CN110009603B

CN110009603B - High-voltage cable insulation detection method and high-voltage cable maintenance method

Info

Publication number: CN110009603B
Application number: CN201910192454.6A
Authority: CN
Inventors: 索智鑫; 林志波; 宋强; 卢廷杰; 劳卫伦; 陆宏治; 陈凌剑
Original assignee: Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
Current assignee: Guangzhou Power Supply Bureau of Guangdong Power Grid Co Ltd
Priority date: 2019-03-14
Filing date: 2019-03-14
Publication date: 2021-01-29
Anticipated expiration: 2039-03-14
Also published as: CN110009603A

Abstract

The application relates to a high-voltage cable insulation detection method and a high-voltage cable maintenance method, wherein the insulation detection method comprises the following steps: the four image acquisition instruments are deployed at the same section position of the high-voltage cable, the four shooting centers form a rectangle, and image acquisition is simultaneously carried out from respective angles in parallel; and respectively detecting the concave-convex edges of the surface images of the insulating layers, determining whether the surface smoothness of the insulating layer of the high-voltage cable corresponding to the surface images of the insulating layers meets the requirements, and judging that the surface smoothness of the insulating layer of the high-voltage cable does not meet the quality requirement when any one of the detection results is negative. The automatic detection is realized, the potential accident risk caused by manual detection is avoided, the detection effect quality is stable, the detection efficiency is higher, the detection section position of the rectangular design is adopted, the image acquired by each image acquisition instrument can reflect the surface of the high-voltage cable insulating layer more accurately, and therefore whether the smoothness of the surface of the high-voltage cable insulating layer meets the requirement or not can be judged subsequently, and the detection effect is more accurate.

Description

High-voltage cable insulation detection method and high-voltage cable maintenance method

Technical Field

The application relates to the field of high-voltage cable insulation detection, in particular to a high-voltage cable insulation detection method and a high-voltage cable maintenance method.

Background

The uneven surface of the high-voltage cable insulating layer can cause the uneven electric field to cause safety accidents, so that the quality of the cable is ensured to play a key role in stable power transmission. However, the smoothness and flatness detection of the surface of the cable insulation layer is difficult, and digital image acquisition is not facilitated, so that a mature application technology is not available depending on manual inspection at present, but more manpower is consumed depending on manual detection, the quality of a detection effect is not stable enough, and the detection efficiency is low.

Disclosure of Invention

Accordingly, there is a need for a method for detecting insulation of a high voltage cable and a method for maintaining a high voltage cable.

A high-voltage cable insulation detection method comprises the following steps:

s1000, a detection platform is set up, the detection platform comprises digital image processing equipment and at least one image capturing group, each image capturing group comprises four image acquiring instruments, the four image acquiring instruments are uniformly arranged at four corners of the same section of the high-voltage cable, photographing centers of the four image acquiring instruments form a rectangle and are respectively positioned at the four corners of the rectangle, the digital image processing equipment is respectively connected with each image acquiring instrument, and the digital image processing equipment is also connected with a detection judgment module;

s2000, extracting image information of the surface of the high-voltage cable insulation layer through the detection platform; for each image capturing group, the four image acquiring instruments parallelly acquire images of the high-voltage cable from respective angles at the same time, respectively obtain surface images of the insulating layer and transmit the surface images to the digital image processing equipment;

s3000, the digital image processing equipment respectively detects the concave-convex edges of the surface images of the insulating layers, determines whether the surface smoothness of the insulating layer of the high-voltage cable corresponding to the surface images of the insulating layers meets the requirements or not, obtains a detection result and transmits the detection result to the detection judgment module;

and S4000, judging that the surface smoothness of the insulating layer of the high-voltage cable does not meet the quality requirement by the detection judgment module when any one of the detection results is negative.

According to the high-voltage cable insulation detection method, whether the flatness of the surface of the high-voltage cable insulation layer corresponding to the surface image of each insulation layer meets the requirement or not is detected through designing the detection platform, on one hand, automatic detection is achieved, human resources are saved, on the other hand, potential accident risks caused by manual detection are avoided, on the other hand, image acquisition to the high-voltage cable is facilitated rapidly and efficiently, the detection effect quality is stable, the detection efficiency is high, the detection cross section position is designed in a rectangular mode, the image acquired by each image acquisition instrument can reflect the surface of the high-voltage cable insulation layer more accurately, and therefore whether the flatness of the surface of the high-voltage cable insulation layer meets the requirement or not is favorably judged subsequently, and the detection.

