Power transmission line defect detection method and system based on multi-dimensional state matching

Abstract

The embodiment of the invention provides a power transmission line defect detection method and system based on multi-dimensional state matching, and belongs to the technical field of power transmission line operation and maintenance. The power transmission line defect detection method based on multi-dimensional state matching comprises the following steps: acquiring multi-dimensional detection data of a plurality of tower pole units in a power transmission line; performing defect classification on the multi-dimensional detection data to obtain a target defect matrix; performing correlation analysis on the multi-dimensional detection data to obtain a correlation coefficient matrix; and according to the target defect matrix and the correlation coefficient matrix, adopting a power transmission line defect detection model to detect the defects of the power transmission line. According to the power transmission line defect detection method and system, line defects can be automatically classified and identified, and the intelligent operation and maintenance level of the line is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of power transmission line operation and maintenance, and in particular to a power transmission line defect detection method and system based on multi-dimensional state matching. Background Art

[0002] There are a large number of transmission lines with a wide distribution range. They are usually located in sparsely populated areas such as hills, mountains and poor geological areas, and the operating conditions are extremely harsh. Affected by external environmental factors such as wind, icing, and temperature for a long time, the transmission lines may have defects or damage. Although such hidden dangers will not affect the equipment in a short period of time, if they are not discovered and handled in time, they will not only increase the loss of equipment and reduce efficiency, but also cause major accidents such as wire breakage, damage to substation equipment, and shutdown of distribution networks in serious cases, directly threatening the safety of public life and property. Therefore, it is crucial to carry out regular inspections or even uninterrupted monitoring of transmission lines to discover hidden dangers and faults and deal with them in a timely manner for social life and production safety.

[0003] The traditional method of power transmission line inspection relies on human vision to detect equipment anomalies. The camera deployed on the tower or drone is used to take pictures and videos of the wires, and then the back-end personnel manually identify them. This method is heavily dependent on the operating experience of the back-end personnel, and it consumes a lot of manpower and is very inefficient. In addition, the image storage and access are currently operated manually by the inspection personnel. For example, the images taken by drones are first stored locally on the drone, and then manually imported to the server after returning to the office. The timeliness is low and there is a lack of automatic defect detection technology. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a transmission line defect detection method and system based on multi-dimensional state matching, which can automatically classify and identify line defects, thereby improving the intelligent operation and maintenance level of the line.

[0005] In order to achieve the above object, an embodiment of the present invention provides a transmission line defect detection method based on multi-dimensional state matching, comprising:

[0006] Obtain multi-dimensional detection data of multiple tower units in transmission lines;

[0007] Performing defect classification on the multi-dimensional detection data to obtain a target defect matrix;

[0008] Performing correlation analysis on the multidimensional detection data to obtain a correlation coefficient matrix;

[0009] According to the target defect matrix and the correlation coefficient matrix, a transmission line defect detection model is adopted to detect transmission line defects.

[0010] Optionally, defect classification is performed on the multi-dimensional detection data to obtain a target defect matrix, including:

[0011] According to a preset defect threshold, defect classification is performed on the multi-dimensional detection data to obtain a data vector group corresponding to multiple defects;

[0012] The target defect matrix is ​​established according to a plurality of the data vector groups.

[0013] Optionally, the defect threshold includes a first defect threshold, a second defect threshold and a third defect threshold.

[0014] Optionally, correlation analysis is performed on the multidimensional detection data to obtain a correlation coefficient matrix, including:

[0015] Performing standardization processing on the multi-dimensional detection data to obtain target detection data;

[0016] According to the preset detection indicators, the target detection data is subjected to correlation analysis to obtain the correlation coefficient vector corresponding to each of the detection indicators;

[0017] The correlation coefficient matrix is ​​established according to a plurality of the correlation coefficient vectors.

[0018] Optionally, according to the target defect matrix and the correlation coefficient matrix, a transmission line defect detection model is used to detect transmission line defects, including:

[0019] Obtain current status data of the transmission line;

[0020] Using the transmission line defect detection model, according to the current state data, a defect detection value is calculated and obtained;

[0021] A matching calculation is performed based on the defect detection value, the target defect matrix and the correlation coefficient matrix to obtain a defect detection result of the transmission line.

[0022] Optionally, the multi-dimensional detection data includes at least one of image detection data, manual detection data and actual detection data.

