Rapid positioning device, method and equipment for cable insulation layer damage in cable trench

Abstract

The invention discloses a rapid positioning device, method and equipment for cable insulation layer damage in a cable trench, and belongs to the technical field of electric power facilities. The device comprises an image data acquisition module which is used for acquiring image data of a cable in a cable trench in a cable trench inspection process; wherein the image data is visible light image data; the edge detection module is used for carrying out edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data; the local anomaly recognition module is used for recognizing the edge detection data, and if a local bulge condition exists, the local anomaly of edge damage is recognized; and the prompt module is used for generating prompt information of local abnormity of the edge damage. According to the technical scheme, whether the insulation layer of the cable is damaged or not can be determined by identifying the image data of the cable, the scheme is beneficial to improving the inspection efficiency of workers, and the real-time performance is high.

Description

Technical Field

[0001] The present application belongs to the technical field of electric power facilities, and specifically relates to a device, method and equipment for quickly locating damaged cable insulation in a cable trench. Background Art

[0002] A cable trench is an underground passage used to lay and protect cables. While preventing the cables from being damaged by the external environment, it can also reduce the occupation of space above the ground in the city and beautify the urban environment.

[0003] Since the space of the cable trench is closed, in the process of manual cable inspection, considering the space limitation and the influence of toxic and harmful gases, a lot of preparation work needs to be done before the inspection, which not only affects the efficiency of manual inspection, but also causes the inspection to lack real-time performance. Therefore, how to effectively inspect the cables in the cable trench to ensure that the cable insulation layer is intact and not damaged is a technical problem that needs to be solved urgently by technicians in this field. Summary of the invention

[0004] The embodiments of the present application provide a device, method and equipment for quickly locating damaged cable insulation in a cable trench. It can determine whether the cable insulation is damaged by identifying the image data of the cable. This solution helps to improve the inspection efficiency of staff and has strong real-time performance.

[0005] In a first aspect, an embodiment of the present application provides a device for quickly locating a damaged cable insulation layer in a cable trench, the device comprising:

[0006] An image data acquisition module is used to acquire image data of cables in the cable trench during the cable trench inspection; wherein the image data is visible light image data;

[0007] An edge detection module, used to perform edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data;

[0008] A local anomaly recognition module is used to recognize the edge detection data, and if there is a local bulge, it is recognized as a local anomaly of edge damage;

[0009] The prompt module is used to generate prompt information of edge damage local abnormalities.

[0010] Furthermore, the device also includes:

[0011] A crack detection module is used to detect cracks in the cable insulation layer in the visible light image data to obtain crack detection data;

[0012] The crack anomaly identification module is used to identify the crack detection data, and if there is a rupture in the insulation layer, it is identified as a local abnormality of crack damage.

[0013] Furthermore, the image data acquisition module is also used to acquire cable image data at the cable fixing part;

[0014] The device also includes:

[0015] A shrinkage detection module, used to identify whether the shrinkage degree of the cable insulation layer at the cable fixing part is greater than a set threshold;

[0016] A damage degree determination module, used to determine the damage degree of the cable insulation layer according to the correlation relationship between the shrinkage degree and the preset damage degree when the shrinkage degree is greater than a set threshold value;

[0017] The prompt module is also used for:

[0018] When the degree of damage is greater than a preset degree, a prompt message is generated.

[0019] Furthermore, the shrinkage degree detection module is also used for:

[0020] recognizing that the curvature of the cable insulation layer at the cable fixing part reaches a set value;

[0021] The damage degree determination module is further used for:

[0022] When the curvature reaches a set value, the degree of damage to the cable insulation layer is determined according to a correlation between the curvature and a preset degree of damage.

[0023] Furthermore, the image data acquisition module is also used to acquire cable image data at the cable fixing part;

[0024] The device also includes:

[0025] A fixture parameter acquisition module is used to obtain the size information and material information of the fixture;

[0026] A model building module, used to build a heat dissipation model and a water immersion model at the cable fixing part according to the size information and the material information;

[0027] An aging degree estimation module, used for estimating the aging rate of the cable insulation layer at the cable fixing part according to the heat dissipation model and the water immersion model;

[0028] The prompt information generation module is used to generate aging prompt information according to the estimation result.

