CN113922500A - Power transmission line state multi-source monitoring data access method and device - Google Patents
Power transmission line state multi-source monitoring data access method and device Download PDFInfo
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- CN113922500A CN113922500A CN202111089627.5A CN202111089627A CN113922500A CN 113922500 A CN113922500 A CN 113922500A CN 202111089627 A CN202111089627 A CN 202111089627A CN 113922500 A CN113922500 A CN 113922500A
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00002—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by monitoring
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
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Abstract
The invention provides a method and a device for accessing multi-source monitoring data of a power transmission line state, wherein the method for accessing the multi-source monitoring data of the power transmission line state comprises the following steps: s1: receiving state data of the power transmission line; s2: cleaning the power transmission line state data to obtain effective data of the power transmission line state; s3: fusing the effective data of the power transmission line state to obtain a power transmission line state data set; and S4: and sending an alarm in response to the terminal recognizing that the transmission line state data set is abnormal.
Description
Technical Field
The invention relates to the technical field of data access, in particular to a multi-source monitoring data access method and device for a power transmission line state.
Background
At present, on-line monitoring devices for images, videos, microclimates, temperature measurement, tower inclination, icing and the like are mutually independent, are distributed in systems, are incomplete in information, are complex in terminal data access mode, lack of unified management and control and are redundant in device communication flow. Based on the current situation, a comprehensive online monitoring mode combining multiple online monitoring data needs to be developed.
In order to solve the above-mentioned drawbacks of the prior art, it is necessary to provide a method and an apparatus for accessing multi-source monitoring data of a power transmission line state.
Disclosure of Invention
In view of the above, the present invention provides a method and an apparatus for accessing multi-source monitoring data of a power transmission line state, so as to at least partially solve the problems of the prior art or provide an alternative data access method.
In order to achieve the above object, a first aspect of the present invention provides an access method for multi-source monitoring data of a power transmission line state, where the access method for multi-source monitoring data of a power transmission line state includes:
s1: receiving state data of the power transmission line;
s2: cleaning the power transmission line state data to obtain effective data of the power transmission line state;
s3: fusing the effective data of the power transmission line state to obtain a power transmission line state data set; and
s4: and sending an alarm in response to the terminal recognizing that the transmission line state data set is abnormal.
The above power transmission line state multi-source monitoring data access method, wherein in step S1, the power transmission line state data includes: image data, microclimate data, temperature data and tower angle data.
The above power transmission line state multi-source monitoring data access method, wherein in step S2, the step of cleaning the power transmission line state data includes:
s21: calculating a first arithmetic mean or a first geometric mean X of the measurement parameter samples of the transmission line state datamean1Finding the maximum value X of the measurement parameter samplemaxLet Xmean1Substitution of XmaxTo obtain a first updated measurement parameter sample;
s22: calculating a second arithmetic mean or a second geometric mean X of the first updated measured parameter samplesmean2Finding the minimum value X of the measurement parameter sample after the first updateminLet Xmean2Substitution of XminTo obtain a second updated measurement parameter sample;
s23: calculating a third arithmetic mean or a third geometric mean X of the second updated sample of the measured parametermean3And solving the variance e of the measurement parameter sample after the second updating, and if the variance e is greater than the preset variance threshold, iterating to the step S21 until the variance e is less than or equal to the preset variance threshold so as to obtain the effective data of the power transmission line state.
The above power transmission line state multi-source monitoring data access method, wherein in step S3, the fusing the power transmission line state valid data includes: data layer fusion, feature layer fusion, and decision layer fusion.
The power transmission line state multi-source monitoring data access method comprises the following steps between the step S3 and the step S4: and sending the power transmission line state data set to a terminal for identification.
In the above power transmission line state multi-source monitoring data access method, in step S4, in response to the terminal recognizing that the power transmission line state data set is normal, the power transmission line state data set is sent to a backend platform.
