CN113888483A - Insulator damage detection method, system and medium - Google Patents
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Abstract
The embodiment of the invention discloses a method, a system and a medium for detecting damage of an insulator, wherein the method comprises the following steps: acquiring real-time image or video data of the insulator and corresponding position information; detecting and analyzing image or video data based on a small sample insulator multi-scale expansion cascade detection model, positioning an insulator on a picture, and evaluating the damage state of the insulator; and outputting the insulator damage state evaluation result containing the position information. According to the embodiment of the invention, the detection efficiency of the damage condition of the insulator of the power transmission line can be improved, and the power utilization safety is ensured.
Description
Technical Field
The invention relates to an insulator monitoring system, in particular to a method, a system and a medium for detecting damage of an insulator.
Background
The insulator is an indispensable electrical insulation and support control in the transmission line, and when the insulator breaks down, the electric wire which loses support and protection is easy to contact with other electric wires and an electric tower, so that the transmission line is short-circuited, large-range power failure and other accidents are caused, and the electricity utilization safety is seriously damaged.
The power transmission line equipment has wide distribution, a large number, long mileage and complex environment, the insulator is also one of components and parts which are easy to break down in the power transmission line, the circuit insulator detection and maintenance at the present stage is still mainly performed on-site inspection and feedback maintenance by a line maintenance department manually and periodically, the detection precision and the maintenance efficiency are low in the mode, the waste of a large amount of manpower and resources is caused, the safety of inspection personnel cannot be guaranteed, and an accurate and efficient monitoring and processing system is urgently needed.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides an insulator damage detection method which can solve the problems of low efficiency and high labor cost of the existing insulator monitoring mode of a power transmission line.
The invention also provides an insulator damage detection system using the insulator damage detection method.
The invention also provides a computer readable storage medium for implementing the insulator damage detection method.
According to the insulator damage detection method of the embodiment of the first aspect of the invention, the method comprises the following steps: acquiring real-time image or video data of the insulator and corresponding position information; detecting and analyzing image or video data based on a small sample insulator multi-scale expansion cascade detection model, positioning an insulator on a picture, and evaluating the damage state of the insulator; and outputting the insulator damage state evaluation result containing the position information.
The insulator damage detection method provided by the embodiment of the invention at least has the following beneficial effects: according to the insulator damage detection method, real-time insulator image/video data are obtained, and through small-sample insulator multi-scale expansion cascade detection model detection analysis, the requirement of manual regular on-site inspection can be reduced, the detection precision and the maintenance efficiency are improved, and waste of a large amount of manpower and resources is avoided.
According to some embodiments of the invention, the method further comprises: training the insulator multi-scale expansion cascade model through insulator defect data to obtain the small-sample insulator multi-scale expansion cascade detection model, and specifically comprising the following steps of: acquiring insulator defect data, and constructing insulator marking data meeting the requirements according to the marking requirements of the insulator defect detection algorithm; wherein, the insulator mark divide into the two-stage: marking an insulator string and marking an insulator defect; constructing an insulator multi-scale expansion cascade model, wherein the model is formed by adding a multi-scale expansion enhancement branch with FPN on the basis of a Fast-RCNN model, and the branch enriches the object scale in a training network by using multi-scale positive sample expansion; pre-training the insulator multi-scale expansion cascading model by using other domain data to obtain a pre-training model; wherein the other domain data comprises coco and/or voc; performing data enhancement on the insulator marking data to obtain enhanced insulator marking data; respectively carrying out fine adjustment on the pre-training model by using the enhanced insulator marking data of different levels to obtain an insulator string detection model and an insulator defect detection model; and cascading the insulator string detection model and the insulator defect detection model to obtain the small-sample insulator multi-scale expansion cascading detection model.
According to some embodiments of the present invention, the data enhancement of the insulator marking data at least includes one of the following steps: rotation, inversion, color transformation, brightness transformation, and contrast transformation.
