feature and the preset segmentation obstacle influence value, wherein the one group of segmentation mark positions comprise mark positions of two preset features;
and calculating a first center position corresponding to each group according to the mark position of the preset feature in each group, and dividing the power line to be detected according to the first center position corresponding to each group.
Through adopting above-mentioned technical scheme, through analyzing historical trouble information, confirm the obstacle sign that can lead to waiting to detect power line and break down, because the position of obstacle is generally fixed, consequently the obstacle influence value that same obstacle caused to different positions is different, it divides to wait to detect power line according to the obstacle influence value that every mark position corresponds, because the probability that different obstacle influence value corresponds to break down is different, consequently through being in same horizontal mark position to the obstacle influence value and unified management, be convenient for carry out pertinence management and control to the detected line after dividing.
In one possible implementation manner, the determining the obstacle impact value of each preset feature according to the impact range corresponding to the obstacle identifier, the impact probability and the marking position of each preset feature in the initial dividing detection route includes:
determining at least one influence dimension according to the influence range corresponding to the obstacle identifier;
determining influence dimension probability corresponding to each influence dimension according to the influence probability;
determining adjacent influence dimensions of each marking position from at least one influence dimension according to the marking position of each preset feature, and judging whether the adjacent influence dimensions are associated influence dimensions according to the adjacent influence dimensions corresponding to each marking position, wherein the associated influence dimensions are influence object dimensions with the interval distance between the adjacent influence dimensions being lower than a preset interval distance;
if not, determining a dimension interval distance between each marking position and the adjacent influence dimension, determining the influence dimension with the smallest dimension interval distance as a target influence dimension, and determining the influence dimension probability corresponding to each target influence dimension as an obstacle influence value corresponding to a preset feature;
if so, determining adjacent influence dimensions as target influence dimensions, and determining the sum of influence dimension probabilities corresponding to the adjacent influence dimensions as obstacle influence values corresponding to preset features.
By adopting the technical scheme, the influence dimension is determined directly according to the influence range corresponding to the obstacle identifier, rather than the influence dimension is determined through the identification result of the preset feature, so that the accuracy can be improved. Because the recognition result of the preset features may be affected by factors such as image quality and feature extraction algorithm, misrecognition or missing recognition may occur, and the situation can be avoided by directly determining the influence dimension according to the influence range corresponding to the obstacle identifier.
In one possible implementation, the method further includes:
determining boundary mark positions in each divided detection route and adjacent mark positions adjacent to the boundary mark positions according to mark positions of preset features in each divided detection route;
calculating a boundary distance between each boundary mark position and the corresponding first center position, and an adjacent distance between the boundary mark position and the corresponding adjacent mark position;
and when the boundary distance is lower than the adjacent distance, determining a second center position of the boundary mark position and the corresponding adjacent mark position, and adjusting the division detection route according to the second center position.
Through adopting above-mentioned technical scheme, adjust the division detection route through boundary mark position and adjacent mark position, reject some interval distance remote mark position from the current division detection route, be convenient for promote the uniformity of dividing the interior mark position of detection route to be convenient for reflect the rule and the trend of this division detection route interior mark position more accurately.
In one possible implementation manner, the determining, based on the mark density corresponding to each divided detection route, a second preset height and a stay position corresponding to each divided detection route, and generating, based on the second preset height and the stay position corresponding to each to-be-detected divided route, a second inspection instruction corresponding to each divided detection route includes:
determining the stay position of each division detection route according to the obstacle influence value of each preset feature;
determining the patrol stay time and the second preset height corresponding to each stay position according to the mark density corresponding to each divided detection route;
and determining a second inspection instruction of each divided detection route according to the corresponding stay position, stay time length and second preset height of each divided detection route.
Through adopting above-mentioned technical scheme, because the trouble probability that different obstacle influence values correspond is different, consequently confirm to patrol and examine the position of staying through dividing the obstacle influence value that the mark position corresponds of route, promptly stay longer in the mark position that the obstacle influence value is higher, just through promoting image acquisition's comprehensiveness and integrality, more comprehensive image acquisition helps collecting more detailed and comprehensive information to be convenient for know better and master the condition of the mark position that the obstacle influence value is higher.
In a second aspect, the present application provides a highway power line fault detection device, which adopts the following technical scheme:
a highway power line fault detection apparatus comprising:
the hidden danger line partition determining module is used for determining hidden danger line partitions from the inspection line model according to hidden danger characteristics, wherein the inspection line model is a three-dimensional model corresponding to the power line to be detected, and the power line to be detected can be divided into at least one line partition;
the hidden danger information determining module is used for acquiring a field image corresponding to the hidden danger line partition, and determining hidden danger information corresponding to the hidden danger feature according to the field image;
The interface information determining module is used for determining initial display interface information of the hidden danger characteristics based on the hidden danger information, wherein the initial display interface information comprises an initial display interface size of a window simulation model and an initial display position of the window simulation model in a routing inspection line model, and the window simulation model is a three-dimensional model corresponding to the hidden danger line partition;
the simulation image determining module is used for acquiring weather features in a preset time period, and adding the hidden danger information and the weather features into the window simulation model for simulation to obtain a simulation image;
the image display module is used for obtaining a three-dimensional simulation result of the window simulation model in the preset time period, matching the three-dimensional simulation result with the hidden danger information, determining a hidden danger change value, adjusting the initial interface display information according to the hidden danger change value to obtain target interface display information, and displaying the simulation image according to the target interface display information.
By adopting the technical scheme, the environment where the power line to be detected is located is supervised through the three-dimensional model corresponding to the power line to be detected, potential hazards possibly existing in the power line are conveniently and timely found, when the potential hazards exist in the power line to be detected, warning signals are not directly generated, but the potential hazards are simulated through the change possibly occurring in a period of time in the future so as to judge the probability that the potential hazards can cause faults, the danger level of the potential hazards is judged, the accuracy in abnormal condition determination is conveniently improved, and the simulation image corresponding to the potential hazards is conveniently displayed through the small window, the importance degree of relevant maintainers is conveniently improved, the corresponding display interface information is conveniently determined according to the influence possibly caused by the potential hazards, so that the relevant maintainers can be conveniently assisted to distinguish different potential hazards, the relevant maintainers can be conveniently and reasonably allocate maintenance resources, the corresponding potential hazards can be conveniently and timely checked in the optimal maintenance period, the probability of faults is conveniently reduced through giving sufficient importance to the potential hazards with high priority and timely treatment, and loss caused by faults is conveniently reduced.