A second aspect of the present invention provides a multi-source monitoring data access device for a power transmission line state, which is characterized by comprising:
the receiving module is used for receiving the state data of the power transmission line;
the cleaning module is used for cleaning the power transmission line state data to obtain effective data of the power transmission line state;
the fusion module is used for fusing the effective data of the power transmission line state to obtain a power transmission line state data set; and
and the response module is used for responding to the terminal to identify that the power transmission line state data set is abnormal and sending an alarm.
The above multi-source monitoring data access device for the state of the power transmission line, wherein the cleaning of the state data of the power transmission line comprises:
calculating a first arithmetic mean of the measured parameter samples of the transmission line state data orFirst geometric mean value Xmean1Finding the maximum value X of the measurement parameter samplemaxLet Xmean1Substitution of XmaxTo obtain a first updated measurement parameter sample;
calculating a second arithmetic mean or a second geometric mean X of the first updated measured parameter samplesmean2Finding the minimum value X of the measurement parameter sample after the first updateminLet Xmean2Substitution of XminTo obtain a second updated measurement parameter sample;
calculating a third arithmetic mean or a third geometric mean X of the second updated sample of the measured parametermean3And solving the variance e of the measurement parameter sample after the second updating, and if the variance e is greater than the preset variance threshold, iterating to the step S21 until the variance e is less than or equal to the preset variance threshold so as to obtain the effective data of the power transmission line state.
A third aspect of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the above-described multi-source monitoring data access method for power transmission line status when executing the computer program.
A fourth aspect of the present invention provides a computer-readable storage medium, which stores a computer program, where the computer program, when executed by a processor, implements the steps of the above-mentioned power transmission line state multi-source monitoring data access method.
The features mentioned above can be combined in various suitable ways or replaced by equivalent features as long as the object of the invention is achieved.
Drawings
Fig. 1 is a flowchart of a multi-source monitoring data access method for a power transmission line state according to an embodiment of the present invention;
FIG. 2 is a schematic block diagram of multi-sensor data fusion target recognition according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a multi-sensor data fusion system based on a support vector machine according to an embodiment of the present invention;
fig. 4 is a flowchart of a multi-source monitoring data access method for a power transmission line state according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a multi-source monitoring data access device for a power transmission line state according to an embodiment of the present invention; and
fig. 6 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to specific embodiments and the accompanying drawings.
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative only and should not be construed as limiting the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are used for distinguishing two entities with the same name but different names or different parameters, and it should be noted that "first" and "second" are merely for convenience of description and should not be construed as limitations of the embodiments of the present invention, and they are not described in any more detail in the following embodiments.
The technical solution of the embodiments of the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the present invention provides a method for accessing multi-source monitoring data of a power transmission line state, wherein the method for accessing multi-source monitoring data of a power transmission line state of the present invention comprises:
s1: and receiving the state data of the power transmission line.
In a specific embodiment, the data collection uses each monitoring unit on the transmission line to collect data. The image monitoring and monitoring unit is a set of video online monitoring device designed for line patrol and remote monitoring of the power transmission line iron tower, and a monitoring camera on the tower captures images of specific areas such as the power transmission line iron tower, a line corridor and the like to obtain image data. The microclimate monitoring unit monitors local meteorological environment of a power transmission line corridor, and the front-end monitoring device monitors meteorological parameters such as line region temperature, humidity, wind direction, wind speed, air pressure and rainfall in real time. And the wire temperature monitoring unit monitors the wire temperature in real time according to the dynamic capacity increasing theory of the power transmission line. And (4) acquiring various numerical values of the tower through gps positioning and calculating the inclination of the tower.
S2: and cleaning the transmission line state data to obtain the effective data of the transmission line state.
In particular, in the large amount of data obtained from the sensors, it is inevitable that some abnormal values occur due to various uncertain factors, and the reasons for the generation of the abnormal values are many, such as instantaneous or intermittent measurement system failure or electromagnetic interference. The main purpose of data analysis is to reject these outliers. At present, the outlier rejection method widely applied in engineering is basically a rhendard criterion, a grabbs criterion, a dixon criterion, a schowerler criterion, and an aecc method. However, most of these methods need to pre-determine the statistical characteristics of the measured data, such as the sample distribution rule, and have certain requirements on the number of sample points, such as when the measured data samples are uniformly distributed, the rhinestone criterion and the aecc method will fail. Therefore, the use of these methods is limited in cases where the statistical properties of the measured parameters in flight tests are not known in advance. Therefore, the method and the device adopt a steady-state data processing algorithm based on mean iteration, do not need to estimate the probability distribution of the measured parameter samples, avoid the complex calculation process of some traditional algorithms, and are suitable for data preprocessing of power transmission line data monitoring.