[0023] On the other hand, the present invention further provides a power transmission line defect detection system based on multi-dimensional state matching, wherein the power transmission line defect detection system comprises a controller, and the controller is used to execute any of the power transmission line defect detection methods described above.

[0024] Through the above technical scheme, the transmission line defect detection method and system based on multi-dimensional state matching provided by the present invention obtains a target defect matrix by performing defect classification on the multi-dimensional detection data, performs correlation analysis on the multi-dimensional detection data, obtains a correlation coefficient matrix, and then detects transmission line defects based on the target defect matrix and the correlation coefficient matrix using a transmission line defect detection model, thereby realizing automatic classification and identification of transmission line defects and improving the level of intelligent operation and maintenance of the line.

[0025] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific implementations, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings:

[0027] Figure 1 is a flow chart of a power transmission line defect detection method based on multi-dimensional state matching according to an embodiment of the present invention;

[0028] Figure 2 It is a flow chart of classifying defects in multi-dimensional detection data and obtaining a target defect matrix in a transmission line defect detection method based on multi-dimensional state matching according to an embodiment of the present invention;

[0029] Figure 3 It is a flow chart of performing correlation analysis on multi-dimensional detection data to obtain a correlation coefficient matrix in a transmission line defect detection method based on multi-dimensional state matching according to an embodiment of the present invention;

[0030] Figure 4 It is a flowchart of detecting transmission line defects using a transmission line defect detection model according to a target defect matrix and a correlation coefficient matrix in a transmission line defect detection method based on multi-dimensional state matching according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The specific implementation of the embodiment of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0032] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations. In the embodiments of this application, some existing solutions in the industry such as certain software, components, and models may be mentioned, which should be considered as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0033] like Figure 1 FIG. 1 is a flow chart of a method for detecting power line defects based on multi-dimensional state matching according to an embodiment of the present invention. Figure 1 In the method for detecting defects in a power transmission line, the method may include the following steps:

[0034] In step S10, multi-dimensional detection data of multiple tower units in the transmission line is obtained;

[0035] In step S11, defect classification is performed on the multi-dimensional inspection data to obtain a target defect matrix;

[0036] In step S12, correlation analysis is performed on the multi-dimensional detection data to obtain a correlation coefficient matrix;

[0037] In step S13, the power transmission line defects are detected using a power transmission line defect detection model according to the target defect matrix and the correlation coefficient matrix.

[0038] In this Figure 1 In the method shown, step S11 is used to classify defects in the multi-dimensional detection data to obtain a target defect matrix. In this embodiment, the method for classifying defects in the multi-dimensional detection data to obtain a target defect matrix can be in various forms known to those skilled in the art. In a preferred example of the present invention, the method for classifying defects in the multi-dimensional detection data to obtain a target defect matrix can include the following: Figure 2 The steps shown. Figure 2 In the method of classifying defects in multi-dimensional inspection data and obtaining a target defect matrix, the method may include the following steps:

[0039] In step S110, defect classification is performed on the multi-dimensional detection data according to a preset defect threshold to obtain a data vector group corresponding to multiple defects;

[0040] In step S111 , a target defect matrix is ​​established according to a plurality of data vector groups.

[0041] In this embodiment, the defect threshold may be in various forms known to those skilled in the art. In a preferred example of the present invention, the defect threshold may include a first defect threshold, a second defect threshold and a third defect threshold.

[0042] In this Figure 1 In the method shown, step S12 is used to perform correlation analysis on the multidimensional detection data to obtain a correlation coefficient matrix. In this embodiment, the method for performing correlation analysis on the multidimensional detection data to obtain a correlation coefficient matrix can be in various forms known to those skilled in the art. In a preferred example of the present invention, the method for performing correlation analysis on the multidimensional detection data to obtain a correlation coefficient matrix can include the following: Figure 3 The steps shown. Figure 3 In the method of performing correlation analysis on multidimensional detection data to obtain a correlation coefficient matrix may include the following steps:

[0043] In step S120, the multi-dimensional detection data is standardized to obtain target detection data;

[0044] In step S121, according to the preset detection index, the target detection data is subjected to correlation analysis to obtain the correlation coefficient vector corresponding to each detection index;

[0045] In step S122, a correlation coefficient matrix is ​​established according to the multiple correlation coefficient vectors.