[0029] Furthermore, the device also includes:

[0030] An ultrasonic signal acquisition module is used to acquire ultrasonic signals during cable inspection through an ultrasonic sensor;

[0031] A parameter information extraction module, used to extract parameter information of the ultrasonic signal;

[0032] A matching module, used for matching the ultrasonic signal with the characteristics of partial discharge caused by damage to the cable insulation layer based on the parameter information;

[0033] A prompt information production module is used to generate partial discharge prompt information after identifying that the matching similarity is greater than a first set threshold; after identifying that the matching similarity is less than the first set threshold and greater than a second set threshold, generate prompt information of suspected partial discharge; wherein the first set threshold is greater than the second set threshold.

[0034] Furthermore, the edge detection module is specifically used for:

[0035] Using a gradient detection algorithm to perform gradient detection on the visible light image data to obtain boundary information;

[0036] The edge position of the cable insulation layer is determined according to the boundary information to obtain edge detection data.

[0037] In a second aspect, an embodiment of the present application provides a method for quickly locating a damaged cable insulation layer in a cable trench, the method comprising:

[0038] During the cable trench inspection, image data of the cables in the cable trench is obtained; wherein the image data is visible light image data;

[0039] Performing edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data;

[0040] Identify the edge detection data, and if there is a local bulge, identify it as a local abnormality of edge damage;

[0041] Generate prompt information for local abnormalities of edge damage.

[0042] Furthermore, the method further comprises:

[0043] Detecting cracks in the cable insulation layer in the visible light image data to obtain crack detection data;

[0044] The crack detection data is identified, and if there is a rupture in the insulation layer, it is identified as a local abnormality of crack damage.

[0045] In a third aspect, an embodiment of the present application provides an electronic device, which includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method described in the first aspect.

[0046] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0047] In a fifth aspect, an embodiment of the present application provides a chip, comprising a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the method described in the first aspect.

[0048] In an embodiment of the present application, an image data acquisition module is used to acquire image data of cables in a cable trench during the inspection of the cable trench; wherein the image data is visible light image data; an edge detection module is used to perform edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data; a local abnormality recognition module is used to recognize the edge detection data, and if there is a local protrusion, it is recognized as a local abnormality of edge damage; a prompt module is used to generate prompt information of the local abnormality of edge damage. The above scheme can determine whether the cable insulation layer is damaged by recognizing the image data of the cable. This scheme helps to improve the inspection efficiency of the staff and has strong real-time performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic structural diagram of a device for quickly locating a damaged cable insulation layer in a cable trench provided in Example 1 of the present application;

[0050] Figure 2 It is a structural schematic diagram of a device for quickly locating a damaged cable insulation layer in a cable trench provided in Example 2 of the present application;

[0051] Figure 3 It is a schematic structural diagram of a device for quickly locating a damaged cable insulation layer in a cable trench provided in Embodiment 3 of the present application;

[0052] Figure 4 It is a structural schematic diagram of a device for quickly locating a damaged cable insulation layer in a cable trench provided in a fourth embodiment of the present application;

[0053] Figure 5 It is a schematic flow chart of a method for quickly locating a damaged cable insulation layer in a cable trench provided in Embodiment 5 of the present application;

[0054] Figure 6It is a structural diagram of an electronic device provided in Example 6 of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all the contents are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0056] The following will be combined with the drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments in the present application belong to the scope of protection of this application.

[0057] The terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and / or" in the specification and claims represents at least one of the connected objects, and the character " / " generally indicates that the objects associated with each other are in an "or" relationship.

[0058] In conjunction with the accompanying drawings, the device, method and equipment for quickly locating damaged cable insulation in a cable trench provided in the embodiments of the present application are described in detail below through specific embodiments and their application scenarios.

[0059] Embodiment 1

[0060] Figure 1 1 is a schematic diagram of the structure of a device for quickly locating a damaged cable insulation layer in a cable trench provided in Example 1 of the present application. Figure 1 As shown, the specific steps include:

[0061] The image data acquisition module 101 is used to acquire image data of cables in the cable trench during the inspection of the cable trench; wherein the image data is visible light image data;

[0062] An edge detection module 102 is used to perform edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data;

[0063] A local abnormality identification module 103 is used to identify the edge detection data, and if there is a local bulge, it is identified as a local abnormality of edge damage;

[0064] The prompt module 104 is used to generate prompt information of edge damage local abnormality.