In one embodiment, the detection platform comprises at least two image capturing groups, and the plane of the rectangle formed by the shooting centers of the four image acquiring instruments in the image capturing groups is parallel to the plane of the rectangle formed by the shooting centers of the four image acquiring instruments in other image capturing groups.

In one embodiment, the rectangle is a square.

In one embodiment, the distance between two adjacent image capturing groups is the shooting distance of the image acquisition instrument; in one embodiment, the image acquisition instrument has a shooting distance of 2 meters.

In one embodiment, the inspection platform comprises two of the image capture groups.

In one embodiment, the digital image processing device comprises a plurality of digital image processors, each of the digital image processors is connected with one of the image acquisition instruments in a one-to-one correspondence manner, and each of the digital image processors is further connected with the detection and judgment module.

In one embodiment, the detection platform further includes a client, and the detection judgment module is disposed in the client.

In one embodiment, the high-voltage cable insulation detection method specifically comprises the following steps;

s1100, a detection platform is built, the detection platform comprises a plurality of image capturing groups, each image capturing group comprises four industrial cameras, the four industrial cameras are uniformly arranged at four corners of the same cross section of the high-voltage cable, and the shooting centers of the four industrial cameras form a rectangle and are respectively positioned at the four corners of the rectangle;

s1200, each industrial camera is respectively connected with a digital image processor, and an image edge detection module is arranged in each digital image processor;

s1300, each digital image processor is respectively connected with a detection judgment module;

s2000, extracting image information of the surface of the high-voltage cable insulation layer through the detection platform; for each image capturing group, four industrial cameras are used for simultaneously acquiring images of the high-voltage cable in parallel to respectively obtain an image G of the surface of the insulating layer₁、G₂、G₃、G₄And G is₁、G₂、G₃、G₄Respectively transmitted to the digital image processor U corresponding to each industrial camera₁、U₂、U₃、U₄；G₁、G₂、G₃、G₄All the sizes of (A) and (B) are W × L, W represents G₁、G₂、G₃、G₄The number of pixels in each row, L represents G₁、G₂、G₃、G₄The number of pixel points in each row, W and L are positive integers;

S3000，U₁、U₂、U₃、U₄the image edge detection modules respectively detect G in parallel₁、G₂、G₃、G₄Concave-convex edge of (1), determination G₁、G₂、G₃、G₄Whether the surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement or not, U_qImage edge detection software of (G)_qThe steps of the concave-convex edge are as follows, wherein q is more than or equal to 1 and less than or equal to 4;

S3100，U_qthe image edge detection software adopts wiener filtering to the digital image G_qPerforming denoising operation to obtain G_qA，G_qAThe size is W multiplied by L;

S3200，U_qimage edge detection software of (1) calculates G_qAThe image threshold value T of (a);

S3300，U_qimage edge detection software pair G_qAPerforming edge detection on the concave and convex area to determine G_qAWhether the corresponding high-voltage cable insulating layer has a real edge or not, and if so, G_qAThe surface smoothness of the corresponding high-voltage cable insulating layer does not meet the requirement, and if no real edge exists, G_qAThe surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement; the edge detection comprises the following steps:

s3310, set G_qAMiddle a row and b column pixel point P_a,bAccess Flag of (1) is false, P_a,bFlag for access Flag of_a,bIndicating, i.e. commanding Flag_a,bRespectively initializing a pixel stack S and a pixel queue Q to be empty, setting a Connected flag Connected for the queue Q, and defaulting Connected to be false;

s3320, let row variable a be 1 and column variable b be 1;

s3321, if 1 is less than or equal to a<L is 1. ltoreq. b<W, executing the step S33211; if b is W and a<L, executing the step S3322; if a is L and b<W performs step S3323; if a is L and b is W, then the whole G_qAAfter the detection is finished and no real edge exists, the detection result is G_qAThe surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement, the high-voltage cable insulating layer is transmitted to the detection and judgment module, and the step S4000 is executed;

s33211, calculating a pixel P_a,bGradient value K of_a,b，

G_xRepresents P_a,bGray value of the image detected by the transverse edge, G_yRepresents P_a,bImage gray values detected by the longitudinal edges;

s33212, if P_a,bGradient value K of_a,bGreater than or equal to T, then P_a,bFor strong edge points, let Flag_a,bStep S3321 is performed, where b is false and b + 1; if P_a,bGradient value K of_a,bLess than T, P is determined_a,bWeak edge points, if Flag_a,bSet b to b +1, go to step S3321, if Flag is set_a,bStep S33213 is performed;

s33213, adding P_a,bPut S as an element S in S_a,bA 1 is to P_a,bPut Q as an element Q in Q_a,b；