In one possible implementation, the apparatus further includes:
the first inspection instruction generation module is used for acquiring a route to be detected and a first preset height, generating a first inspection instruction according to the route to be detected and the first preset height, and controlling inspection equipment to acquire images of the route to be detected according to the first preset height to obtain an initial inspection image;
the feature marking module is used for marking the preset features contained in the initial inspection image when the preset features are contained in the initial inspection image, so as to obtain marking positions corresponding to each preset feature;
the second inspection instruction generation module is used for generating a second inspection instruction according to the mark position and the number of each preset feature, and the second inspection instruction is used for controlling inspection equipment to acquire images of the route to be detected according to the second preset height so as to obtain a final inspection image;
and the hidden danger feature recognition module is used for carrying out hidden danger feature recognition on the final inspection image.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when generating the second inspection instruction according to the marking position and the number of each preset feature:
Dividing the route to be detected based on the mark position of each preset feature to obtain at least one divided detection route, and determining the mark density corresponding to each divided detection route;
and determining a second preset height and a stop position corresponding to each divided detection route based on the mark density corresponding to each divided detection route, and generating a second inspection instruction corresponding to each divided detection route based on the second preset height and the stop position corresponding to each divided detection route.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when dividing the route to be detected based on the marking position of each preset feature:
when the patrol image contains an obstacle identifier, historical fault information is acquired, and an influence range and an influence probability corresponding to the obstacle identifier are determined according to the historical fault information;
determining an obstacle influence value of each preset feature according to an influence range corresponding to the obstacle identifier, the influence probability and the mark position of each preset feature in the initial dividing detection route;
determining at least one group of segmentation mark positions according to the obstacle influence value corresponding to each preset feature and the preset segmentation obstacle influence value, wherein the one group of segmentation mark positions comprise mark positions of two preset features;
And calculating a first center position corresponding to each group according to the mark position of the preset feature in each group, and dividing the power line to be detected according to the first center position corresponding to each group.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when determining the obstacle impact value of each preset feature according to the impact range corresponding to the obstacle identifier, the impact probability, and the mark position of each preset feature in the initial dividing detection route:
determining at least one influence dimension according to the influence range corresponding to the obstacle identifier;
determining influence dimension probability corresponding to each influence dimension according to the influence probability;
determining adjacent influence dimensions of each marking position from at least one influence dimension according to the marking position of each preset feature, and judging whether the adjacent influence dimensions are associated influence dimensions according to the adjacent influence dimensions corresponding to each marking position, wherein the associated influence dimensions are influence object dimensions with the interval distance between the adjacent influence dimensions being lower than a preset interval distance;
if not, determining a dimension interval distance between each marking position and the adjacent influence dimension, determining the influence dimension with the smallest dimension interval distance as a target influence dimension, and determining the influence dimension probability corresponding to each target influence dimension as an obstacle influence value corresponding to a preset feature;
If so, determining adjacent influence dimensions as target influence dimensions, and determining the sum of influence dimension probabilities corresponding to the adjacent influence dimensions as obstacle influence values corresponding to preset features.
In one possible implementation, the apparatus further includes:
a module for determining adjacent mark positions, which is used for determining boundary mark positions in each divided detection route and adjacent mark positions adjacent to the boundary mark positions according to mark positions of preset features in each divided detection route;
the adjacent distance determining module is used for calculating the boundary distance between each boundary mark position and the corresponding first center position and the adjacent distance between the boundary mark position and the corresponding adjacent mark position;
and the route adjustment module is used for determining the boundary mark position and a second center position corresponding to the adjacent mark position when the boundary distance is lower than the adjacent distance, and adjusting the division detection route according to the second center position.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when determining, based on the mark density corresponding to each of the divided detection routes, a second preset height and a residence position corresponding to each of the divided detection routes, and generating, based on the second preset height and the residence position corresponding to each of the divided detection routes to be detected, a second inspection instruction corresponding to each of the divided detection routes:
Determining the stay position of each division detection route according to the obstacle influence value of each preset feature;
determining the patrol stay time and the second preset height corresponding to each stay position according to the mark density corresponding to each divided detection route;
and determining a second inspection instruction of each divided detection route according to the corresponding stay position, stay time length and second preset height of each divided detection route.
In a third aspect, the present application provides an electronic device, which adopts the following technical scheme:
an electronic device, the electronic device comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: and executing the road power line fault detection method.
In a fourth aspect, the present application provides a computer readable storage medium, which adopts the following technical scheme:
a computer-readable storage medium, comprising: a computer program capable of being loaded by a processor and executing the above road power line fault detection method is stored.
In summary, the present application includes at least one of the following beneficial technical effects:
The environment where the power line to be detected is located is supervised through the three-dimensional model corresponding to the power line to be detected, potential hazards possibly existing in the power line are conveniently and timely found, when the potential hazards exist in the power line to be detected, warning signals are not directly generated, but the potential hazards possibly occurring in a period of time in the future are simulated to judge the probability that the potential hazards can cause faults, the accuracy in determining the faults is conveniently improved through judging the danger level of the potential hazards, the importance degree of related maintenance personnel is conveniently improved through displaying the simulation image corresponding to the potential hazards by using the small window, the corresponding display interface information is conveniently determined according to the influence possibly caused by the potential hazards, so that the related maintenance personnel can be conveniently and reasonably allocated with maintenance resources, the corresponding potential hazard points can be conveniently and timely checked in the optimal maintenance period, the probability of faults occurring is conveniently reduced through giving sufficient importance to the potential hazards with high priority, and the loss caused by faults is conveniently reduced.