[0065] The application scenario of this solution may be a scenario of patrolling cables in a cable trench.

[0066] Based on the above scenario, it can be understood that the executor of this scenario can be an inspection robot used for cable inspection, or a smart terminal held by staff, etc., or a terminal device for processing cable images collected during inspection, such as a desktop computer, etc., without too much limitation here.

[0067] Cable trenches can be underground pipelines used to lay and replace power or telecommunication cable facilities, and are also the enclosure structures for the laid cable facilities. There are rectangular, circular, arched and other pipeline structural forms.

[0068] During the cable inspection process, an image sensor can be used to obtain image data of the cable. It can be set on the inspection robot and directed toward the cable layout position in the cable trench. Specifically, an image sensor can be an electronic device used to capture optical images. Its main function is to convert visible light, infrared light or other light in the spectral range into electrical signals so that digital devices can process, display or store these images. Image sensors are based on semiconductor technology and use the photoelectric conversion function of optoelectronic devices to convert the light image on the photosensitive surface into an electrical signal that is proportional to the light image.

[0069] In this solution, the image sensor may also be provided on a wearable device of the user, or a handheld device, etc. For example, the image sensor may be provided on a safety helmet worn by the user, or on a handheld operation auxiliary terminal, etc.

[0070] It should be noted that, in this solution, the image data collected for the cable may be the collected visible light image data.

[0071] After the visible light data is collected, it can be identified and processed to obtain the cable positions therein, and one or more cables in the cable trench can be determined as the target cables for this identification.

[0072] During the inspection of cables, it is an important task to identify whether the insulation layer is damaged. Therefore, edge detection can be performed on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data.

[0073] Specifically, the edge position of the insulating layer can be detected based on the brightness data of the pixel points, or based on the color data of the pixel points. For example, in the cable image data, the brightness of the pixel points at the cable position is lower than that of the pixel points at other positions, or the color of the pixel points at the cable position is different from that of the pixel points at other positions, which can be used as the basis for the edge position of the cable to perform edge detection and obtain edge detection data.

[0074] The edge detection data may include the detected edge position of the cable insulation layer, the extension direction formed by the edge pixels, etc.

[0075] In a feasible embodiment, optionally, the edge detection module 102 is specifically configured to:

[0076] Using a gradient detection algorithm to perform gradient detection on the visible light image data to obtain boundary information;

[0077] The edge position of the cable insulation layer is determined according to the boundary information to obtain edge detection data.

[0078] In this solution, image gradient is mainly used to describe the degree and direction of change of pixel values ​​in an image. It can help us detect important features such as edges and contours in an image.

[0079] Mathematically, image gradients are usually obtained by calculating the rate of change of pixel values ​​in the horizontal and vertical directions. For example, for a grayscale image, the commonly used gradient calculation method is to use the Sobel operator or the Prewitt operator.

[0080] The Sobel operator calculates the gradient through convolution operation, which has a certain ability to suppress noise.

[0081] The calculation method of the Prewitt operator is similar to that of the Sobel operator, but it is relatively simpler.

[0082] In this solution, you can use Python and OpenCV library to implement the sample code of cable edge detection:

[0083] Python

[0084] import cv2

[0085] def detect_cable_edges(image_path):

[0086] #Read the image

[0087] image=cv2.imread(image_path)

[0088] #Convert the image to grayscale

[0089] gray_image=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)

[0090] #Apply Gaussian blur to reduce noise

[0091] blurred_image=cv2.GaussianBlur(gray_image,(5,5),0)

[0092] #Use Canny edge detection algorithm

[0093] edges=cv2.Canny(blurred_image,50,150)

[0094] # Display results

[0095] cv2.imshow('Edges',edges)

[0096] cv2.waitKey(0)

[0097] cv2.destroyAllWindows()

[0098] #Call the function and pass in the image path

[0099] detect_cable_edges('cable_image.jpg')

[0100] In the above code, we first read the image, convert it to grayscale, and then perform Gaussian blur to reduce the effect of noise. Next, we use the Canny edge detection algorithm to detect edges.

[0101] Note that you need to replace 'cable_image.jpg' with the path to your actual cable image.

