Cable defect analysis method and system in cable laying process

Abstract

The invention discloses a cable defect analysis method and system in a cable laying process, and the method comprises the steps: dividing a current data sequence according to a preset data division strategy, obtaining at least one current data sub-sequence, and obtaining cable images of different monitoring positions according to the at least one current data sub-sequence; preprocessing the cable image to obtain a target cable image, and performing cable contour and background region segmentation on the target cable image to obtain a cable contour image; calculating a cable area based on the cable contour image, and extracting cable surface features; analyzing the surface features of the cable based on a set noise threshold, and removing noise features to obtain optimized surface features of the cable; and analyzing the surface features of the optimized cable based on the defect detection model, and outputting surface defect information. The accuracy and the real-time performance of defect detection are remarkably improved, the manual inspection cost and the leakage detection risk are reduced, and reliable guarantee is provided for safe operation of the cable.

Description

Technical Field

[0001] The present invention belongs to the technical field of cable analysis, and in particular relates to a method and system for analyzing cable defects during cable laying. Background Art

[0002] Various defects may occur in the cable during the manufacturing and installation process. Cables buried underground for a long time will suffer from local damage and aging due to the long-term effects of factors such as temperature, humidity, chemical corrosion, mechanical and physical effects, such as local aging, corrosion, copper shield damage and moisture.

[0003] In the existing technology, cable defect analysis often involves identifying a section of cable or the surface of all cables, and then obtaining cable defect information. However, in actual situations, cables often suffer from local aging, corrosion, copper shield damage, and moisture. Using a traversal identification method will actually increase the amount of identification data. Summary of the Invention

[0004] The present invention provides a cable defect analysis method and system during cable laying, which is used to solve the technical problem that cables usually have local aging, corrosion, copper shield damage and moisture, and the use of traversal identification will increase the amount of identification data.

[0005] In a first aspect, the present invention provides a method for analyzing cable defects during cable laying, comprising:

[0006] Acquire current data at each monitoring position of the cable, and sort each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position;

[0007] Dividing the current data sequence according to a preset data division strategy to obtain at least one current data subsequence, and acquiring cable images at different monitoring positions according to the at least one current data subsequence;

[0008] Preprocessing the cable image to obtain a target cable image, and segmenting the target cable image into a cable outline and a background area to obtain a cable outline image;

[0009] Calculating the cable area based on the cable contour image and extracting cable surface features;

[0010] Analyze the cable surface characteristics based on the set noise threshold, eliminate the noise characteristics, and obtain the optimized cable surface characteristics;

[0011] The optimized cable surface features are analyzed based on the defect detection model, and surface defect information is output.

[0012] In a second aspect, the present invention provides a cable defect analysis system during cable laying, comprising:

[0013] a sorting module configured to obtain current data at each monitoring position of the cable within a preset time period, and sort each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position;

[0014] a partitioning module configured to partition the current data sequence according to a preset data partitioning strategy to obtain at least one current data subsequence, and acquire cable images at different monitoring positions according to the at least one current data subsequence;

[0015] a segmentation module configured to preprocess the cable image to obtain an enhanced cable image, and segment the enhanced cable image into a cable outline and a background area to obtain a cable outline image;

[0016] a calculation module configured to calculate the cable area based on the cable contour image and extract cable surface features;

[0017] an optimization module configured to analyze the surface characteristics of the cable based on a set noise threshold, eliminate the noise characteristics, and obtain optimized cable surface characteristics;

[0018] The analysis module is configured to analyze the surface characteristics of the optimized cable based on the defect detection model and output surface defect information.

[0019] In a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the cable defect analysis method during the cable laying process of any embodiment of the present invention.

[0020] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the program instructions are executed by a processor, the processor executes the steps of the cable defect analysis method during cable laying in any embodiment of the present invention.

[0021] The cable defect analysis method and system of the present application during the cable laying process, by sorting the current data of each monitoring position of the cable into a sequence by position, and dividing the data subsequences based on a preset strategy to associate the cable images of different monitoring positions, combines image preprocessing, contour segmentation, region calculation and surface feature extraction, and finally eliminates the noise features by setting a noise threshold and uses the defect detection model to analyze the optimized surface features, thereby realizing automated and precise detection of cable defects, and being able to efficiently output key information such as defect location, type and severity, significantly improving the accuracy and real-time performance of defect detection, reducing the cost of manual inspection and the risk of missed detection, and providing reliable protection for the safe operation of the cable. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0023] Figure 1 A flowchart of a method for analyzing cable defects during cable laying provided by one embodiment of the present invention;

[0024] Figure 2 A structural block diagram of a cable defect analysis system during cable laying provided by one embodiment of the present invention;

[0025] Figure 3 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] See also Figure 1 , which shows a flow chart of a cable defect analysis method during the cable laying process of the present application.