Through analyzing historical fault information, determining the obstacle mark which possibly causes the power line to be detected to fail, because the positions of the obstacles are generally fixed, the obstacle influence values of the same obstacle caused to different positions are different, the power line to be detected is divided according to the obstacle influence values corresponding to each mark position, and because the probability of failure corresponding to different obstacle influence values is different, the mark positions with the obstacle influence values at the same level are uniformly managed, and the divided detection lines are convenient to manage and control in a targeted manner.
Drawings
Fig. 1 is a schematic flow chart of a method for detecting a fault of a highway power line according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of a route dividing method according to an embodiment of the present application;
FIG. 3 is a diagram illustrating an example of routing in an embodiment of the present application;
FIG. 4 is an exemplary illustration of a dwell position in an embodiment of the application;
fig. 5 is a schematic structural diagram of an apparatus of a highway power line fault detection method according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
Further details of the present application are described below in conjunction with FIGS. 1-6.
Modifications of the embodiments which do not creatively contribute to the invention may be made by those skilled in the art after reading the present specification, but are protected by patent laws only within the scope of claims of the present application.
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
Specifically, the embodiment of the application provides a method for detecting a fault of a highway power line, which is executed by electronic equipment, wherein the electronic equipment can be a server or a terminal device, and the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server for providing cloud computing service. The terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto, and the terminal device and the server may be directly or indirectly connected through a wired or wireless communication manner, which is not limited herein.
Referring to fig. 1, fig. 1 is a flow chart of a highway power line fault detection method according to an embodiment of the present application, where the method includes steps S110 to S150, where:
step S110: and determining hidden danger line partitions from the inspection line model according to hidden danger characteristics, wherein the inspection line model is a three-dimensional model corresponding to the power line to be detected, and the power line to be detected can be divided into at least one line partition.
Specifically, when the inspection line model is constructed, the to-be-detected power line and the road marks around the to-be-detected power line, such as road signs, service areas and the like, can be identified from the historical inspection image, and then the to-be-detected power line and the road marks around the to-be-detected power line are modeled by three-dimensional modeling software, wherein the three-dimensional modeling software can be SketchUp, blender, autoCAD and the like, and specific software is not specifically limited in the embodiment of the application, so long as the three-dimensional model corresponding to the to-be-detected power line can be obtained. The hidden trouble line partition is an area containing hidden trouble features, and one hidden trouble line partition can contain 1 hidden trouble feature, can also contain a plurality of hidden trouble features, and specific quantity is not specifically limited in the embodiment of the application, and can be set by relevant technicians.
Step S120: and acquiring a field image corresponding to the hidden danger line partition, and determining hidden danger information corresponding to hidden danger features according to the field image.
Specifically, the on-site image is different from the inspection image, the inspection image is uniformly shot by the inspection device, the on-site image can be shot by the image acquisition device arranged in the hidden danger line zone and then uploaded to the electronic device, and the on-site image can be shot by other inspection devices, so that compared with the inspection image, the on-site image shot image is more comprehensive and targeted. The hidden danger information is information of hidden danger features, including hidden danger feature sizes, areas, colors and the like, and hidden danger information corresponding to different hidden danger features is different, for example, when the hidden danger features are cracks, the hidden danger information can be crack lengths, crack widths and the like; when the hidden danger is characterized by backlog, the hidden danger information can be backlog area, backlog thickness and the like.
Step S130: and determining initial display interface information of hidden danger features based on hidden danger information, wherein the initial display interface information comprises an initial display interface size of a window simulation model and an initial display position of the window simulation model in a routing inspection line model, and the window simulation model is a three-dimensional model corresponding to hidden danger line partitions.
Specifically, a corresponding mapping relation is determined according to the hidden danger feature, hidden danger information is compared with the corresponding mapping relation to determine the probability that the hidden danger feature causes faults, wherein the mapping relation corresponding to the hidden danger feature contains different hidden danger information which can cause faults, the mapping relation corresponding to the different hidden danger feature is different, and the specific content of the mapping relation is not specifically limited in the embodiment of the present application. The larger the probability of occurrence of the fault is, the larger the corresponding initial interface size is, and the initial interface size can be determined according to the probability mapping relation and the probability of occurrence of the fault, wherein the probability mapping relation comprises interface sizes corresponding to different probabilities of occurrence of the fault, the specific content of the probability mapping relation is not specifically limited in the embodiment of the application, and can be set by related technicians. The initial display position is the position of the display interface in the inspection line model, and corresponds to the marking position corresponding to the hidden danger information.
When the window model is acquired, the window model can be acquired after the model is constructed directly according to the image containing the hidden trouble line partition, and the process of constructing the window simulation model can refer to the mode of constructing the inspection route model in the above embodiment, and details are not repeated here; the corresponding part of the hidden trouble line partition can also be extracted from the constructed inspection line model, and the specific mode is not specifically limited in the embodiment of the present application.
Step S140: and obtaining weather features within a preset time period, and adding hidden danger information and the weather features into a window simulation model to simulate so as to obtain a simulation image.
Specifically, the preset time period may be 24 hours, 36 hours or 48 hours after the current time, and the specific time period is not specifically limited in the embodiment of the present application, and the weather features include rainfall, wind blowing or snowfall, rainfall, wind direction, wind force, snowfall, and the like. And adding hidden danger information and weather features into a window simulation model for simulation, wherein the model simulates possible changes of hidden danger information in hidden danger line subareas under the condition that the weather features correspond to the input data.
Step S150: the method comprises the steps of obtaining a three-dimensional simulation result of a window simulation model in a preset time period, matching the three-dimensional simulation result with hidden danger information, determining a hidden danger change value, adjusting initial interface display information according to the hidden danger change value, obtaining target interface display information, and displaying a simulation image according to the target interface display information.
Specifically, the three-dimensional simulation result can be determined by a simulation picture corresponding to the window simulation model at the last moment of the first preset time period, the simulation hidden danger information is identified from the simulation picture to be the three-dimensional simulation result, the hidden danger information is matched with the simulation hidden danger information to be convenient for determining the change of the hidden danger feature in the first preset time period, the hidden danger change value is a displacement difference value of the hidden danger feature, and the larger the displacement difference value is, the larger the change of the hidden danger feature in the preset time period is represented.