[0102] In addition, you can also try to use other edge detection algorithms, such as the Sobel operator, as shown below:

[0103] Python

[0104] import cv2

[0105] def detect_cable_edges_sobel(image_path):

[0106] image=cv2.imread(image_path)

[0107] gray_image=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)

[0108] #Sobel operator edge detection in the x direction

[0109] sobel_x=cv2.Sobel(gray_image,cv2.CV_64F,1,0,ksize=5)

[0110] #Sobel operator edge detection in the y direction

[0111] sobel_y=cv2.Sobel(gray_image,cv2.CV_64F,0,1,ksize=5)

[0112] # Combine the edges in the x and y directions

[0113] sobel_combined=cv2.addWeighted(sobel_x,0.5,sobel_y,0.5,0)

[0114] #Threshold processing to get clearer edges

[0115] _,thresholded=cv2.threshold(sobel_combined,100,255,cv2.THRESH_BINARY)

[0116] cv2.imshow('Edges',thresholded)

[0117] cv2.waitKey(0)

[0118] cv2.destroyAllWindows()

[0119] detect_cable_edges_sobel('cable_image.jpg')

[0120] Based on the above code, you can adjust the parameters according to the characteristics of the image to obtain better edge detection effects.

[0121] The technical solution is configured in this way so that when detecting the edge, boundary information can be obtained first, and then the edge position of the cable insulation layer can be determined based on the boundary information, so as to subsequently identify whether the insulation layer of the cable is damaged.

[0122] The local anomaly identification module 103 can identify the edge detection data to determine whether there is a local bulge. For example, the edge of the cable should be a straight line at the current position, but a bulge occurs at a certain position. In this case, it can be identified as a local anomaly of edge damage. Specifically, the identification of the bulge can be based on the distribution of the pixel points at the edge position mentioned above. For example, if the slope of the line segment composed of the pixel points suddenly changes and finally returns to the same slope as the original, it can be determined that there is a bulge at this position. Among them, the length of the line segment can be the window width for identifying whether there is a bulge. For example, if the window width is 10, the slope can be identified by the line segment composed of the pixel points at the adjacent 10 edge positions. Among them, the window width can be a default setting, or it can be manually set according to the requirements of the detection accuracy.

[0123] When local abnormalities such as edge damage are detected, prompt information can be generated based on the type of abnormality detected, the corresponding cable image data and the detection location, so as to prompt the staff to check whether there is any local damage abnormality in the cable at the current detection location, and perform corresponding maintenance processing if there is any abnormality, such as reinforcing with tape, or replacing the cable segment where the abnormal location is located, so as to ensure the safe operation of the cable.

[0124] The technical solution provided in this embodiment is an image data acquisition module, which is used to acquire image data of cables in the cable trench during the inspection of the cable trench; wherein the image data is visible light image data; an edge detection module, which is used to perform edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data; a local abnormality recognition module, which is used to recognize the edge detection data, and if there is a local protrusion, it is recognized as a local abnormality of edge damage; a prompt module, which is used to generate prompt information of the local abnormality of edge damage. The above scheme can determine whether the cable insulation layer is damaged by recognizing the image data of the cable. This scheme helps to improve the inspection efficiency of the staff and has strong real-time performance.

[0125] Embodiment 2

[0126] Figure 2This is a schematic diagram of the structure of a device for quickly locating damaged cable insulation in a cable trench provided in Example 2 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is: the device also includes: a crack detection module, which is used to detect cracks in the cable insulation layer in the visible light image data to obtain crack detection data; a crack abnormality identification module, which is used to identify the crack detection data, and if there is a rupture in the insulation layer, it is identified as a local abnormality of crack damage.

[0127] like Figure 2 As shown, specifically including the following:

[0128] The image data acquisition module 201 is used to acquire image data of cables in the cable trench during the inspection of the cable trench; wherein the image data is visible light image data;

[0129] A crack detection module 202 is used to detect cracks in the cable insulation layer in the visible light image data to obtain crack detection data;

[0130] The crack abnormality identification module 203 is used to identify the crack detection data, and if there is a crack in the insulation layer, it is identified as a local abnormality of crack damage;

[0131] The prompt module 204 is used to generate prompt information of edge damage local abnormality.

[0132] Among them, crack detection is mainly used to identify cracks in the insulation layer of the cable. After obtaining the identification results, the staff can conduct further verification. For the crack detection method, the crack traces can be identified between the edges of the insulation layer of the cable. For example, the color value of the pixel point at the location of the crack trace will be darker than other locations, so it can be identified based on the color value of the pixel point. Or after the crack, the internal structure of the cable is exposed, causing the brightness value of the pixel point at the crack gap to be brighter, so detection can be performed based on the brightness value of the pixel point.