[0028] like Figure 1 As shown, the cable defect analysis method during cable laying specifically includes the following steps:

[0029] Step S101 , obtaining current data of each monitoring position of the cable, and sorting each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position.

[0030] In this step, current data at each monitoring position of the cable is obtained; the current data at each monitoring position is sorted along the length direction of the cable to obtain a current data sequence.

[0031] Step S102 : dividing the current data sequence according to a preset data division strategy to obtain at least one current data subsequence, and acquiring cable images at different monitoring positions according to the at least one current data subsequence.

[0032] In this step, a preset sliding window is slid on the current data sequence. Each time it slides, it is judged whether a certain current data in the sliding window is greater than a preset threshold, wherein the sliding window only contains one current data each time it slides; if it is greater than the preset threshold, the certain current data is used as the cutoff current data, and all current data between two adjacent cutoff current data are divided into the same current data subsequence to obtain at least one current data subsequence; if it is not greater than the preset threshold, it is continued to judge whether another current data in the next sliding window is greater than the preset threshold until the judgment of all current data in the current data sequence is completed to obtain at least one current data subsequence; and the cable image of the monitoring position corresponding to each cutoff current in each current data subsequence is obtained.

[0033] Step S103 , preprocessing the cable image to obtain a target cable image, and segmenting the target cable image into a cable outline and a background area to obtain a cable outline image.

[0034] In this step, the cable image is denoised to obtain a target cable image; a preset dynamic sliding window is slid on the edge of the target cable image, and each time it slides, the regional edge features in the dynamic sliding window are compared with the set features for similarity; at least one regional edge feature with a similarity greater than a preset threshold is used as a cable edge feature, and it is determined whether the ratio of the cable edge feature in the current dynamic sliding window to all features in the current dynamic sliding window is greater than a preset ratio threshold; if it is greater than the preset ratio threshold, the size of the current dynamic sliding window is reduced to a preset size; if it is not greater than the preset ratio threshold, the size of the current dynamic sliding window is not reduced to the preset size; the cable edge features in each dynamic sliding window are connected to obtain a cable contour, and a cable contour image containing the cable contour is determined.

[0035] It should be noted that, by judging whether the ratio of the cable edge features in the current dynamic sliding window to all the features in the current dynamic sliding window is greater than the preset ratio threshold each time sliding, if it is greater than the preset ratio threshold, the size of the current dynamic sliding window is reduced to the preset size, which can reduce the processing amount of feature recognition while obtaining the complete cable contour as much as possible.

[0036] Step S104: Calculate the cable area based on the cable contour image and extract cable surface features.

[0037] In this step, the cable surface features are obtained and compared with the set feature interval; it is determined whether the cable surface features belong to the set feature interval; if they belong to the set feature interval, normalization processing is performed to obtain the optimized cable surface features; if they do not belong to the set feature interval, they are determined to be interference features, the interference features are eliminated, and the optimized cable surface features are obtained.

[0038] Step S105 , analyzing the cable surface features based on the set noise threshold, eliminating the noise features, and obtaining optimized cable surface features.

[0039] Step S106: Analyze the optimized cable surface characteristics based on the defect detection model and output surface defect information.

[0040] In this step, a training set is established based on historical defect analysis data, and the initial model is iteratively trained according to the training set to obtain training results; it is determined whether the training results have converged; if so, a defect detection model is generated, and the optimized cable surface features are input into the defect detection model to obtain surface defect information; if not, adjustment parameters are generated; and the model parameters are adjusted according to the adjustment parameters until the initial model converges.

[0041] In summary, the method of the present application forms a sequence by sorting the current data of each monitoring position of the cable by position, and divides the data subsequences based on a preset strategy to associate the cable images of different monitoring positions. It combines image preprocessing, contour segmentation, region calculation and surface feature extraction, and finally eliminates noise features by setting a noise threshold and uses the defect detection model to analyze the optimized surface features, thereby realizing automated and precise detection of cable defects. It can efficiently output key information such as defect location, type and severity, significantly improve the accuracy and real-time performance of defect detection, reduce the cost of manual inspection and the risk of missed detection, and provide reliable protection for the safe operation of the cable.