The mean value iteration method adopted by the method does not need to estimate the probability distribution of the measured parameter samples, the number of data sample points is not limited, the steady-state data can be effectively processed, and the authenticity of the data is improved. The mean iteration method adopts mean iteration to update the maximum value and the minimum value in the measured data, so that the influence of an abnormal value on the whole steady-state data in each iteration process is reduced until the precision is converged. And if the number of iterations is enough, the abnormal value in the data can be rejected, and if the abnormal value cannot be converged, the measurement parameters can be evaluated according to the number of iterations and the iteration curve to judge whether the stable-segment data has unacceptable jitter. The specific algorithm steps are as follows:
s21: calculating a first arithmetic mean or a first geometric mean X of measured parameter samples of transmission line state datamean1Finding the maximum value X of the measured parameter samplemaxLet Xmean1Substitution of XmaxTo obtain a first updated measurement parameter sample;
s22: calculating a second arithmetic mean or a second geometric mean X of the first updated measured parameter samplesmean2Finding out the minimum value X of the first updated measurement parameter sampleminLet Xmean2Substitution of XminTo obtain a second updated measurement parameter sample;
s23: calculating a third arithmetic mean or a third geometric mean X of the second updated sample of the measured parametermean3And solving the variance e of the measurement parameter sample after the second updating, and if the variance e is greater than the preset variance threshold, iterating to the step S21 until the variance e is less than or equal to the preset variance threshold so as to obtain the effective data of the power transmission line state.
S3: and fusing the effective data of the transmission line state to obtain a transmission line state data set.
In one embodiment, the multi-sensor data fusion system adopts a plurality of homogeneous or heterogeneous sensors for measurement and comprehensively analyzes and processes the measurement information, fully utilizes complementary and redundant characteristics in the plurality of sensors to increase the reliability of the measurement and improve the reliability and robustness of the multi-sensor data fusion system. According to the information abstraction degree, from the form of input information, the multi-sensor data fusion can be divided into three structural levels: data layer fusion, feature layer fusion and decision layer fusion.
(1) The data layer fusion is to extract the characteristics of the observation data of each sensor, and belongs to low-level fusion. And fusing all the characteristic parameters to obtain a fused characteristic vector related to the target. The data size of the data level fusion processing is large, and the cost is high. And the influence of the stability of the sensor makes the data-level fusion difficult to obtain stable and consistent comprehensive information, and has great limitation.
(2) Feature layer fusion belongs to middle layer fusion. Firstly, extracting the characteristics of single sensor data to obtain a characteristic vector, and then fusing each group of characteristic information. The hierarchy is compatible with the advantages and disadvantages of data layer fusion and decision layer fusion, and has a wide application range.
(3) And the decision layer fuses high-level data fusion. The data of each sensor is preprocessed independently, and target attributes are independently decided to obtain an independent identity judgment, and then fusion is carried out to obtain an overall consistent decision result, so that the fault tolerance is good. In addition, decision-level fusion has no special requirements on original sensing information, and a heterogeneous sensor can be used, so that the application range is wide.
In the application, data layer fusion is required to be adopted for monitoring data of the part of the tower inclination. In order to accurately measure the inclination degree of the tower, more than two tower inclination sensors are generally arranged on the tower and belong to the same type of data, and the data only need to be screened and then subjected to low-level fusion. And for other different types of monitoring data, decision-making level data fusion is required, such as monitoring data of air pressure, wind speed, images and the like. The multi-sensor data fusion target recognition principle block diagram is shown in fig. 2, a single sensor firstly measures and processes attributes of a target to be recognized, received target information is collected and preprocessed to obtain a feature vector representing observation data, then feature extraction and selection are carried out, the result is used as a recognition basis, then classification recognition and subsequent processing are carried out on the target of the single sensor, information about the target identity provided by a plurality of sensors is comprehensively processed (namely data alignment and association are carried out), more effective and more accurate identity estimation and classification judgment are generated compared with any single sensor in the system, and finally the recognition result of the target is stably and effectively given.