[0133] It should be noted that the crack detection data may be description data obtained through detection, which may include an image of the crack, the size of the crack in the image, the opening range, etc.

[0134] After the crack detection data is obtained, it can be identified. If there is a rupture in the insulation layer, it is identified as a local abnormality of crack damage and a corresponding prompt message is generated.

[0135] The following is a simple example code for cable insulation crack detection:

[0136] import cv2

[0137] import numpy as np

[0138] def detect_cable_insulation_cracks(image_path):

[0139] #Read the image

[0140] image=cv2.imread(image_path)

[0141] #Convert to grayscale image

[0142] gray_image=cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)

[0143] #Apply Gaussian blur

[0144] blurred_image=cv2.GaussianBlur(gray_image,(5,5),0)

[0145] #Use Canny edge detection

[0146] edges=cv2.Canny(blurred_image,50,150)

[0147] #Perform morphological operations such as dilation and erosion to connect and clean up edges

[0148] kernel=np.ones((5,5),np.uint8)

[0149] dilated_edges=cv2.dilate(edges,kernel,iterations=1)

[0150] eroded_edges=cv2.erode(dilated_edges,kernel,iterations=1)

[0151] #Find contours

[0152] contours,_=cv2.findContours(eroded_edges,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)

[0153] #Draw the outline

[0154] cv2.drawContours(image,contours,-1,(0,0,255),2)

[0155] # Display results

[0156] cv2.imshow('Cracks Detection',image)

[0157] cv2.waitKey(0)

[0158] cv2.destroyAllWindows()

[0159] #Call the function and pass in the image path

[0160] detect_cable_insulation_cracks('cable_image.jpg');

[0161] The above code first preprocesses the input image, including grayscale conversion, Gaussian blur and edge detection. Then it processes the edges through morphological operations, finds the contours and draws them to show possible cracks.

[0162] Here, you can adjust the parameters according to the actual image effect, such as the kernel size of Gaussian blur, the threshold of Canny edge detection, and the kernel size and number of iterations of morphological operations. In addition, you can also consider using more complex image processing and machine learning methods to improve the accuracy of detection, such as using deep learning models for crack detection.

[0163] Based on the above embodiments, this embodiment provides a method for detecting cracks in the image of the cable insulation layer, and generates prompt information when cracks are identified after detection to prompt the existence of cracks in the insulation layer of the cable, so that the staff can quickly locate the damaged position of the insulation layer and determine whether other maintenance operations are needed based on the actual situation.

[0164] Embodiment 3

[0165] Figure 3 It is a structural schematic diagram of a rapid positioning device for damaged cable insulation in a cable trench provided in Example 3 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvement is as follows: the image data acquisition module is also used to acquire cable image data at the cable fixing part; the device also includes: a shrinkage degree detection module, which is used to identify whether the shrinkage degree of the cable insulation layer at the cable fixing part is greater than a set threshold; a damage degree determination module, which is used to determine the damage degree of the cable insulation layer according to the correlation between the shrinkage degree and the preset damage degree when the shrinkage degree is greater than the set threshold; the prompt module is also used to generate a prompt message when the damage degree is greater than the preset degree.

[0166] like Figure 3 As shown, specifically including the following:

[0167] The image data acquisition module 301 is also used to acquire the cable image data at the cable fixing part;

[0168] A shrinkage detection module 302 is used to identify whether the shrinkage degree of the cable insulation layer at the cable fixing part is greater than a set threshold;

[0169] A damage degree determination module 303 is used to determine the damage degree of the cable insulation layer according to the correlation relationship between the shrinkage degree and the preset damage degree when the shrinkage degree is greater than a set threshold value;

[0170] The prompt module 304 is further configured to generate a prompt message when the degree of damage is greater than a preset degree.

[0171] The cable fixing part is used to fix the cable, for example, to fix the cable on the wire racks on both sides of the cable trench. The cable image data at the cable fixing part may be data collected by an image sensor in a direction perpendicular to the cable.