When the hidden danger change value adjusts the initial interface display information, the initial interface size is mainly adjusted, and because the initial interface size is determined according to the hidden danger information, if the hidden danger information disappears or weakens in a future period of time, the hidden danger information is characterized in that the probability of faults in the future period of time is reduced, for example, the backlog area in the hidden danger information is reduced, the backlog thickness is reduced, the initial interface size can be reduced at the moment, and the specific adjustment quantity is determined by the mapping relation between the change value and the adjustment value. When the simulated image is projected in the inspection model, a binding relation between the simulated image and the initial interface and a starting condition can be established first, and the simulated image is started when the starting condition is met, wherein the starting condition can be to click a certain target area or input a target instruction, a specific form can be set by related technicians, and the method is not limited in the embodiment of the application.
Since the development of different hidden danger features in a future period is different, the probability of occurrence of faults caused by the corresponding different hidden danger features in the future period is also different, and therefore, the interface sizes corresponding to different hidden danger features, namely different marking positions, are also different, as shown in fig. 2.
For the embodiment of the application, the environment where the power line to be detected is located is supervised through the three-dimensional model corresponding to the power line to be detected, so that potential hazards of the power line can be found in time, when the potential hazards exist in the power line to be detected, warning signals are not directly generated, but the potential hazards are simulated to judge the probability that faults occur due to the potential hazards in a future period of time, the danger level of the potential hazards is judged, the accuracy of determining the abnormal conditions is convenient to improve, and the simulation image corresponding to the potential hazards is displayed through the small window, so that the importance degree of relevant maintainers is convenient to improve, the corresponding display interface information is determined according to the influence possibly caused by the potential hazards, so that the relevant maintainers can be helped to distinguish different potential hazards, the relevant maintainers can be helped to reasonably allocate maintenance resources, the corresponding potential hazards can be checked in time in the optimal maintenance period, the probability of faults is convenient to reduce the occurrence probability of the faults due to the faults through generating enough potential hazards with high priority and timely processing, and the loss caused by fault occurrence is convenient to be reduced.
Further, the method further comprises: acquiring a route to be detected and a first preset height, and generating a first inspection instruction according to the route to be detected and the first preset height, wherein the first inspection instruction is used for controlling inspection equipment to acquire images of the route to be detected according to the first preset height, so as to obtain an initial inspection image; when the initial inspection image contains preset features, marking the preset features contained in the initial inspection image to obtain marking positions corresponding to each preset feature; generating a second inspection instruction according to the mark position and the number of each preset feature, wherein the second inspection instruction is used for controlling inspection equipment to acquire images of a route to be detected according to the second inspection instruction, so as to obtain a final inspection image; and carrying out hidden danger feature recognition on the final inspection image.
Specifically, the route to be detected is a route including the power lines to be detected, inspection is performed according to the route to be detected, all the power lines to be detected can be shot, the first preset height can be 6 meters or 7 meters, and the first preset height is the set height of the power lines to be detected, and for example, for 220 kv and above power lines, the minimum ground clearance height should not be less than 7 meters due to different set heights corresponding to different voltage levels; 110 kv power line, the minimum ground clearance should not be less than 6 meters; the minimum ground clearance of the power line of 35 kv and below should not be less than 5 meters, so the specific first preset height is not specifically limited in the embodiment of the present application, and may be set by a relevant technician according to the actual situation of the power line to be detected. After the electronic equipment generates the first inspection instruction, the first inspection instruction can be sent to the inspection equipment, so that the inspection equipment can acquire images according to the first village building instruction.
The preset features may be shadows, deformation, and the like, when the power line to be detected includes the preset features, the power line to be detected cannot be characterized as having a fault at the moment, and it can be stated that when the power line to be detected has the preset features, the power line to be detected may have a fault, and the specific content of the preset features is not specifically limited in the embodiment of the present application, and may be added and modified by related technicians according to actual situations. When the preset features are marked in the initial inspection image, the preset features contained in the initial inspection image can be identified according to the marking content, and the specific marking forms are not particularly limited in the embodiment of the application. The number of preset features included in the initial inspection image may be 0, 1 or more, and the specific number is not specifically limited in the embodiment of the present application.
The more the mark positions are, the greater the probability that the dividing detection route breaks down is, so that the importance degree is improved by adjusting the shooting height during secondary inspection, the second preset height is lower than the first preset height, the lower the height, the clearer the shot image picture is, the specific height value is not particularly limited in the embodiment of the application, and the setting can be performed by related technicians.
The hidden danger features can be cracks, damages, backlog and the like, when the hidden danger features exist in the to-be-detected power line, the to-be-detected power line cannot be characterized as having faults, and the hidden danger feature recognition method can be used for recognizing the hidden danger features contained in the to-be-detected power line through a trained feature recognition model when the hidden danger features are contained in the to-be-detected power line, wherein the feature recognition model is obtained by training a large number of forward sample data and reverse sample data, the forward sample data is sample data containing the hidden danger features and manual labels, and the reverse sample data is sample data not containing the hidden danger features and the manual labels.
Further, generating a second inspection instruction according to the marking position and the number of each preset feature, including:
dividing a route to be detected based on the mark position of each preset feature to obtain at least one divided detection route, and determining the mark density corresponding to each divided detection route; and determining a second preset height and a stop position corresponding to each divided detection route based on the mark density corresponding to each divided detection route, and generating a second inspection instruction corresponding to each divided detection route based on the second preset height and the stop position corresponding to each divided detection route.
Specifically, since the preset features included in the power line to be detected are relatively random, when the power line to be detected is divided, that is, when the power line to be detected is divided, the power line to be detected is mainly divided according to the distribution condition of each preset feature, and the densities and the numbers of the preset features included in different power lines to be detected are different. When determining the mark density corresponding to each divided detection route, the mark density corresponding to each divided detection route can be determined by counting the preset feature quantity contained in each divided detection route and comparing the preset feature quantity with the detection area corresponding to the divided detection route. The mark density corresponding to the dividing detection route can reflect the number of mark positions contained in the dividing detection route and the distribution situation of a plurality of mark positions, the stay position is a position where image shooting is stopped in the second inspection process, the stay position may correspond to the mark position in the dividing detection route, that is, each mark position in the dividing detection route may be used as a stay position, and the stay position may not correspond to the mark position in the dividing detection route. Further, in order to facilitate targeted management and control of the divided detection lines, dividing the route to be detected based on the marking position of each preset feature may specifically include steps Sa1 to Sa4, as shown in fig. 2, where:
Step Sa1: when the patrol image contains the obstacle identifier, historical fault information is acquired, and the influence range and the influence probability corresponding to the obstacle identifier are determined according to the historical fault information.