According to some embodiments of the invention, the small-sample insulator multi-scale extended cascade detection model comprises an insulator string detection model and an insulator defect detection model; the detection and analysis of the analyzed and processed data based on the small sample insulator multi-scale expansion cascade detection model comprises the following steps: during detection, inputting a picture to be detected, detecting an insulator string in the picture to be detected based on the insulator string detection model, and obtaining a local picture of the detected insulator string; detecting the insulator pieces in the insulator string local picture based on the insulator defect detection model to obtain the state of the insulator pieces in the insulator string and outputting the defect position; and converting the defect position into the picture to be detected, and outputting a detection result.
According to some embodiments of the invention, the outputting the insulator damage state evaluation result including the position information comprises: and after the damage state of the insulator is evaluated, recording the insulator detection result to a log by combining the position information, and sending abnormal information to an abnormal processing platform.
According to some embodiments of the invention, the outputting the insulator damage state evaluation result including the position information further comprises: and visualizing the abnormal information, and displaying the position and the damage condition of the abnormal insulator on the terminal.
According to the insulator damage detection system of the embodiment of the second aspect of the present invention, the insulator damage detection method of any one of the embodiments of the first aspect of the present invention includes: the image/video acquisition unit is used for acquiring real-time image or video data of the insulator and corresponding position information; the cloud data processing platform is used for detecting and analyzing the image or video data based on the small-sample insulator multi-scale expansion cascade detection model, positioning the insulator on the image, evaluating the damage state of the insulator and recording the evaluation result into a log; and the exception handling platform is used for receiving the log sent by the cloud data processing platform and visualizing the log.
The insulator damage detection system provided by the embodiment of the invention at least has the following beneficial effects: the insulator damage detection system of the embodiment of the invention can reduce the requirement of manual regular on-site inspection by acquiring real-time insulator image/video data and performing multi-scale expansion cascade detection model detection analysis on the small sample insulator, improve the detection precision and the maintenance efficiency and avoid the waste of a large amount of manpower and resources.
According to some embodiments of the invention, the image/video acquisition unit comprises a tower footing data acquisition module and/or an unmanned aerial vehicle data acquisition module, the tower footing data acquisition module comprising a camera, a tower footing and a tower footing communication module; the unmanned aerial vehicle data acquisition module comprises a camera, an unmanned aerial vehicle, a GPS/radar module and a communication module.
According to some embodiments of the invention, the exception handling platform comprises a terminal machine carrying an alarm control system, including a PC and/or a mobile terminal; and the abnormity processing platform is used for displaying the health condition of the insulators in each current region, and warning the position of a damaged insulator machine to visualize the damage condition.
The computer-readable storage medium according to an embodiment of the third aspect of the invention has stored thereon a computer program which, when executed by a processor, performs the method of any of the embodiments of the first aspect of the invention.
All the advantages of the first aspect of the present invention are achieved because the computer-readable storage medium of the embodiment of the present invention stores thereon computer-executable instructions for executing the insulator damage detection method according to any one of the first aspect of the present invention.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic flow chart of a method according to an embodiment of the present invention.
Fig. 2 is a schematic flow chart of an insulator inspection method according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a training process of a small-sample insulator multi-scale expansion cascade detection model according to an embodiment of the present invention.
Fig. 4 is a schematic flow chart of detecting a damaged state of an insulator based on a small-sample multi-scale extended model of the insulator according to the embodiment of the present invention.
Fig. 5 is a block diagram of a schematic module of an insulator damage detection system according to an embodiment of the present invention.
Fig. 6 is a block diagram of an image/video capture unit according to an embodiment of the present invention.
FIG. 7 is a block diagram of an exception handling platform according to an embodiment of the present invention.
Detailed Description
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 accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and more than, less than, more than, etc. are understood as excluding the present number, and more than, less than, etc. are understood as including the present number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.