S33214, if S is empty and the Connected flag Connected of Q is false, sequentially fetching out the pixels in Q, emptying the queue Q, making b equal to b +1, executing step S3321, if the Connected flag Connected of Q is true, the curve formed by the pixels stored in Q is a real edge, and obtaining G_qAIf true edge exists, the detection result is G_qASequentially taking out pixel points in Q when the surface smoothness of the corresponding high-voltage cable insulating layer does not meet the requirement, emptying the queue Q, transmitting the detection result to the detection judgment module and executing the step S4000; if S is not empty, taking out pixel point S from S_a,bStep S332141 is executed;

s332141, if a is 1 and b is 1, searches for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b+1、P_a+1,b+1And P_a+1,bIf a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 3 neighborhood pixel points are weak edge points and the flags of 3 neighborhood pixel points are false, 3 neighborhood pixel points are respectively placed into S and Q, the Flag of the 3 neighborhood pixel points is equal to true, step S33214 is executed, if the flags of all the weak edge points in the neighborhood pixel points are equal to true, step S33214 is executed, if a strong edge point exists in the neighborhood pixel points, the Connected of the queue Q is set to true, and step S33214 is executed; if a is not 1 and b is 1, then the step is executedStep S332142;

s332142, if b is 1 and 1<a<L, search S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a-1,b、P_a-1,b+1、P_a,b+1、P_a+1,b+1、P_a+1,bIf a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is set to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 5 neighborhood pixels are weak edge points and the flags of the 5 neighborhood pixels are set to false, the 5 neighborhood pixels are respectively placed into S and Q and the Flag of the 5 neighborhood pixels is set to true, step S33214 is executed, if the flags of all weak edge points in the neighborhood pixels are set to true, step S33214 is executed, if a strong edge point exists in the neighborhood pixels, the Connected value of the queue Q is set to true, and step S33214 is executed; if b is not satisfied, 1 and 1<a<L, go to step S332143;

s332143, if a is 1 and 1<b<W, then search for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b-1、P_a+1,b-1、P_a+1,b、P_a+1,b+1、P_a,b+1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 5 neighborhood pixel points are weak edge points and the flags of the 5 neighborhood pixel points are equal to false, the 5 neighborhood pixel points are respectively placed into S and Q, the Flag of the 5 neighborhood pixel points is set to true, step S33214 is executed, if the flags of all weak edge points in the neighborhood pixel points are equal to true, step S33214 is executed, if a strong edge point exists in the neighborhood pixel points, the Connected value of the queue Q is set to true, and step S33214 is executed; if a is not 1 and 1<b<W, go to step S332144;

s332144, if 1<a<L is 1<b<W, then search for S_a,bIn the image G_1ANeighborhood pixel P of middle position (a, b)_a-1,b-1、P_a-1,b、P_a-1,b+1、P_a,b+1、P_a+1,b+1、P_a+1,b、P_a+1,b-1、P_a,b-1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 8 neighborhood pixels are weak edge points and the flags of 8 neighborhood pixels are equal to false, the 8 neighborhood pixels are respectively placed into S and Q and the flags of 8 neighborhood pixels are set to true, step S33214 is executed, if the flags of all weak edge points in the neighborhood pixels are equal to true, step S33214 is executed, if a strong edge point exists in the neighborhood pixels, the Connected value of queue Q is set to true, and step S33214 is executed; if not 1<a<W and 1<b<L, go to step S33214;

s3322, search S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a-1,b、P_a-1,b-1、P_a,b-1、P_a+1,b-1、P_a+1,bIf a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and the Flag of the edge point is set to true, a is a +1, b is 0, step S33214 is executed, if 5 neighborhood pixel points are weak edge points and the flags of the 5 neighborhood pixel points are both Flag equal to false, 5 neighborhood pixel points are respectively placed into S and Q, the Flag of the 5 neighborhood pixel points is set to true, a +1, b is 0, step S33214 is executed, if the flags of all weak edge points in the neighborhood pixel points are equal to true, a is a +1, b is 0, step S33214 is executed, if a strong edge point exists in the neighborhood pixel points, the Connected of Q is set to true, a is a +1, b is 0, and step S33214 is executed;

s3323, search S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b-1、P_a-1,b-1、P_a-1,b、P_a-_1,b+1、P_a,b+1If a weak edge point exists in a neighborhood pixel point and the weak edge point Flag is equal to false, the weak edge point is respectively put into S and Q, and Flag of the edge point is set to true, step S33214 is executed, if 5 neighborhood pixel points are the weak edge point and Flag of 5 neighborhood pixel points is equal to false, 5 neighborhood pixel points are respectively put into S and Q, and Flag of 5 neighborhood pixel points is set to trueStep S33214 is executed, if the Flag of all weak edge points in the neighborhood pixel point is true, step S33214 is executed, and if a strong edge point exists in the neighborhood pixel point, Connected of the queue Q is set to true, and step S33214 is executed;