[0046] In this Figure 1 In the method shown, step S13 is used to detect transmission line defects according to the target defect matrix and the correlation coefficient matrix using the transmission line defect detection model. In this embodiment, the method for detecting transmission line defects according to the target defect matrix and the correlation coefficient matrix using the transmission line defect detection model can be in various forms known to those skilled in the art. In a preferred example of the present invention, the method for detecting transmission line defects according to the target defect matrix and the correlation coefficient matrix using the transmission line defect detection model can include the following: Figure 4 The steps shown. Figure 4 In the method, according to the target defect matrix and the correlation coefficient matrix, a transmission line defect detection model is adopted, and the method for detecting transmission line defects may include the following steps:

[0047] In step S130, current state data of the power transmission line is obtained;

[0048] In step S131, a transmission line defect detection model is used to calculate and obtain a defect detection value according to current state data;

[0049] In step S132, a matching calculation is performed based on the defect detection value, the target defect matrix and the correlation coefficient matrix to obtain the defect detection result of the transmission line.

[0050] In this embodiment, the multi-dimensional detection data may be in various forms known to those skilled in the art. In a preferred example of the present invention, the multi-dimensional detection data may include at least one of image detection data, manual detection data, and actual detection data.

[0051] On the other hand, the present invention further provides a power transmission line defect detection system based on multi-dimensional state matching, wherein the power transmission line defect detection system comprises a controller, and the controller is used to execute any of the power transmission line defect detection methods described above.

[0052] Through the above technical scheme, the transmission line defect detection method and system based on multi-dimensional state matching provided by the present invention obtains a target defect matrix by performing defect classification on the multi-dimensional detection data, performs correlation analysis on the multi-dimensional detection data, obtains a correlation coefficient matrix, and then detects transmission line defects based on the target defect matrix and the correlation coefficient matrix using a transmission line defect detection model, thereby realizing automatic classification and identification of transmission line defects and improving the level of intelligent operation and maintenance of the line.

[0053] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0054] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0055] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1A function specified in one or more boxes.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0057] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0058] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0059] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0060] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0061] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A transmission line defect detection method based on multi-dimensional state matching, characterized in that: The transmission line defect monitoring method comprises: Obtain multi-dimensional detection data of multiple tower units in transmission lines; Performing defect classification on the multi-dimensional detection data to obtain a target defect matrix; Performing correlation analysis on the multidimensional detection data to obtain a correlation coefficient matrix; According to the target defect matrix and the correlation coefficient matrix, a transmission line defect detection model is adopted to detect transmission line defects.

2. The method for detecting defects in a power transmission line according to claim 1, characterized in that: Defect classification is performed on the multi-dimensional detection data to obtain a target defect matrix, including: According to a preset defect threshold, defect classification is performed on the multi-dimensional detection data to obtain a data vector group corresponding to multiple defects; The target defect matrix is ​​established according to a plurality of the data vector groups.

3. The method for detecting defects in a power transmission line according to claim 2, characterized in that: The defect threshold includes a first defect threshold, a second defect threshold and a third defect threshold.

4. The method for detecting defects in a power transmission line according to claim 1, characterized in that: Perform correlation analysis on the multidimensional detection data to obtain a correlation coefficient matrix, including: Performing standardization processing on the multi-dimensional detection data to obtain target detection data; According to the preset detection indicators, the target detection data is subjected to correlation analysis to obtain the correlation coefficient vector corresponding to each of the detection indicators; The correlation coefficient matrix is ​​established according to a plurality of the correlation coefficient vectors.

5. The method for detecting defects in a power transmission line according to claim 1, characterized in that: According to the target defect matrix and the correlation coefficient matrix, a transmission line defect detection model is used to detect transmission line defects, including: Obtain current status data of the transmission line; Using the transmission line defect detection model, according to the current state data, a defect detection value is calculated and obtained; A matching calculation is performed based on the defect detection value, the target defect matrix and the correlation coefficient matrix to obtain a defect detection result of the transmission line.

6. The method for detecting defects in a power transmission line according to claim 1, characterized in that: The multi-dimensional detection data includes at least one of image detection data, manual detection data and actual detection data.

7. A transmission line defect detection system based on multi-dimensional state matching, characterized in that: The power transmission line defect detection system comprises a controller, and the controller is used to execute the power transmission line defect detection method according to any one of claims 1 to 6.

Images