Referring to fig. 1, an embodiment of the present invention provides an insulator damage detection method, including the following steps: acquiring real-time image or video data of the insulator and corresponding position information; detecting and analyzing image or video data based on a small sample insulator multi-scale expansion cascade detection model, positioning an insulator on a picture, and evaluating the damage state of the insulator; and outputting the insulator damage state evaluation result containing the position information.
Referring to fig. 2, the real-time image or video data of the acquisition insulator and the positional information that corresponds in this embodiment can obtain or use unmanned aerial vehicle camera module to patrol and examine the circuit through the fixed camera module of column foot and acquire, need not artifical the collection of observing on the spot, have also reduced the human cost by a wide margin when having promoted observation efficiency. The method comprises the steps that detection analysis is carried out on image or video data based on a small-sample insulator multi-scale expansion cascade detection model, the acquired image/video data need to be uploaded to a cloud data processing platform in real time through a communication module, and the cloud data processing platform carries out analysis processing on the received image/video data and position information so as to guarantee the effectiveness of model input; the cloud data processing platform uses a small sample insulator multi-scale expansion cascade detection model to detect and analyze the processed data, rapidly positions the insulator in the picture and evaluates the damage state of the insulator. The immediacy and the effectiveness of the data are ensured by the powerful computing power of the cloud processing platform. The cloud platform carrying detection model is used for replacing manual judgment, and the accuracy and the detection efficiency of the monitoring feedback system are effectively improved. The insulator damage state evaluation result with the output containing the position information in the embodiment can be visualized by the exception handling platform, the position and damage condition of the abnormal insulator are displayed on the terminal, and maintenance personnel can timely carry out fixed-point maintenance according to the result detected by the terminal, so that the response time is greatly shortened, and the maintenance efficiency is improved.
In some embodiments, after the insulator damage state is evaluated, the insulator detection result is recorded in a log by combining with the position information, and the abnormal information is sent to the abnormal processing platform.
In some embodiments, the abnormal information is visualized, and the position and damage condition of the abnormal insulator are displayed on the terminal.
Referring to fig. 3, in some embodiments, the training process of the small-sample insulator multi-scale expansion cascading detection model of the embodiments of the present invention includes the following steps:
(1) the method comprises the following steps of obtaining insulator defect data by using an image/video obtaining unit, constructing insulator small sample marking data meeting requirements according to algorithm marking requirements, and dividing insulator marking into two stages: marking an insulator string and marking the defects of the insulator.
(2) An insulator multi-scale expansion cascade model is constructed, a multi-scale expansion enhancement branch with FPN is added to the model on the basis of a Fast-RCNN model, the branch enriches the object scale in a training network by using multi-scale positive sample expansion, and the problem of sparse sample space scale distribution in small sample learning is solved. The branch generates multi-scale positive samples as a target pyramid and refines the multi-scale feature prediction at various scales through Fpn networks shared with the main branch.
(3) And (3) pre-training the model in the step (2) by using other domain data (such as coco, voc and the like) to obtain a pre-trained model A.
(4) And (3) performing data enhancement on the insulator marking data obtained in the step (1), wherein the data enhancement can comprise rotation, overturning, color transformation, brightness transformation, contrast transformation and the like, rapidly expanding a data set, and ensuring that the trained model has better generalization on different light rays and different scenes. And respectively using the enhanced insulator data (insulator strings and insulators) at different stages to finely tune the pre-training model A so as to obtain the detection capability in a new vertical field, and obtain a new detection model B and a new detection model C.
(5) And (5) cascading the detection models B, C obtained in the step (4) to obtain a complete insulator small sample multi-scale expansion model.
Referring to fig. 4, the method for detecting the damaged state of the insulator based on the insulator small sample multi-scale expansion model in the embodiment of the invention comprises the following steps: during detection, inputting a whole picture a to be detected, detecting an insulator string in the picture a by using an insulator string detection model B, obtaining a local picture B of the detected insulator string, and outputting the picture B; detecting the insulator sheet in the diagram b by using an insulator defect detection model C to obtain the state of the insulator sheet in the insulator string and outputting a defect position C; and converting the defect position c into the original image a, and finally outputting a final detection result.