Specifically, the obstacle identifier may be a bridge pier, a tree, etc., and the specific obstacle identifier is not specifically limited in the embodiment of the present application, so long as the specific obstacle identifier may cause a fault in a highway power line, for example, if the bridge pier or the bridge is not stable enough or damaged, the passing highway power line may be affected, and a line fault may be caused when serious; if branches or trunks contact with the highway power line under natural conditions such as wind and rain, faults such as short circuit or power interruption of the highway power line may occur. The historical fault information comprises a historical period, and the corresponding fault reason is the obstacle identifier when the highway power line breaks down. The corresponding influence ranges of different obstacle identifiers are different, so that the probability of occurrence of faults is also different, and when the obstacle identifiers are contained in the inspection image, the corresponding influence ranges and influence probabilities can be determined through historical fault information.
Step Sa2: and determining the obstacle influence value of each preset feature according to the influence range, the influence probability and the mark position of each preset feature in the initial dividing detection route corresponding to the obstacle identifier.
Specifically, the shorter the interval distance between the marker position and the obstacle identifier, the larger the probability that the marker position may fail is represented, and in order to improve the accuracy in determining the obstacle influence value corresponding to each marker position, the obstacle influence value of each preset feature is determined according to the influence range, the influence probability and the marker position of each preset feature in the initial dividing detection route corresponding to the obstacle identifier, which specifically includes:
determining at least one influence dimension according to the influence range corresponding to the obstacle identifier; determining influence dimension probabilities corresponding to each influence dimension according to the influence probabilities; determining adjacent influence dimensions of each marking position from at least one influence dimension according to the marking position of each preset feature, and judging whether the adjacent influence dimensions are associated influence dimensions according to the adjacent influence dimensions corresponding to each marking position, wherein the associated influence dimensions are influence object dimensions with the interval distance between the adjacent influence dimensions being lower than a preset interval distance; if not, determining a dimension interval distance between each marking position and the adjacent influence dimension, determining the influence dimension with the smallest dimension interval distance as a target influence dimension, and determining the influence dimension probability corresponding to each target influence dimension as an obstacle influence value corresponding to a preset feature; if so, determining adjacent influence dimensions as target influence dimensions, and determining the sum of influence dimension probabilities corresponding to the adjacent influence dimensions as obstacle influence values corresponding to preset features.
Specifically, the influence range corresponding to the obstacle identifier may be reduced as the range of the obstacle identifier increases, as shown in fig. 3, where the influence range includes a plurality of influence dimensions, the influence dimension probability corresponding to each influence dimension is the same, and when the influence dimension corresponding to each influence range is divided, the influence dimension probability can be divided according to the influence dimension probability, that is, the difference value of the influence dimension probabilities between adjacent influence dimensions is the same; the division may also be performed according to a separation distance, that is, the separation distance between adjacent influencing dimensions is the same, and a specific division manner is not specifically limited in the embodiment of the present application, and may be set by a related technician. When the obstacle influence value corresponding to the mark position is determined, the influence dimension adjacent to the mark position can be determined from a plurality of influence dimensions, and when the associated influence dimension corresponding to the mark position is determined, the influence dimension probability corresponding to the associated influence dimension is directly determined as the obstacle influence value corresponding to the mark position; when the mark position corresponds to the associated influence dimension, that is, the interval record between the mark position and the adjacent influence dimension is not lower than the preset interval distance, at this time, the average influence dimension probability corresponding to the plurality of adjacent influence dimensions may be determined as the obstacle influence value corresponding to the mark position, where the preset interval distance is not specifically limited in the embodiment of the present application.
Step Sa3: and determining at least one group of segmentation mark positions according to the obstacle influence value corresponding to each preset feature and the preset segmentation obstacle influence value, wherein the one group of segmentation mark positions comprise mark positions of two preset features.
Specifically, the preset partition obstacle influence value may be 5 or 0, and the specific preset partition obstacle influence value is not specifically limited in the embodiment of the present application, and may be limited by a related technician, where, when the preset partition obstacle influence value is 0, after the partition is performed based on the preset partition obstacle influence value, the obstacle influence value corresponding to the mark position included in each partition is not 0, or the obstacle influence value corresponding to the mark position included in each partition is all 0. The dividing mark positions are two mark positions about the corresponding influence dimension of the preset dividing obstacle influence value, as shown in fig. 3, and the point e and the point f can be used as a group of dividing mark positions.
Step Sa4: and calculating a first center position corresponding to each group according to the mark position of the preset feature in each group, and dividing the power line to be detected according to the first center position corresponding to each group.
Specifically, when dividing the power line to be detected, a line segment passing through the center position may be determined as a dividing line, and the power line to be detected may be divided based on the dividing line. And determining the corresponding central position of each group, namely determining the coordinates of the central points corresponding to the two mark positions.
The method specifically includes the steps of generating a second inspection instruction corresponding to each divided detection route based on a second preset height and a stay position corresponding to each divided detection route:
determining the stay position of each division detection route according to the obstacle influence value of each preset feature; determining the patrol stay time and the second preset height corresponding to each stay position according to the mark density corresponding to each divided detection route; and determining a second inspection instruction of each divided detection route according to the corresponding stay position, stay time length and second preset height of each divided detection route.
Specifically, a mark position where the obstacle influence value exceeds a first preset standard value is determined as a target position, and each target position is determined as a stay position, in addition to this, a plurality of mark positions where the sum of the obstacle influence values exceeds a second preset standard value may be determined as a target position group, as shown in fig. 4, and the center point position of each target position group is determined as a stay position, where the first preset standard value is lower than the second preset standard value, and specifically may be set by a related technician.