[0172] The shrinkage degree of the cable insulation layer at the cable fixing part may be due to the tightening of the cable fixing part, which causes the cable insulation layer to deform at the position where the fixing part is fixed. Therefore, there is a certain amount of shrinkage. For example, if the diameter of the cable is 5 cm, at the fixing part, the diameter of the cable shrinks from 5 cm to 4.5 cm due to the shrinkage of the fixing part.

[0173] In this case, the degree of damage to the cable insulation layer can be determined based on the correlation between the degree of shrinkage and the preset degree of damage. For example, when the degree of shrinkage is 100%-95%, the degree of damage is 0, when the degree of shrinkage is 95%-90%, the degree of damage is 10 points, when the degree of shrinkage is 90%-86%, the degree of damage is 15 points, when the degree of shrinkage is 86%-82%, the degree of damage is 20 points, and so on. The number of points of the degree of damage represents the possibility of damage to the cable insulation layer and the severity of the damage. When the degree of damage to the cable insulation layer exceeds 20 points, other treatments are required, such as replacing the cable, or thickening and reinforcing the insulation layer.

[0174] Accordingly, a prompt message may be generated when the degree of damage is greater than a preset degree, for example, greater than 10 points.

[0175] Through such a setting, the present solution can identify the degree of damage to the insulation layer of the cable fixing position through images, and generate prompt information after the identification is completed, so that the staff can check whether the cable fixing position is damaged due to the tightening of the fixings, thereby achieving more comprehensive maintenance of the cable.

[0176] On the basis of the above technical solution, optionally, the shrinkage degree detection module is further used to:

[0177] recognizing that the curvature of the cable insulation layer at the cable fixing part reaches a set value;

[0178] The damage degree determination module is further used for:

[0179] When the curvature reaches a set value, the degree of damage to the cable insulation layer is determined according to a correlation between the curvature and a preset degree of damage.

[0180] Among them, since the edge of the cable insulation layer originally presents a straight line, but due to the effect of the fixing, the area close to the fixing will be curved. Therefore, the degree of damage to the cable insulation layer can be determined by identifying the curvature. For example, the damage degree of the part with a small change in curvature is low, or it will not be damaged, but the damage degree of the part with a large change in curvature will be relatively large. This solution can determine the degree of damage to the cable insulation layer based on the correlation between the curvature and the preset degree of damage.

[0181] This solution provides a method for determining the degree of damage of the cable insulation layer by identifying its curvature. Through such a setting, the accuracy of identifying the degree of damage of the cable at the fixing position can be improved, and a full range of cable inspections can be achieved, eliminating safety hazards in cable operation and avoiding the problem of incomplete inspections due to the inability to visually view.

[0182] Embodiment 4

[0183] Figure 4 It is a structural schematic diagram of a rapid positioning device for damaged cable insulation in a cable trench provided in Example 4 of the present application. This solution makes a better improvement on the above-mentioned embodiment, and the specific improvements are as follows: the image data acquisition module is also used to acquire cable image data at the cable fixing part; the device also includes: a fixing part parameter acquisition module, which is used to acquire the size information and material information of the fixing part; a model construction module, which is used to construct a heat dissipation model and a water immersion model at the cable fixing part according to the size information and the material information; an aging degree estimation module, which is used to estimate the aging speed of the cable insulation layer at the cable fixing part according to the heat dissipation model and the water immersion model; and a prompt information generation module, which is used to generate aging prompt information according to the estimation result.

[0184] like Figure 4 As shown, specifically including the following:

[0185] The image data acquisition module 401 is also used to acquire the cable image data at the cable fixing part;

[0186] The fixing part parameter acquisition module 402 is used to acquire the size information and material information of the fixing part;

[0187] A model building module 403, used to build a heat dissipation model and a water immersion model at the cable fixing part according to the size information and the material information;

[0188] An aging degree estimation module 404, for estimating an aging rate of the cable insulation layer at the cable fixture according to the heat dissipation model and the water immersion model;

[0189] The prompt information generating module 405 is used to generate aging prompt information according to the estimation result.

[0190] After acquiring the cable image data at the cable fixture, the size information and material information of the cable fixture can be identified. For example, it can be identified that the width of the cable fixture is 5 cm, the thickness is 0.3 cm, and the material of the cable fixture is iron sheet.