[0042] See also Figure 2 , which shows a structural block diagram of a cable defect analysis system during the cable laying process of the present application.

[0043] like Figure 2As shown, the cable defect analysis system 200 during the cable laying process includes a sorting module 210 , a dividing module 220 , a segmentation module 230 , a calculation module 240 , an optimization module 250 and an analysis module 260 .

[0044] Among them, the sorting module 210 is configured to obtain current data of each monitoring position of the cable within a preset time period, and sort each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position; the division module 220 is configured to divide the current data sequence according to a preset data division strategy to obtain at least one current data subsequence, and obtain cable images of different monitoring positions based on the at least one current data subsequence; the segmentation module 230 is configured to preprocess the cable image to obtain an enhanced cable image, and segment the enhanced cable image into a cable contour and a background area to obtain a cable contour image; the calculation module 240 is configured to calculate the cable area based on the cable contour image and extract the cable surface features; the optimization module 250 is configured to analyze the cable surface features based on a set noise threshold, eliminate the noise features, and obtain the optimized cable surface features; the analysis module 260 is configured to analyze the optimized cable surface features based on the defect detection model and output surface defect information.

[0045] It should be understood that Figure 2 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects also apply to Figure 2 The modules in it will not be described in detail here.

[0046] In other embodiments, embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor is caused to execute the cable defect analysis method during cable laying in any of the above method embodiments;

[0047] As an embodiment, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows:

[0048] Acquire current data at each monitoring position of the cable, and sort each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position;

[0049] Dividing the current data sequence according to a preset data division strategy to obtain at least one current data subsequence, and acquiring cable images at different monitoring positions according to the at least one current data subsequence;

[0050] Preprocessing the cable image to obtain a target cable image, and segmenting the target cable image into a cable outline and a background area to obtain a cable outline image;

[0051] Calculating the cable area based on the cable contour image and extracting cable surface features;

[0052] Analyze the cable surface characteristics based on the set noise threshold, eliminate the noise characteristics, and obtain the optimized cable surface characteristics;

[0053] The optimized cable surface features are analyzed based on the defect detection model, and surface defect information is output.

[0054] The computer-readable storage medium may include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for the function; the data storage area may store data generated based on the use of the cable defect analysis system during cable laying. Furthermore, the computer-readable storage medium may include high-speed random access memory and may also include storage, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the computer-readable storage medium may optionally include storage remote from the processor. Such remote storage may be connected to the cable defect analysis system during cable laying via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0055] Figure 3 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 3 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 3 The example uses a bus connection. Memory 320 is the aforementioned computer-readable storage medium. Processor 310 executes the various server functional applications and data processing by running the non-volatile software programs, instructions, and modules stored in memory 320, thereby implementing the cable defect analysis method during cable laying described in the aforementioned method embodiment. Input device 330 can receive input digital or character information and generate key signal input related to user settings and function control of the cable defect analysis system during cable laying. Output device 340 may include a display device such as a display screen.

[0056] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0057] As an embodiment, the electronic device is applied to a cable defect analysis system during cable laying, and is used for a client, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0058] Acquire current data at each monitoring position of the cable, and sort each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position;

[0059] Dividing the current data sequence according to a preset data division strategy to obtain at least one current data subsequence, and acquiring cable images at different monitoring positions according to the at least one current data subsequence;

[0060] Preprocessing the cable image to obtain a target cable image, and segmenting the target cable image into a cable outline and a background area to obtain a cable outline image;

[0061] Calculating the cable area based on the cable contour image and extracting cable surface features;

[0062] Analyze the cable surface characteristics based on the set noise threshold, eliminate the noise characteristics, and obtain the optimized cable surface characteristics;

[0063] The optimized cable surface features are analyzed based on the defect detection model, and surface defect information is output.

[0064] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus the necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods of each embodiment or certain parts of the embodiment.

[0065] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for analyzing cable defects during cable laying, characterized in that: include: Acquire current data at each monitoring position of the cable, and sort each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position; Dividing the current data sequence according to a preset data division strategy to obtain at least one current data subsequence, and acquiring cable images at different monitoring positions according to the at least one current data subsequence; Preprocessing the cable image to obtain a target cable image, and segmenting the target cable image into a cable outline and a background area to obtain a cable outline image; Calculating the cable area based on the cable contour image and extracting cable surface features; Analyze the cable surface characteristics based on the set noise threshold, eliminate the noise characteristics, and obtain the optimized cable surface characteristics; The optimized cable surface features are analyzed based on the defect detection model, and surface defect information is output.