In order to solve the problems that the Kalman filter is low in tracking accuracy under the nonlinear and non-Gaussian conditions and the particle filter algorithm is high in calculation complexity, algorithms combining Kalman filtering and particle filtering emerge. The application adopts a multi-sensor data fusion system based on a support vector machine, as shown in figure 3.
The algorithm adopts a compact combination mode, a support vector machine is used as an intermediate layer, an environment variable and a measurement variance normalization vector are used as the input of the SVM, the environment variable describes the usability of sensor data, the measurement variance normalization vector reflects the measurement precision of the sensor, and the output of the SVM is the trust degree of the sensor. And carrying out real-time training by using a known training sample, and carrying out online estimation by using real-time filter information. Support vector machines are mainly classified into two types, Support Vector Regression (SVR) and Support Vector Classification (SVC). Selecting SVR or SVC according to different system identification degrees, and using SVC classification training for discrete multi-resolution output; SVR regression training is selected for continuous output. The fusion knowledge base is an important component of the fusion system, and a proper fusion algorithm is selected according to the obtained sensor trust degree.
In one embodiment, the image monitoring unit: the image monitoring device is arranged on a line tower and consists of a front-end data acquisition unit and a state monitoring device. The front-end data acquisition unit of the image device is a high-speed dome camera. The front-end simulation high-speed dome camera converts image signals into PAL analog signals through CCD image sensor and DSP processing, the PAL analog signals are transmitted to a compression module in the device through a coaxial cable, the compression module collects and compresses the PAL signals to form a static single-frame picture of JPEG, and the rotation of the dome camera and the zooming of the optical lens are controlled by communication through an RS485 bus between the main controller and the dome camera. The on-site image signals of the power transmission line can be acquired at regular time or according to remote instructions.
In one embodiment, the microclimate monitoring unit: the microclimate monitoring unit for the power transmission line is designed for monitoring the meteorological environment of the power transmission line in a special place. The wind power generation system is arranged on a line tower to detect weather through meteorological sensors (a temperature sensor, a humidity sensor, a wind speed sensor, a wind direction sensor, a rainfall sensor and an air pressure sensor).
In a specific embodiment, the tower inclination monitoring unit: the tower can be inclined when the center of the tower deviates from the vertical position due to uneven foundation and unstable foundation sinking. Due to the fact that the high-voltage transmission line is complex in regional environment, the tower is prone to deformation, inclination and collapse caused by the influence of various factors in the operation process, and huge economic loss is caused. By utilizing the latest MEMS sensor technology and wireless communication technology, the bidirectional inclination angle (parallel to the line direction and perpendicular to the line direction) of the electric wire tower in unfavorable geological areas such as ice disasters, snow disasters, debris flows, mountain landslide and multi-occurrence areas, coal mine goafs and the like is monitored in real time.
In one embodiment, the wire temperature detection unit: the transmission line may overheat due to various factors during operation to cause a line problem, and therefore, the temperature of the transmission line needs to be monitored in real time. The lead has different temperatures due to the use of materials, and the threshold temperature of normal operation is between 50 ℃ and 200 ℃, so that the thermistor sensor is used for temperature monitoring, and the temperature measurement range of the thermistor sensor is between-40 ℃ and 400 ℃, thereby meeting the requirements of the application.
S4: and sending an alarm in response to the terminal recognizing that the transmission line state data set is abnormal.
Specifically, the power transmission line state data set is sent to a terminal for recognition, an alarm is sent out and the power transmission line state data set is sent to a rear-end platform in response to the terminal recognizing that the power transmission line state data set is abnormal, and the power transmission line state data set is sent to the rear-end platform in response to the terminal recognizing that the power transmission line state data set is normal. The terminal identifies whether the transmission line state data set has an abnormality or not is a well-known technology in the field, and a detailed trace is omitted here.