The inspection residence time length is residence time length of the inspection equipment at each residence position, when the inspection residence time length of each divided detection route is determined, the obstacle influence mean value corresponding to the mark position contained in each divided detection route can be calculated first, then the corresponding inspection residence time length is determined according to the time length mapping relation, the residence time length corresponding to different obstacle influence values is contained in the time length mapping relation, and specific contents of the time length mapping relation are not specifically limited in the embodiment of the application. When determining the second inspection height, the height adjustment value corresponding to each division detection route may be determined according to the adjustment value mapping relationship, where the adjustment value mapping relationship includes height adjustment values corresponding to different obstacle impact values, and the specific content of the adjustment mapping relationship is not specifically limited in the embodiments of the present application. The specific manner of generating the second inspection instruction may refer to the embodiment corresponding to the first inspection instruction generating portion, which is not described herein. Each divided image contains a corresponding power line to be detected, and the inspection equipment uploads the power line to the electronic equipment after shooting the divided images.
Further, in order to more accurately reflect the rule and trend of the mark position in the dividing detection route, the method further includes:
determining boundary mark positions and adjacent mark positions adjacent to the boundary mark positions in each divided detection route according to mark positions of preset features in each divided detection route; calculating a boundary distance between each boundary mark position and the corresponding first center position, and an adjacent distance between the boundary mark position and the corresponding adjacent mark position; and when the boundary distance is lower than the adjacent distance, determining a second center position of the boundary mark position and the corresponding adjacent mark position, and adjusting the division detection route according to the second center position.
Specifically, the boundary mark positions in the divided detection route are the start position and the end position in the divided detection route, such as point a and point e in fig. 3, which respectively belong to the start position and the end position in the first divided detection route; the point f and the point g belong to the start position and the end position in the second division detection route, respectively. The adjacent mark positions of the initial positions are the positions adjacent to the initial positions in the same dividing detection route, and the adjacent mark positions of the tail end positions are the positions adjacent to the initial positions in the same dividing detection route. For example, the adjacent mark position corresponding to the start position point a in the first division detection route is the point b.
The center position is the end position in the last division detection route and the start position in the next division detection route, such as point e and point f in fig. 3. The boundary distance includes a start boundary distance and an end boundary distance, when the start boundary distance and the end boundary distance are lower than adjacent distances, the dividing detection route needs to be adjusted, when the boundary distance is calculated, the start boundary distance and the end boundary distance can be calculated according to a distance formula between points, for example, in fig. 3, when the end boundary distance needs to be calculated, a point e coordinate and a center point coordinate can be imported into the distance formula for calculation. Similarly, the boundary identification position and the corresponding adjacent mark position can be imported into a distance formula between points, and the adjacent distance can be calculated.
When the boundary distance is lower than the adjacent distance, such as the boundary distance between the point e and the point f, and is lower than the adjacent distance between the point d and the point e, the point e is removed from the first division detection route and is divided into a second detection route, then the center position between the point d and the point e is determined as a second center position, and finally a division line is generated based on the second center position, so that adjustment of the division detection route is realized. The dividing detection route is adjusted through the boundary mark positions and the adjacent mark positions, and some mark positions with longer intervals are removed from the current dividing detection route, so that consistency of mark positions in the dividing detection route is improved, and rules and trends of the mark positions in the dividing detection route are reflected more accurately.
The above embodiments describe a method for detecting a fault of a highway power line from the viewpoint of a method flow, and the following embodiments describe a device for detecting a fault of a highway power line from the viewpoint of a virtual module or a virtual unit, specifically the following embodiments are described below.
The embodiment of the application provides a highway power line fault detection device, as shown in fig. 5, the device may specifically include: a determine hidden trouble line partition module 510, a determine hidden trouble information module 520, a determine interface information module 530, a determine simulated image module 540, and an image presentation module 550, wherein:
the hidden danger line partition determining module 510 is configured to determine hidden danger line partitions from a patrol line model according to hidden danger characteristics, where the patrol line model is a three-dimensional model corresponding to a power line to be detected, and the power line to be detected may be divided into at least one line partition;
the hidden danger information determining module 520 is configured to obtain a field image corresponding to the hidden danger line partition, and determine hidden danger information corresponding to hidden danger features according to the field image;
the interface information determining module 530 is configured to determine initial display interface information of hidden danger features based on hidden danger information, where the initial display interface information includes an initial display interface size of a window simulation model and an initial display position of the window simulation model in a routing inspection line model, and the window simulation model is a three-dimensional model corresponding to a hidden danger line partition;
The simulation image determining module 540 is configured to obtain weather features within a preset time period, and add hidden danger information and the weather features to the window simulation model for simulation, so as to obtain a simulation image;
the image display module 550 is configured to obtain a three-dimensional simulation result of the window simulation model in a preset time period, match the three-dimensional simulation result with the hidden danger information, determine a hidden danger change value, adjust initial interface display information according to the hidden danger change value, obtain target interface display information, and display the simulation image according to the target interface display information.