s4000, the detection judgment module is connected with the slave U₁、U₂、U₃、U₄Respectively receiving G by the image edge detection module₁、G₂、G₃、G₄The result of whether the surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement or not is judged, and if all 4 results meet the requirement, G is judged₁、G₂、G₃、G₄The surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement, and the surface smoothness of the insulating layer of the high-voltage cable with the corresponding length section meets the quality requirement; if one of the 4 results is not satisfactory, G is determined₁、G₂、G₃、G₄The surface smoothness of the corresponding high-voltage cable insulating layer does not meet the requirement, and the surface smoothness of the insulating layer of the high-voltage cable with the corresponding length section does not meet the quality requirement.

In one embodiment, in step S2000, before the image information of the surface of the high-voltage cable insulation layer is extracted by the detection platform, the method for detecting insulation of a high-voltage cable further includes the steps of: moving the detection platform; the distance for moving the detection platform is L1+ L2, wherein L1 is the length of the detection platform, and L2 is the shooting distance of the image acquisition instrument.

A high voltage cable maintenance method comprising any one of the high voltage cable insulation detection methods, the high voltage cable maintenance method further comprising the steps of: and when the surface smoothness of the insulating layer of the high-voltage cable is judged not to meet the quality requirement, maintaining the cable.

According to the high-voltage cable maintenance method, whether the flatness of the surface of the high-voltage cable insulating layer corresponding to the surface images of the insulating layers meets the requirements or not is detected through designing the detection platform, on one hand, automatic detection is achieved, human resources are saved, on the other hand, potential accident risks caused by manual detection are avoided, on the other hand, image acquisition on the high-voltage cable is facilitated rapidly and efficiently, the detection effect quality is stable, the detection efficiency is high, the detection cross section position is designed in a rectangular mode, the image acquired by each image acquisition instrument can reflect the surface of the high-voltage cable insulating layer more accurately, and accordingly, whether the flatness of the surface of the high-voltage cable insulating layer meets the requirements or not is favorably judged subsequently, the detection effect is more accurate, cable maintenance can be carried out timely and effectively.

Drawings

Fig. 1 is a schematic flow chart of an embodiment of a high-voltage cable insulation detection method according to the present application.

Fig. 2 is a schematic diagram illustrating a positional relationship between a square formed by four image acquisition instruments of an image capturing group and a high-voltage cable according to an embodiment of the high-voltage cable insulation detection method.

Fig. 3is a schematic diagram illustrating a positional relationship between a square formed by four image capturing devices in an image capturing group and a high voltage cable according to another embodiment of the insulation detection method for a high voltage cable.

Fig. 4 is a schematic diagram illustrating a positional relationship between a square formed by four image capturing devices in an image capturing group and a high voltage cable according to another embodiment of the insulation detection method for a high voltage cable.

Fig. 5 is a schematic flow chart of another embodiment of the insulation detection method for a high-voltage cable according to the present application.

Fig. 6 is a schematic flow chart of an embodiment of a high-voltage cable maintenance method according to the present application.

Detailed Description

In order to make the aforementioned objects, features and advantages of the present application more comprehensible, embodiments accompanying the present application are described in detail below with reference to the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application. This application is capable of embodiments in many different forms than those described herein and that modifications may be made by one skilled in the art without departing from the spirit and scope of the application and it is therefore not intended to be limited to the specific embodiments disclosed below.

It will be understood that when an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or intervening elements may also be present. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The terms "vertical," "horizontal," "left," "right," and the like as used herein are for illustrative purposes only and do not represent the only embodiments.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein in the description of the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