Referring to fig. 5, the insulator damage detection system according to the embodiment of the present invention includes an image/video acquisition unit, a cloud data processing platform unit, and an exception handling platform unit. The image/video acquisition unit is mainly responsible for acquiring and uploading image and video data; the cloud data processing platform is mainly used for processing the uploaded data through an insulator defect detection algorithm, judging the state of the insulator, recording a log and reporting defect information; the abnormal processing platform can receive the abnormal defect information of the cloud end and check the abnormal information and schedule maintenance personnel.
Referring to fig. 6, the module of the image/video acquisition unit is mainly composed of a camera and a camera-mounted platform. If the tower footing data acquisition module consists of a camera, a tower footing and a tower footing communication module; the unmanned aerial vehicle data acquisition module consists of a camera, an unmanned aerial vehicle, a gps/radar module and a communication module. This unit uploads the video information of camera detectable within range to cloud data processing platform through communication module and handles, need not artifical and observes the collection on the spot, has also reduced the human cost by a wide margin when having promoted observation efficiency.
The cloud data processing platform is mainly provided with a data analysis module and a self-developed small sample multi-scale expansion detection cascade model, and the model can obtain a monitoring result with higher precision under the condition of a small amount of samples. The cloud platform has a great amount of computing power, can accurately process massive monitoring uploading data in a short time, records the result into a log, and transmits the result to the terminal of the exception handling platform through the internet. The cloud platform carrying detection model is used for replacing manual judgment, and the accuracy and the detection efficiency of the monitoring feedback system are effectively improved.
Referring to fig. 7, the abnormality processing platform is mainly various terminal devices equipped with an alarm control system, and mainly includes a pc and a mobile terminal. The abnormal processing platform terminal can visualize the abnormal log of the cloud platform, display the health condition of the insulators in each current area, warn the damaged insulators and the positions of the damaged insulators, and further visualize the damaged conditions.
Although specific embodiments have been described herein, those of ordinary skill in the art will recognize that many other modifications or alternative embodiments are equally within the scope of this disclosure. For example, any of the functions and/or processing capabilities described in connection with a particular device or component may be performed by any other device or component. In addition, while various illustrative implementations and architectures have been described in accordance with embodiments of the present disclosure, those of ordinary skill in the art will recognize that many other modifications of the illustrative implementations and architectures described herein are also within the scope of the present disclosure.
It should be recognized that the method steps in embodiments of the present invention may be embodied or carried out by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer readable memory. The method may use standard programming techniques. Each program may be implemented in a high level procedural or object oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Furthermore, the program can be run on a programmed application specific integrated circuit for this purpose.
Further, the operations of processes described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and/or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented by hardware or combinations thereof as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more microprocessors. The computer program includes a plurality of instructions executable by one or more microprocessors.
Further, the method may be implemented in any type of computing platform operatively connected to a suitable interface, including but not limited to a personal computer, mini computer, mainframe, workstation, networked or distributed computing environment, separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, and the like. Aspects of the invention may be embodied in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, optically read and/or write storage medium, RAM, ROM, or the like, such that it may be read by a programmable computer, which when read by the storage medium or device, is operative to configure and operate the computer to perform the procedures described herein. Further, the machine-readable code, or portions thereof, may be transmitted over a wired or wireless network. The invention described herein includes these and other different types of non-transitory computer-readable storage media when such media include instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor. The invention also includes the computer itself when programmed according to the methods and techniques described herein.
A computer program can be applied to input data to perform the functions described herein to transform the input data to generate output data that is stored to non-volatile memory. The output information may also be applied to one or more output devices, such as a display. In a preferred embodiment of the invention, the transformed data represents physical and tangible objects, including particular visual depictions of physical and tangible objects produced on a display. The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention.