In one possible implementation, the apparatus further includes:
the first inspection instruction generation module is used for acquiring a route to be detected and a first preset height, generating a first inspection instruction according to the route to be detected and the first preset height, and controlling the inspection equipment to acquire images of the route to be detected according to the first preset height to obtain an initial inspection image;
the feature marking module is used for marking the preset features contained in the initial inspection image when the preset features are contained in the initial inspection image, so as to obtain marking positions corresponding to each preset feature;
The second inspection instruction generation module is used for generating a second inspection instruction according to the mark position and the number of each preset feature, and the second inspection instruction is used for controlling the inspection equipment to acquire images of the route to be detected according to the second inspection instruction, so that a final inspection image is obtained;
and the hidden danger feature recognition module is used for carrying out hidden danger feature recognition on the final inspection image.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when generating the second inspection instruction according to the marking position and the number of each preset feature:
dividing a route to be detected based on the mark position of each preset feature to obtain at least one divided detection route, and determining the mark density corresponding to each divided detection route;
and determining a second preset height and a stop position corresponding to each divided detection route based on the mark density corresponding to each divided detection route, and generating a second inspection instruction corresponding to each divided detection route based on the second preset height and the stop position corresponding to each divided detection route.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when dividing the route to be detected based on the marking position of each preset feature:
When the patrol image contains the obstacle identifier, acquiring historical fault information, and determining an influence range and influence probability corresponding to the obstacle identifier according to the historical fault information;
determining an obstacle influence value of each preset feature according to an influence range, influence probability and a mark position of each preset feature in an initial dividing detection route corresponding to the obstacle mark;
determining at least one group of segmentation mark positions according to the obstacle influence value corresponding to each preset feature and the preset segmentation obstacle influence value, wherein the one group of segmentation mark positions comprise mark positions of two preset features;
and calculating a first center position corresponding to each group according to the mark position of the preset feature in each group, and dividing the power line to be detected according to the first center position corresponding to each group.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when determining the obstacle impact value of each preset feature according to the impact range, the impact probability and the mark position of each preset feature in the initial dividing detection route corresponding to the obstacle identifier:
determining at least one influence dimension according to the influence range corresponding to the obstacle identifier;
Determining influence dimension probabilities corresponding to each influence dimension according to the influence probabilities;
determining adjacent influence dimensions of each marking position from at least one influence dimension according to the marking position of each preset feature, and judging whether the adjacent influence dimensions are associated influence dimensions according to the adjacent influence dimensions corresponding to each marking position, wherein the associated influence dimensions are influence object dimensions with the interval distance between the adjacent influence dimensions being lower than a preset interval distance;
if not, determining a dimension interval distance between each marking position and the adjacent influence dimension, determining the influence dimension with the smallest dimension interval distance as a target influence dimension, and determining the influence dimension probability corresponding to each target influence dimension as an obstacle influence value corresponding to a preset feature;
if so, determining adjacent influence dimensions as target influence dimensions, and determining the sum of influence dimension probabilities corresponding to the adjacent influence dimensions as obstacle influence values corresponding to preset features.
In one possible implementation, the apparatus further includes:
the adjacent mark position determining module is used for determining a boundary mark position in each division detection route and an adjacent mark position adjacent to the boundary mark position according to the mark position of the preset feature in each division detection route;
The adjacent distance determining module is used for calculating the boundary distance between each boundary mark position and the corresponding first center position and the adjacent distance between the boundary mark position and the corresponding adjacent mark position;
and the route adjustment module is used for determining the boundary mark position and a second center position corresponding to the adjacent mark position when the boundary distance is lower than the adjacent distance, and adjusting the division detection route according to the second center position.
In one possible implementation manner, the second inspection instruction generating module is specifically configured to, when determining, based on the mark density corresponding to each of the divided detection routes, a second preset height and a residence position corresponding to each of the divided detection routes, and generating, based on the second preset height and the residence position corresponding to each of the divided detection routes to be detected, a second inspection instruction corresponding to each of the divided detection routes:
determining the stay position of each division detection route according to the obstacle influence value of each preset feature;
determining the patrol stay time and the second preset height corresponding to each stay position according to the mark density corresponding to each divided detection route;
and determining a second inspection instruction of each divided detection route according to the corresponding stay position, stay time length and second preset height of each divided detection route.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the above-described highway power line fault detection device may refer to the corresponding process in the foregoing method embodiment, which is not repeated herein.
In an embodiment of the present application, as shown in fig. 6, an electronic device 600 shown in fig. 6 includes: a processor 601 and a memory 603. The processor 601 is coupled to a memory 603, such as via a bus 602. Optionally, the electronic device 600 may also include a transceiver 604. It should be noted that, in practical applications, the transceiver 604 is not limited to one, and the structure of the electronic device 600 is not limited to the embodiment of the present application.
The processor 601 may be a CPU (Central Processing Unit ), general purpose processor, DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit ), FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic device, transistor logic device, hardware components, or any combination thereof. Which may implement or perform the various exemplary logic blocks, modules, and circuits described in connection with this disclosure. The processor 601 may also be a combination that performs computing functions, such as including one or more microprocessors, a combination of a DSP and a microprocessor, and the like.
Bus 602 may include a path to transfer information between the components. Bus 602 may be a PCI (Peripheral Component Interconnect, peripheral component interconnect Standard) bus or an EISA (Extended Industry Standard Architecture ) bus, or the like. The bus 602 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in fig. 6, but not only one bus or one type of bus.
The Memory 603 may be, but is not limited to, ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, RAM (Random Access Memory ) or other type of dynamic storage device that can store information and instructions, EEPROM (Electrically Erasable Programmable Read Only Memory ), CD-ROM (Compact Disc Read Only Memory, compact disc Read Only Memory) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
The memory 603 is used for storing application program codes for executing the present application and is controlled to be executed by the processor 601. The processor 601 is arranged to execute application code stored in the memory 603 for implementing what is shown in the foregoing method embodiments.
Among them, electronic devices include, but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and stationary terminals such as digital TVs, desktop computers, and the like. But may also be a server or the like. The electronic device shown in fig. 6 is only an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present application.
The present application provides a computer readable storage medium having a computer program stored thereon, which when run on a computer, causes the computer to perform the corresponding method embodiments described above.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
The foregoing is only a partial embodiment of the present application, and it should be noted that, for a person skilled in the art, several improvements and modifications can be made without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A highway power line fault detection method, comprising:
determining hidden danger line partitions from a patrol line model according to hidden danger characteristics, wherein the patrol line model is a three-dimensional model corresponding to a power line to be detected, and the power line to be detected can be divided into at least one line partition;
acquiring a field image corresponding to the hidden danger line partition, and determining hidden danger information corresponding to the hidden danger feature according to the field image;
determining initial display interface information of the hidden danger characteristics based on the hidden danger information, wherein the initial display interface information comprises an initial display interface size of a window simulation model and an initial display position of the window simulation model in a routing inspection line model, and the window simulation model is a three-dimensional model corresponding to the hidden danger line partition;
acquiring weather features within a preset time period, and adding the hidden danger information and the weather features into the window simulation model for simulation to obtain a simulation image;
The method comprises the steps of obtaining a three-dimensional simulation result of the window simulation model in the preset time period, matching the three-dimensional simulation result with hidden danger information, determining a hidden danger change value, adjusting initial interface display information according to the hidden danger change value to obtain target interface display information, and displaying the simulation image according to the target interface display information.