As shown in fig. 1, a method for detecting insulation of a high voltage cable includes the following steps: s1000, a detection platform is set up, the detection platform comprises digital image processing equipment and at least one image capturing group, each image capturing group comprises four image acquiring instruments, the four image acquiring instruments are uniformly arranged at four corners of the same section of the high-voltage cable, photographing centers of the four image acquiring instruments form a rectangle and are respectively positioned at the four corners of the rectangle, the digital image processing equipment is respectively connected with each image acquiring instrument, and the digital image processing equipment is also connected with a detection judgment module; s2000, extracting image information of the surface of the high-voltage cable insulation layer through the detection platform; for each image capturing group, the four image acquiring instruments parallelly acquire images of the high-voltage cable from respective angles at the same time, respectively obtain surface images of the insulating layer and transmit the surface images to the digital image processing equipment; s3000, the digital image processing equipment respectively detects the concave-convex edges of the surface images of the insulating layers, determines whether the surface smoothness of the insulating layer of the high-voltage cable corresponding to the surface images of the insulating layers meets the requirements or not, obtains a detection result and transmits the detection result to the detection judgment module; and S4000, judging that the surface smoothness of the insulating layer of the high-voltage cable does not meet the quality requirement by the detection judgment module when any one of the detection results is negative. According to the high-voltage cable insulation detection method, whether the flatness of the surface of the high-voltage cable insulation layer corresponding to the surface image of each insulation layer meets the requirement or not is detected through designing the detection platform, on one hand, automatic detection is achieved, human resources are saved, on the other hand, potential accident risks caused by manual detection are avoided, on the other hand, image acquisition to the high-voltage cable is facilitated rapidly and efficiently, the detection effect quality is stable, the detection efficiency is high, the detection cross section position is designed in a rectangular mode, the image acquired by each image acquisition instrument can reflect the surface of the high-voltage cable insulation layer more accurately, and therefore whether the flatness of the surface of the high-voltage cable insulation layer meets the requirement or not is favorably judged subsequently, and the detection.

In one embodiment of the application, the high-voltage cable insulation detection method comprises the following steps of part of or all of the following embodiments; namely, the insulation detection method for the high-voltage cable comprises the following technical characteristics in part or all.

In one embodiment, S1000, a detection platform is established, the detection platform comprises digital image processing equipment and at least one image capturing group, each image capturing group comprises four image acquiring instruments, the four image acquiring instruments are uniformly arranged at four corners of the same section of the high-voltage cable, the shooting centers of the four image acquiring instruments form a rectangle and are respectively located at the four corners of the rectangle, the digital image processing equipment is respectively connected with each image acquiring instrument, and the digital image processing equipment is further connected with a detection judgment module; namely, the shooting centers of the four image acquisition instruments are positioned at four corners of a rectangle. In one embodiment, the rectangle is a square, that is, the centers of the four image acquiring apparatuses are located at four corners of the square. As shown in fig. 2, in one embodiment, each of the image capturing groups includes four image capturing apparatuses 100, four image capturing apparatuses 100 are uniformly disposed at four corners of the same cross-sectional position of the high voltage cable 200, and the photographing centers 110 of the four image capturing apparatuses form a square and are respectively located at the four corners of the square, that is, the photographing centers or centers called the viewing positions of the four image capturing apparatuses are located at the four corners of the same cross-sectional position of the high voltage cable 200 and form a square 300. As shown in fig. 3, in one embodiment, the photographing centers 110 of four image capturing apparatuses (one of which is shielded by the high voltage cable 200) of one image capturing group are located at four corners of the same cross-sectional position of the high voltage cable 200 and form a square, the photographing directions of the photographing centers 110 of four image capturing apparatuses 100 converge at the same position of the high voltage cable 200, and the distance between two adjacent image capturing groups is L2. As shown in fig. 4, in one embodiment, the photographing centers 110 of the four image capturing apparatuses of one image capturing group are located at four corners of the same cross-sectional position of the high voltage cable 200 and form a square, the photographing directions of the photographing centers 110 of the four image capturing apparatuses 100 converge at the same position of the high voltage cable 200, and the distance between two adjacent image capturing groups is L2. In one embodiment, the detection platform comprises at least two image capturing groups, and the planes of the rectangles formed by the shooting centers of the four image acquiring instruments in the image capturing groups are parallel to the planes of the rectangles formed by the shooting centers of the four image acquiring instruments in other image capturing groups; namely, four image acquisition instruments of each image capturing group are respectively arranged in a one-to-one correspondence manner, and a cuboid is formed in a spatial manner; that is, the section where the shooting centers of the four image acquisition instruments of each image capturing group are uniformly arranged at the same section position of the high-voltage cable is parallel to the corresponding section where the shooting centers of the four image acquisition instruments of the other image capturing groups are uniformly arranged at the same section position of the high-voltage cable. In one embodiment, the distance between two adjacent image capturing groups is 2 meters, that is, the distance between two parallel sections is 2 meters, that is, L2 is 2 meters, and it is understood that the length of L2 depends on the accuracy of an image acquisition instrument such as an industrial camera or a video camera. In one embodiment, the image acquisition instrument is or includes an industrial camera. Further, in one embodiment, four of the image acquisition instruments of each of the image capture sets form a square. In one embodiment, the inspection platform comprises two of the image capture groups. In one embodiment, the distance between the two image capturing groups is the shooting distance of the image acquisition instrument; in one embodiment, the image acquisition instrument has a shooting distance of 2 meters. In one embodiment, the digital image processing device comprises a plurality of digital image processors, each of the digital image processors is connected with one of the image acquisition instruments in a one-to-one correspondence manner, and each of the digital image processors is further connected with the detection and judgment module. That is, the same number of digital image processors are provided for each matching of the image acquisition instruments. In one embodiment, the detection platform further includes a client, and the detection judgment module is disposed in the client. Further, in one embodiment, the client includes a mobile terminal, a PC, a tablet, or the like. By means of the design, the problem that the cross-linked polyethylene insulating layer shows that the flatness detection difficulty is large is solved by means of an image acquisition instrument such as an industrial camera and an insulating layer surface flatness detection algorithm below, and the detection cross section position of the rectangular design is matched, so that whether the flatness of the surface of the high-voltage cable insulating layer meets the requirement or not can be judged conveniently, and the detection effect is more accurate.