As shown in fig. 5, a second aspect of the present invention provides an access apparatus for multi-source monitoring data of power transmission line status, including:
the receiving module 10 is configured to receive power transmission line state data;
the cleaning module 20 is used for cleaning the transmission line state data to obtain effective data of the transmission line state;
the fusion module 30 is used for fusing the effective data of the transmission line state to obtain a transmission line state data set; and
and the response module 40 is used for sending an alarm in response to the terminal recognizing that the transmission line state data set is abnormal.
The detailed functions of the receiving module 10, the cleaning module 20, the fusion module 30 and the response module 40 correspond to the processes of the steps S1 to S4, and are not described herein again.
Fig. 6 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 6, the terminal device 6 of this embodiment includes: a processor 60, a memory 61 and a computer program 62 stored in the memory 61 and operable on the processor 60, for example a program for transmission line condition multi-source monitoring data access. The processor 60 executes the computer program 62 to implement the steps of the above-mentioned multi-source monitoring data access method for each power transmission line status, such as the steps S1 to S4 shown above. Alternatively, the processor 60, when executing the computer program 62, implements the functions of the various modules/units in the above-described apparatus embodiments, such as the functions of the modules 10 to 40 shown in fig. 5.
Illustratively, the computer program 62 may be divided into one or more modules/units, which are stored in the memory 61 and executed by the processor 60 to implement the present invention. One or more of the modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution of the computer program 62 in the terminal device 6.
The terminal device 6 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. Terminal device 6 may include, but is not limited to, a processor 60, a memory 61. Those skilled in the art will appreciate that fig. 6 is merely an example of a terminal device 6 and does not constitute a limitation of terminal device 6 and may include more or less components than those shown, or some components in combination, or different components, for example, the terminal device may also include input output devices, network access devices, buses, etc.
The Processor 60 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 61 may be an internal storage unit of the terminal device 6, such as a hard disk or a memory of the terminal device 6. The memory 61 may also be an external storage device of the terminal device 6, such as a plug-in hard disk provided on the terminal device 6, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like. Further, the memory 61 may also include both an internal storage unit of the terminal device 6 and an external storage device. The memory 61 is used for storing computer programs and other programs and data required by the terminal device 6. The memory 61 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments may be implemented. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of the invention, also features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.
In addition, well known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown within the provided figures for simplicity of illustration and discussion, and so as not to obscure the invention. Furthermore, devices may be shown in block diagram form in order to avoid obscuring the invention, and also in view of the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the present invention is to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the invention, it should be apparent to one skilled in the art that the invention can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.
While the present invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures (e.g., dynamic ram (dram)) may use the discussed embodiments.
Those skilled in the art will appreciate that the present invention includes apparatus directed to performing one or more of the operations described in the present application. These devices may be specially designed and manufactured for the required purposes, or they may comprise known devices in general-purpose computers. These devices have stored therein computer programs that are selectively activated or reconfigured. Such a computer program may be stored in a device (e.g., computer) readable medium, including, but not limited to, any type of disk including floppy disks, hard disks, optical disks, CD-ROMs, and magnetic-optical disks, ROMs (Read-Only memories), RAMs (Random Access memories), EPROMs (Erasable Programmable Read-Only memories), EEPROMs (Electrically Erasable Programmable Read-Only memories), flash memories, magnetic cards, or optical cards, or any type of media suitable for storing electronic instructions, and each coupled to a bus. That is, a readable medium includes any medium that stores or transmits information in a form readable by a device (e.g., a computer). It will be understood by those within the art that each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by computer program instructions. Those skilled in the art will appreciate that the computer program instructions may be implemented by a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, implement the features specified in the block or blocks of the block diagrams and/or flowchart illustrations of the present disclosure.