Claims (10)
1. An insulator damage detection method is characterized by comprising the following steps:
acquiring real-time image or video data of the insulator and corresponding position information;
detecting and analyzing image or video data based on a small sample insulator multi-scale expansion cascade detection model, positioning an insulator on a picture, and evaluating the damage state of the insulator;
and outputting the insulator damage state evaluation result containing the position information.
2. The insulator damage detection method according to claim 1, further comprising: training the insulator multi-scale expansion cascade model through insulator defect data to obtain the small-sample insulator multi-scale expansion cascade detection model, and specifically comprising the following steps of:
acquiring insulator defect data, and constructing insulator marking data meeting the requirements according to the marking requirements of the insulator defect detection algorithm; wherein, the insulator mark divide into the two-stage: marking an insulator string and marking an insulator defect;
constructing an insulator multi-scale expansion cascade model, wherein the model is formed by adding a multi-scale expansion enhancement branch with FPN on the basis of a Fast-RCNN model, and the branch enriches the object scale in a training network by using multi-scale positive sample expansion;
pre-training the insulator multi-scale expansion cascading model by using other domain data to obtain a pre-training model; wherein the other domain data comprises coco and/or voc;
performing data enhancement on the insulator marking data to obtain enhanced insulator marking data;
respectively carrying out fine adjustment on the pre-training model by using the enhanced insulator marking data of different levels to obtain an insulator string detection model and an insulator defect detection model;
and cascading the insulator string detection model and the insulator defect detection model to obtain the small-sample insulator multi-scale expansion cascading detection model.
3. The insulator damage detection method according to claim 2, wherein the data enhancement of the insulator marking data at least comprises one of the following steps: rotation, inversion, color transformation, brightness transformation, and contrast transformation.
4. The insulator damage detection method according to claim 1, wherein the small-sample insulator multi-scale extended cascade detection model comprises an insulator string detection model and an insulator defect detection model; the detection and analysis of the image or video data based on the small sample insulator multi-scale expansion cascade detection model comprises the following steps:
during detection, inputting a picture to be detected, detecting an insulator string in the picture to be detected based on the insulator string detection model, and obtaining a local picture of the detected insulator string;
detecting the insulator pieces in the insulator string local picture based on the insulator defect detection model to obtain the state of the insulator pieces in the insulator string and outputting the defect position;
and converting the defect position into the picture to be detected, and outputting a detection result.
5. The insulator damage detection method according to claim 1, wherein the outputting the insulator damage state evaluation result including the position information includes: and after the damage state of the insulator is evaluated, recording the insulator detection result to a log by combining the position information, and sending abnormal information to an abnormal processing platform.
6. The insulator breakage detection method according to claim 5, wherein the outputting the insulator breakage state evaluation result including the position information further includes: and visualizing the abnormal information, and displaying the position and the damage condition of the abnormal insulator on the terminal.
7. An insulator damage detection system using the insulator damage detection method according to any one of claims 1 to 6, comprising:
the image/video acquisition unit is used for acquiring real-time image or video data of the insulator and corresponding position information;
the cloud data processing platform is used for detecting and analyzing the image or video data based on the small-sample insulator multi-scale expansion cascade detection model, positioning the insulator on the image, evaluating the damage state of the insulator and recording the evaluation result into a log;
and the exception handling platform is used for receiving the log sent by the cloud data processing platform and visualizing the log.
8. The insulator damage detection system of claim 7, wherein the image/video acquisition unit comprises a tower-based data acquisition module and/or a drone data acquisition module,
the tower footing data acquisition module comprises a camera, a tower footing and a tower footing communication module;
the unmanned aerial vehicle data acquisition module comprises a camera, an unmanned aerial vehicle, a GPS/radar module and a communication module.
9. The insulator damage detection system according to claim 7, wherein the exception handling platform comprises a terminal machine carrying an alarm control system, including a PC and/or a mobile terminal;
and the abnormity processing platform is used for displaying the health condition of the insulators in each current region, and warning the position of a damaged insulator machine to visualize the damage condition.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method of any one of claims 1 to 6.
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