In one embodiment, S2000, extracting surface image information of the high-voltage cable insulation layer through the detection platform; for each image capturing group, the four image acquiring instruments parallelly acquire images of the high-voltage cable from respective angles at the same time, respectively obtain surface images of the insulating layer and transmit the surface images to the digital image processing equipment; in one embodiment, in step S2000, before the image information of the surface of the high-voltage cable insulation layer is extracted by the detection platform, the method for detecting insulation of a high-voltage cable further includes the steps of: moving the detection platform; the distance for moving the detection platform is L1+ L2, wherein L1 is the length of the detection platform, and L2 is the shooting distance of the image acquisition instrument, i.e. the distance between two adjacent image capturing groups. Further, in one embodiment, the detection platform is translated, i.e. the direction of movement of the detection platform is parallel to the high voltage cable. In one embodiment, the length of the detection platform is the distance between the image capturing groups at two ends, that is, the length of the detection platform is the total length of the image capturing groups of the detection platform. By the design, the surface smoothness of the insulating layer of the high-voltage cable can be continuously detected by translating the detection platform, so that the automatic detection of the long cable is really realized. Further, in one embodiment, for each of the image capturing groups, four industrial cameras located at the same cross-sectional position of the high-voltage cable photograph the high-voltage cable at the same time from respective angles in parallel to obtain four images, and the four images are transmitted to the digital image processors corresponding to the industrial cameras respectively. The image is the surface image of the insulating layer.

In one embodiment, S3000, the digital image processing device respectively detects the concave-convex edges of the surface images of the insulating layers, determines whether the surface smoothness of the insulating layer of the high-voltage cable corresponding to the surface images of the insulating layers meets the requirement, obtains a detection result, and transmits the detection result to the detection and judgment module; further, in one embodiment, before detecting the image, the image is denoised to improve the processing speed, and the strong edge point/the weak edge point of the image is judged by adopting the image threshold, which is beneficial to improving the accuracy of the edge point judgment. Further, in one embodiment, the digital image processing device detects the concave-convex edges of the surface images of the insulating layers respectively in a breadth-first traversal mode. The design is favorable for displaying the adjacency relation between the strong edge points, is favorable for judging the edge curve, and improves the detection efficiency and the accuracy of edge detection. In one embodiment, the image edge detection module of each digital image processor can be converted into image edge detection software through software, and the image edge detection module detects the concave-convex edges of the images in parallel and judges whether the surface smoothness of the high-voltage cable insulating layer corresponding to each image meets the requirement or not.

In one embodiment, in S4000, when any one of the detection results is negative, the detection and judgment module determines that the surface smoothness of the insulating layer of the high-voltage cable does not meet the quality requirement. In cooperation with step S3000, the image processor processes the image and then determines by integrating the image results, thereby reducing the workload of the image processor in processing each image information and increasing the processing speed of the image processor. It can be understood that if one of the detection results is not satisfactory, the surface smoothness of the insulating layer of the high-voltage cable is judged not to meet the quality requirement.