Those of skill in the art will appreciate that various operations, methods, steps in the processes, acts, or solutions discussed in the present application may be alternated, modified, combined, or deleted. Further, various operations, methods, steps in the flows, which have been discussed in the present application, may be interchanged, modified, rearranged, decomposed, combined, or eliminated. Further, steps, measures, schemes in the various operations, methods, procedures disclosed in the prior art and the present invention can also be alternated, changed, rearranged, decomposed, combined, or deleted. It should be understood by one of ordinary skill in the art that the above discussion of any embodiment is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the idea of the invention, also features in the above embodiments or in different embodiments may be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity. Therefore, any omissions, modifications, substitutions, improvements and the like that may be made without departing from the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The power transmission line state multi-source monitoring data access method is characterized by comprising the following steps:
s1: receiving state data of the power transmission line;
s2: cleaning the power transmission line state data to obtain effective data of the power transmission line state;
s3: fusing the effective data of the power transmission line state to obtain a power transmission line state data set; and
s4: and sending an alarm in response to the terminal recognizing that the transmission line state data set is abnormal.
2. The multi-source monitoring data access method for the power transmission line state according to claim 1, wherein in step S1, the power transmission line state data includes: image data, microclimate data, temperature data and tower angle data.
3. The multi-source monitoring data access method for the power transmission line state according to claim 1, wherein in step S2, the step of cleaning the power transmission line state data includes:
s21: calculating a first arithmetic mean or a first geometric mean X of the measurement parameter samples of the transmission line state datamean1Finding samples of said measured parametersMaximum value XmaxLet Xmean1Substitution of XmaxTo obtain a first updated measurement parameter sample;
s22: calculating a second arithmetic mean or a second geometric mean X of the first updated measured parameter samplesmean2Finding the minimum value X of the measurement parameter sample after the first updateminLet Xmean2Substitution of XminTo obtain a second updated measurement parameter sample;
s23: calculating a third arithmetic mean or a third geometric mean X of the second updated sample of the measured parametermean3And solving the variance e of the measurement parameter sample after the second updating, and if the variance e is greater than the preset variance threshold, iterating to the step S21 until the variance e is less than or equal to the preset variance threshold so as to obtain the effective data of the power transmission line state.
4. The multi-source monitoring data access method for the power transmission line state according to claim 3, wherein in step S3, the fusing the valid data for the power transmission line state includes: data layer fusion, feature layer fusion, and decision layer fusion.
5. The multi-source monitoring data access method for the power transmission line state according to claim 1, wherein between the step S3 and the step S4, the method comprises the following steps: and sending the power transmission line state data set to a terminal for identification.
6. The multi-source monitoring data access method for the power transmission line state according to any one of claims 1 to 5, wherein in step S4, in response to the terminal recognizing that the power transmission line state data set is normal, the power transmission line state data set is sent to a backend platform.
7. The utility model provides a transmission line state multisource monitoring data access device which characterized in that includes:
the receiving module is used for receiving the state data of the power transmission line;
the cleaning module is used for cleaning the power transmission line state data to obtain effective data of the power transmission line state;
the fusion module is used for fusing the effective data of the power transmission line state to obtain a power transmission line state data set; and
and the response module is used for responding to the terminal to identify that the power transmission line state data set is abnormal and sending an alarm.
8. The multi-source monitoring data access device for the power transmission line state according to claim 7, wherein the cleaning of the power transmission line state data comprises:
calculating a first arithmetic mean or a first geometric mean X of the measurement parameter samples of the transmission line state datamean1Finding the maximum value X of the measurement parameter samplemaxLet Xmean1Substitution of XmaxTo obtain a first updated measurement parameter sample;
calculating a second arithmetic mean or a second geometric mean X of the first updated measured parameter samplesmean2Finding the minimum value X of the measurement parameter sample after the first updateminLet Xmean2Substitution of XminTo obtain a second updated measurement parameter sample;
calculating a third arithmetic mean or a third geometric mean X of the second updated sample of the measured parametermean3And solving the variance e of the measurement parameter sample after the second updating, and if the variance e is greater than the preset variance threshold, iterating to the step S21 until the variance e is less than or equal to the preset variance threshold so as to obtain the effective data of the power transmission line state.
9. Terminal equipment, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the multi-source monitoring data access method for power transmission line status according to any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the steps of the transmission line status multi-source monitoring data access method according to any one of claims 1 to 6.
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