2. The highway power line fault detection method according to claim 1, further comprising:
acquiring a route to be detected and a first preset height, and generating a first inspection instruction according to the route to be detected and the first preset height, wherein the first inspection instruction is used for controlling inspection equipment to acquire images of the route to be detected according to the first preset height so as to obtain an initial inspection image;
when the initial inspection image contains preset features, marking the preset features contained in the initial inspection image to obtain marking positions corresponding to each preset feature;
generating a second inspection instruction according to the mark position and the number of each preset feature, wherein the second inspection instruction is used for controlling inspection equipment to acquire images of the route to be detected according to the second inspection instruction, so as to obtain a final inspection image;
And carrying out hidden danger feature recognition on the final inspection image.
3. The method for detecting a fault in a highway power line according to claim 2, wherein the generating a second inspection command according to the marking position and the number of each preset feature includes:
dividing the route to be detected based on the mark position of each preset feature to obtain at least one divided detection route, and determining the mark density corresponding to each divided detection route;
and determining a second preset height and a stop position corresponding to each divided detection route based on the mark density corresponding to each divided detection route, and generating a second inspection instruction corresponding to each divided detection route based on the second preset height and the stop position corresponding to each divided detection route.
4. A highway power line fault detection method according to claim 3, wherein the dividing the route to be detected based on the marking position of each preset feature comprises:
when the patrol image contains an obstacle identifier, historical fault information is acquired, and an influence range and an influence probability corresponding to the obstacle identifier are determined according to the historical fault information;
Determining an obstacle influence value of each preset feature according to an influence range corresponding to the obstacle identifier, the influence probability and the mark position of each preset feature in the initial dividing detection route;
determining at least one group of segmentation mark positions according to the obstacle influence value corresponding to each preset feature and the preset segmentation obstacle influence value, wherein the one group of segmentation mark positions comprise mark positions of two preset features;
and calculating a first center position corresponding to each group according to the mark position of the preset feature in each group, and dividing the power line to be detected according to the first center position corresponding to each group.
5. The method for detecting a fault in a highway power line according to claim 4, wherein determining the obstacle impact value of each preset feature according to the impact range corresponding to the obstacle identifier, the impact probability and the marking position of each preset feature in the initially divided detection route comprises:
determining at least one influence dimension according to the influence range corresponding to the obstacle identifier;
determining influence dimension probability corresponding to each influence dimension according to the influence probability;
determining adjacent influence dimensions of each marking position from at least one influence dimension according to the marking position of each preset feature, and judging whether the adjacent influence dimensions are associated influence dimensions according to the adjacent influence dimensions corresponding to each marking position, wherein the associated influence dimensions are influence object dimensions with the interval distance between the adjacent influence dimensions being lower than a preset interval distance;
If not, determining a dimension interval distance between each marking position and the adjacent influence dimension, determining the influence dimension with the smallest dimension interval distance as a target influence dimension, and determining the influence dimension probability corresponding to each target influence dimension as an obstacle influence value corresponding to a preset feature;
if so, determining adjacent influence dimensions as target influence dimensions, and determining the sum of influence dimension probabilities corresponding to the adjacent influence dimensions as obstacle influence values corresponding to preset features.
6. The method for detecting a fault in a highway power line according to claim 4, wherein after the dividing the power line to be detected according to the first center position corresponding to each group, the method further comprises:
determining boundary mark positions in each divided detection route and adjacent mark positions adjacent to the boundary mark positions according to mark positions of preset features in each divided detection route;
calculating a boundary distance between each boundary mark position and the corresponding first center position, and an adjacent distance between the boundary mark position and the corresponding adjacent mark position;
and when the boundary distance is lower than the adjacent distance, determining a second center position of the boundary mark position and the corresponding adjacent mark position, and adjusting the division detection route according to the second center position.
7. The method for detecting a fault in a highway power line according to claim 4, wherein the determining the second preset height and the stop position corresponding to each divided detection route based on the mark density corresponding to each divided detection route, and generating the second inspection instruction corresponding to each divided detection route based on the second preset height and the stop position corresponding to each divided detection route to be detected, comprises:
determining the stay position of each division detection route according to the obstacle influence value of each preset feature;
determining the patrol stay time and the second preset height corresponding to each stay position according to the mark density corresponding to each divided detection route;
and determining a second inspection instruction of each divided detection route according to the corresponding stay position, stay time length and second preset height of each divided detection route.
8. A highway power line fault detection device, comprising:
the hidden danger line partition determining module is used for determining hidden danger line partitions from the inspection line model according to hidden danger characteristics, wherein the inspection line model is a three-dimensional model corresponding to the power line to be detected, and the power line to be detected can be divided into at least one line partition;
The hidden danger information determining module is used for acquiring a field image corresponding to the hidden danger line partition, and determining hidden danger information corresponding to the hidden danger feature according to the field image;
the interface information determining module is used for determining initial display interface information of the hidden danger characteristics based on the hidden danger information, wherein the initial display interface information comprises an initial display interface size of a window simulation model and an initial display position of the window simulation model in a routing inspection line model, and the window simulation model is a three-dimensional model corresponding to the hidden danger line partition;
the simulation image determining module is used for acquiring weather features in a preset time period, and adding the hidden danger information and the weather features into the window simulation model for simulation to obtain a simulation image;
the image display module is used for obtaining a three-dimensional simulation result of the window simulation model in the preset time period, matching the three-dimensional simulation result with the hidden danger information, determining a hidden danger change value, adjusting the initial interface display information according to the hidden danger change value to obtain target interface display information, and displaying the simulation image according to the target interface display information.
9. An electronic device, comprising:
at least one processor;
a memory;
at least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application configured to: a highway power line fault detection method as claimed in any one of claims 1 to 7.
10. A computer-readable storage medium, comprising: a computer program which can be loaded by a processor and which performs a method of road power line fault detection as claimed in any one of claims 1 to 7.
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