By the design, the built detection platform can realize 360-degree dead-angle-free information capture on the surface image of the high-voltage cable insulating layer in a mode of more than 90-degree angle superposition through four image acquisition instruments, and detects the surface smoothness of the insulating layer in the image through the image acquisition instruments, particularly an image processor connected with an industrial camera; therefore, automatic inspection is realized, human resources are saved, and potential accident risks caused by manual inspection are avoided; the detection device has the advantages that the image acquisition is rapidly and efficiently carried out on the high-voltage cable, the quality of the detection effect is stable, the detection efficiency is high, the detection section position with the rectangular design is adopted, the image acquired by each image acquisition instrument can more accurately reflect the surface of the high-voltage cable insulation layer, and therefore whether the flatness of the surface of the high-voltage cable insulation layer meets the requirement or not can be conveniently and subsequently judged, and the detection effect is more accurate.

A specific example is given below. In one embodiment, the insulation detection method for the high-voltage cable specifically comprises the following partial or all steps.

S1100, a detection platform is built, the detection platform comprises a plurality of image capturing groups, each image capturing group comprises four industrial cameras, the four industrial cameras are uniformly arranged at four corners of the same cross section position of the high-voltage cable, the shooting centers of the four industrial cameras form a rectangle, and the shooting centers of the four industrial cameras are respectively located at the four corners of the rectangle;

further, in one embodiment, four industrial cameras are arranged on the high-voltage cable at intervals of a distance L (length), the four industrial cameras are uniformly arranged at the upper left side, the upper right side, the lower left side and the lower right side of the same cross section position of the high-voltage cable, and the industrial cameras form a 90-degree stereoscopic space angle with each other to capture image information on the surface of the insulating layer of the high-voltage cable; l (length) is 2 meters to 3 meters, for example L (length) is 2 meters or 3 meters, and when the industrial camera precision is higher, L (length) can be higher. The industrial camera is a CCD (Charge coupled Device) industrial line camera, wherein the parameter requirements are as follows: the video system adopts a PAL system of 768 multiplied by 576, the pixel depth of 12 bits, and a line-by-line exposure mode, the exposure time is consistent with the line period, and the pixel size of the camera is 5 μm. Each industrial camera is respectively connected with a digital image processor, the digital image processor is a special integrated chip or a digital signal processor or a field programmable gate array FPGA, and image edge detection software is burnt in the digital image processor to serve as an image edge detection module; the four digital image processors are all connected with the client, and a detection judgment module is installed on the client, for example, the detection judgment module is set as result judgment software in a software mode.

S2000, extracting image information of the surface of the high-voltage cable insulation layer through the detection platform; in one embodiment, an industrial camera is used to extract surface image information of the high voltage cable insulation layer. For each image capturing group, four industrial cameras are used for simultaneously acquiring images of the high-voltage cable in parallel, namely, the four industrial cameras located at the same cross section position of the high-voltage cable are used for simultaneously photographing the high-voltage cable from respective angles in parallel to respectively obtain an image G of the surface of the insulating layer₁、G₂、G₃、G₄And G is₁、G₂、G₃、G₄Respectively transmitted to the digital image processor U corresponding to each industrial camera₁、U₂、U₃、U₄；G₁、G₂、G₃、G₄All the sizes of (A) and (B) are W × L, W represents G₁、G₂、G₃、G₄Each row ofNumber of pixels, L represents G₁、G₂、G₃、G₄The number of pixel points in each row, W and L are positive integers; in one embodiment, before or after the image information of the surface of the high-voltage cable insulation layer is extracted by the detection platform, the high-voltage cable insulation detection method further comprises the following steps: moving the detection platform; the distance for moving the detection platform is L1+ L2, wherein L1 is the length of the detection platform, and L2 is the shooting distance of the image acquisition instrument.

S3000，U₁、U₂、U₃、U₄The image edge detection modules respectively detect G in parallel₁、G₂、G₃、G₄Concave-convex edge of (1), determination G₁、G₂、G₃、G₄Whether the surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement or not, namely U₁Image edge detection software of (G)₁Edge of (U), U₂Image edge detection software of (G)₂Edge of (U), U₃Image edge detection software of (G)₃Edge of (U), U₄Image edge detection software of (G)₄Edge of (U), U₁、U₂、U₃、U₄Image edge detection software pair G₁、G₂、G₃、G₄The edge detection method of (2) is identical. U shape_qImage edge detection software of (G)_qThe steps of the concave-convex edge are as follows, wherein q is more than or equal to 1 and less than or equal to 4. And detecting concave-convex edges of the surface images of the insulating layers respectively in a breadth-first traversal mode. The design is favorable for displaying the adjacency relation between the strong edge points, is favorable for judging the edge curve, and improves the detection efficiency and the accuracy of edge detection.