[0191] After determining the size information and material information, the heat dissipation model and water immersion model of the cable fixture can be constructed based on the size information and material information. The heat dissipation model is used to model the heat generated by the cable during operation and the heat dissipation is affected by the existence of the cable fixture. The heat dissipation model can be used to determine the temperature information at the fixture during the operation of the cable. The water immersion model refers to a model in which the water at the cable fixture will evaporate completely after a certain period of time after being sprinkled or immersed in water. The water immersion model can be used to determine how long it will take for the cable to evaporate once there is water.

[0192] Because local high temperature and local immersion will affect the aging of the cable insulation layer, the aging speed of the cable insulation layer at the cable fixture can be estimated based on the heat dissipation model and the water immersion model, and aging prompt information can be generated based on the estimation result.

[0193] Through such an arrangement, this embodiment can improve the model for inspecting the aging position of the cable insulation layer at the cable fixing member.

[0194] Based on the above embodiments, optionally, the device further includes:

[0195] An ultrasonic signal acquisition module is used to acquire ultrasonic signals during cable inspection through an ultrasonic sensor;

[0196] A parameter information extraction module, used to extract parameter information of the ultrasonic signal;

[0197] A matching module, used for matching the ultrasonic signal with the characteristics of partial discharge caused by damage to the cable insulation layer based on the parameter information;

[0198] A prompt information production module is used to generate partial discharge prompt information after identifying that the matching similarity is greater than a first set threshold; after identifying that the matching similarity is less than the first set threshold and greater than a second set threshold, generate prompt information of suspected partial discharge; wherein the first set threshold is greater than the second set threshold.

[0199] In this solution, by collecting ultrasonic signals, it can be matched with the ultrasonic signals generated by the cable during partial discharge. If the matching similarity is greater than the first set threshold, it can be determined that partial discharge exists. If the matching similarity is less than the first set threshold and greater than the second set threshold, a prompt message of suspected partial discharge can be generated, so that the staff can further determine whether there is a partial discharge phenomenon based on actual observation results.

[0200] This embodiment can realize efficient inspection of cable insulation layer damage by collecting and matching ultrasonic signals, and improve the detection capability of some fault locations that are difficult to find during the inspection process.

[0201] Embodiment 5

[0202] Figure 5 1 is a flow chart of a method for quickly locating a damaged cable insulation layer in a cable trench provided in Embodiment 5 of the present application. Figure 5 As shown, the specific steps include:

[0203] S501. During the cable trench inspection, image data of cables in the cable trench is obtained; wherein the image data is visible light image data;

[0204] S502, performing edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data;

[0205] S503, identifying the edge detection data, and if there is a local bulge, identifying it as a local abnormality of edge damage;

[0206] S504: Generate prompt information of edge damage local abnormality.

[0207] Furthermore, the method further comprises:

[0208] Detecting cracks in the cable insulation layer in the visible light image data to obtain crack detection data;

[0209] The crack detection data is identified, and if there is a rupture in the insulation layer, it is identified as a local abnormality of crack damage.

[0210] The technical solution of this embodiment is to obtain image data of the cables in the cable trench during the inspection of the cable trench; wherein the image data is visible light image data; edge detection is performed on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data; the edge detection data is identified, and if there is a local protrusion, it is identified as a local abnormality of edge damage; and prompt information of the local abnormality of edge damage is generated. The above solution can determine whether the cable insulation layer is damaged by identifying the image data of the cable. This solution helps to improve the inspection efficiency of the staff and has strong real-time performance.

[0211] The method for quickly locating damaged cable insulation in a cable trench provided in an embodiment of the present application corresponds to the device for quickly locating damaged cable insulation in a cable trench provided in the above-mentioned embodiment, and has the same functional modules and beneficial effects. To avoid repetition, they will not be described here.

[0212] Embodiment 6

[0213] Figure 6 Schematic diagram of the structure of the electronic device provided in Example 6 of the present application. Figure 6 As shown, an embodiment of the present application also provides an electronic device 600, including a processor 601, a memory 602, and a program or instruction stored in the memory 602 and executable on the processor 601. When the program or instruction is executed by the processor 601, each process of the embodiment of the method for quickly locating damaged cable insulation layer in the above-mentioned cable trench is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0214] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0215] Embodiment 7

[0216] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the embodiment of the method for quickly locating damaged cable insulation layer in the cable trench is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0217] The processor is a processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0218] Embodiment 8

[0219] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned embodiment of the method for quickly locating damaged cable insulation in a cable trench, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0220] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0221] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0222] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0223] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0224] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A rapid positioning device for damaged cable insulation in a cable trench, characterized in that: The device comprises: An image data acquisition module is used to acquire image data of cables in the cable trench during the inspection of the cable trench; wherein the image data is visible light image data; An edge detection module, used to perform edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data; A local anomaly recognition module is used to recognize the edge detection data, and if there is a local bulge, it is recognized as a local anomaly of edge damage; The prompt module is used to generate prompt information of edge damage local abnormalities.