2. The cable defect analysis method during cable laying according to claim 1, characterized in that: The step of obtaining current data at each monitoring position of the cable and sorting each current data based on the monitoring position to obtain a current data sequence includes: Obtain current data at each monitoring position of the cable; The current data at each monitoring position are sorted along the length of the cable to obtain a current data sequence.

3. The cable defect analysis method during cable laying according to claim 1, characterized in that: The step of dividing the current data sequence according to a preset data division strategy to obtain at least one current data subsequence, and acquiring cable images at different monitoring locations according to the at least one current data subsequence includes: Sliding a preset sliding window on the current data sequence, and determining whether a certain current data in the sliding window is greater than a preset threshold each time the sliding window slides, wherein the sliding window only includes one current data each time the sliding window slides; If it is greater than a preset threshold, the certain current data is used as cut-off current data, and all current data between two adjacent cut-off current data are divided into the same current data subsequence to obtain at least one current data subsequence; If it is not greater than the preset threshold, continue to determine whether another current data in the next sliding window is greater than the preset threshold until all current data in the current data sequence are determined to obtain at least one current data subsequence; The cable image of the monitoring position corresponding to each cutoff current in each current data subsequence is obtained.

4. The cable defect analysis method during cable laying according to claim 1, characterized in that: The preprocessing of the cable image to obtain a target cable image, and segmenting the target cable image into a cable outline and a background area to obtain a cable outline image includes: performing denoising processing on the cable image to obtain a target cable image; Sliding a preset dynamic sliding window on the edge of the target cable image, and comparing the regional edge features in the dynamic sliding window with the set features for similarity each time the window slides; Taking at least one regional edge feature with a similarity greater than a preset threshold as a cable edge feature, and determining whether a ratio of the cable edge feature to all features in the current dynamic sliding window is greater than a preset ratio threshold; If the percentage is greater than a preset threshold, the size of the current dynamic sliding window is reduced to a preset size; If the ratio is not greater than the preset proportion threshold, the size of the current dynamic sliding window is not reduced to the preset size; The cable edge features in each dynamic sliding window are connected to obtain a cable outline, and a cable outline image containing the cable outline is determined.

5. The method for analyzing cable defects during cable laying according to claim 1, characterized in that: Calculating the cable area based on the cable contour image and extracting the cable surface features includes: Obtaining cable surface features, comparing the cable surface features with a set feature interval; and determining whether the cable surface features fall within the set feature interval; If it belongs to the set feature interval, normalization processing is performed to obtain the optimized cable surface features; if it does not belong to the set feature interval, it is determined to be an interference feature, and the interference feature is eliminated to obtain the optimized cable surface features.

6. The method for analyzing cable defects during cable laying according to claim 1, characterized in that: The defect detection model is used to analyze the optimized cable surface characteristics and output surface defect information, including: Establish a training set based on historical defect analysis data, iteratively train the initial model based on the training set, and obtain training results; Determining whether the training result has converged; If convergence is achieved, a defect detection model is generated, and the optimized cable surface features are input into the defect detection model to obtain surface defect information; if not convergence is achieved, adjustment parameters are generated; Adjust the model parameters according to the tuning parameters until the initial model converges.

7. A cable defect analysis system during cable laying, characterized in that: include: a sorting module configured to obtain current data at each monitoring position of the cable within a preset time period, and sort each current data based on the monitoring position to obtain a current data sequence, wherein each current data in the current data sequence is associated with the corresponding monitoring position; a partitioning module configured to partition the current data sequence according to a preset data partitioning strategy to obtain at least one current data subsequence, and acquire cable images at different monitoring positions according to the at least one current data subsequence; a segmentation module configured to preprocess the cable image to obtain an enhanced cable image, and segment the enhanced cable image into a cable outline and a background area to obtain a cable outline image; a calculation module configured to calculate the cable area based on the cable contour image and extract cable surface features; an optimization module configured to analyze the surface characteristics of the cable based on a set noise threshold, eliminate the noise characteristics, and obtain optimized cable surface characteristics; The analysis module is configured to analyze the surface characteristics of the optimized cable based on the defect detection model and output surface defect information.

8. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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