2. The rapid positioning device for damaged cable insulation in a cable trench according to claim 1, characterized in that: The device also includes: A crack detection module is used to detect cracks in the cable insulation layer in the visible light image data to obtain crack detection data; The crack anomaly identification module is used to identify the crack detection data, and if there is a rupture in the insulation layer, it is identified as a local abnormality of crack damage.

3. The rapid positioning device for damaged cable insulation in a cable trench according to claim 1, characterized in that: The image data acquisition module is further used to acquire cable image data at the cable fixing part; The device also includes: A shrinkage detection module, used to identify whether the shrinkage degree of the cable insulation layer at the cable fixing part is greater than a set threshold; A damage degree determination module, used to determine the damage degree of the cable insulation layer according to the correlation relationship between the shrinkage degree and the preset damage degree when the shrinkage degree is greater than a set threshold value; The prompt module is also used for: When the degree of damage is greater than a preset degree, a prompt message is generated.

4. The rapid positioning device for damaged cable insulation in a cable trench according to claim 3, characterized in that: The shrinkage degree detection module is further used for: recognizing that the curvature of the cable insulation layer at the cable fixing part reaches a set value; The damage degree determination module is further used for: When the curvature reaches a set value, the degree of damage to the cable insulation layer is determined according to a correlation between the curvature and a preset degree of damage.

5. The rapid positioning device for damaged cable insulation in a cable trench according to claim 1, characterized in that: The image data acquisition module is further used to acquire cable image data at the cable fixing part; The device also includes: A fixture parameter acquisition module is used to obtain the size information and material information of the fixture; A model building module, used to build a heat dissipation model and a water immersion model at the cable fixing part according to the size information and the material information; An aging degree estimation module, used for estimating the aging rate of the cable insulation layer at the cable fixing part according to the heat dissipation model and the water immersion model; The prompt information generation module is used to generate aging prompt information according to the estimation result.

6. The rapid positioning device for damaged cable insulation in a cable trench according to claim 1, characterized in that: The device also includes: An ultrasonic signal acquisition module is used to acquire ultrasonic signals during cable inspection through an ultrasonic sensor; A parameter information extraction module, used to extract parameter information of the ultrasonic signal; A matching module, used for matching the ultrasonic signal with the characteristics of partial discharge caused by damage to the cable insulation layer based on the parameter information; A prompt information production module is used to generate partial discharge prompt information after identifying that the matching similarity is greater than a first set threshold; after identifying that the matching similarity is less than the first set threshold and greater than a second set threshold, generate prompt information of suspected partial discharge; wherein the first set threshold is greater than the second set threshold.

7. The rapid positioning device for damaged cable insulation in a cable trench according to claim 1, characterized in that: The edge detection module is specifically used for: Using a gradient detection algorithm to perform gradient detection on the visible light image data to obtain boundary information; The edge position of the cable insulation layer is determined according to the boundary information to obtain edge detection data.

8. A method for quickly locating damaged cable insulation in a cable trench, characterized in that: The method comprises: During the cable trench inspection, image data of the cables in the cable trench is obtained; wherein the image data is visible light image data; Performing edge detection on the edge position of the cable insulation layer in the visible light image data to obtain edge detection data; Identify the edge detection data, and if there is a local bulge, identify it as a local abnormality of edge damage; Generate prompt information for local abnormalities of edge damage.

9. The method for quickly locating damaged cable insulation in a cable trench according to claim 8, characterized in that: The method further comprises: Detecting cracks in the cable insulation layer in the visible light image data to obtain crack detection data; The crack detection data is identified, and if there is a rupture in the insulation layer, it is identified as a local abnormality of crack damage.

10. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the method for quickly locating damaged cable insulation in a cable trench as described in any one of claims 8 to 9 are implemented.

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