S3100，U_qThe image edge detection software adopts wiener filtering to the digital image G_qPerforming denoising operation to obtain G_qA，G_qAThe size is W multiplied by L; further, in one embodiment, step S3100 includes: for G_qDe-noising by wiener filtering and adopting de-noising function G in Matlab_qA,noise]＝wiener2(G_q,[3,3]) For image G_qImage denoising using a 3 × 3 filter window size, where G_qAFor de-noised images, noise is image G_qThe noise power estimate of (2).

S3200，U_qImage edge detection software of (1) calculates G_qAThe image threshold value T of (a); further, in one embodiment, step S3200 includes: using the maximum inter-class variance function graythresh (G) in Matlab_qA) Determining an image G_qAT, i.e. T ═ graythresh (G)_qA)。

s3310, perform initialization, including: setting G_qAMiddle a row and b column pixel point P_a,bAccess Flag of (1) is false, P_a,bFlag for access Flag of_a,bIndicating, i.e. commanding Flag_a,bRespectively initializing a pixel stack S and a pixel queue Q to be empty, setting a Connected flag Connected for the queue Q, and defaulting Connected to be false;

s3320, let row variable a be 1 and column variable b be 1;

s3321, if 1 is less than or equal to a<L is 1. ltoreq. b<W, executing the step S33211; if b is W and a<L, executing the step S3322; if a is L and b<W performs step S3323; if a is L and b is W, then the whole G_qAAfter the detection is finished and no real edge exists, the detection result is G_qAThe surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement, the high-voltage cable insulating layer is transmitted to the detection and judgment module, and the step S4000 is executed; wherein, if a ═ L and b ═ W, the whole G is specified_qAAfter the detection is finished and no real edge exists, outputting G to the client_qAThe corresponding cable meets the requirements ", executeStep S4000;

s33211, calculating a pixel P_a,bGradient value K of_a,b，

G_xRepresents P_a,bGray value of the image detected by the transverse edge, G_yRepresents P_a,bImage gray values detected by the longitudinal edges; further, in one embodiment, in step S33211, the pixel point P is_a,bGradient value K of_a,bCalculating by using a Prewitt operator, comprising the following steps:

K_a,b＝max[G_x,G_y]

wherein, F (a, b) represents the gray scale value of the pixel (a, b), if a is 1, F (a-1, b-1) is 0, F (a-1, b) is 0, and F (a-1, b +1) is 0; if b is 1, let F (a +1, b-1) be 0, F (a-1, b-1) be 0, F (a, b-1) be 0; if a is equal to L, let F (a +1, b-1) be 0, F (a +1, b +1) be 0; if b is W, F (a +1, b +1) is 0, F (a-1, b +1) is 0, and F (a, b +1) is 0.

S33214, Connected flag fa of Q if S is emptyAnd the lse sequentially takes out the pixel points in the Q, empties the queue Q, makes b equal to b +1, executes the step S3321, and if the Connected flag Connected of the Q is equal to true, the curve formed by the pixel points stored in the Q is a real edge, and obtains G_qAIf true edge exists, the detection result is G_qASequentially taking out pixel points in Q when the surface smoothness of the corresponding high-voltage cable insulating layer does not meet the requirement, emptying the queue Q, transmitting the detection result to the detection judgment module and executing the step S4000; if S is not empty, taking out pixel point S from S_a,bStep S332141 is executed; for example, G_qAWhen there is a true edge, illustrate G_qAThe corresponding cable does not meet the requirement, pixel points in Q are sequentially taken out, the queue Q is emptied, and G is output to the client_qAThe corresponding cable does not meet the requirement, and step S4000 is executed.

S332141, if a is 1 and b is 1, searches for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,_b+1、P_a+1,b+1And P_a+1,bIf a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 3 neighborhood pixel points are weak edge points and the flags of 3 neighborhood pixel points are false, 3 neighborhood pixel points are respectively placed into S and Q, the Flag of the 3 neighborhood pixel points is equal to true, step S33214 is executed, if the flags of all the weak edge points in the neighborhood pixel points are equal to true, step S33214 is executed, if a strong edge point exists in the neighborhood pixel points, the Connected of the queue Q is set to true, and step S33214 is executed; if a is not 1 and b is 1, performing step S332142;

s332142, if b is 1 and 1<a<L, search S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a-1,b、P_a-1,b+1、P_a,b+1、P_a+1,b+1、P_a+1,bIf a weak edge point exists in the neighborhood pixel points and the Flag of the weak edge point is false, the weak edge point is respectively put into the S and the Q, the Flag of the weak edge point is set to true, step S33214 is executed, and if 5 neighborhood pixel points are all weak edgesEdge points and Flag of 5 neighborhood pixel points are Flag ═ false, 5 neighborhood pixel points are respectively put into S and Q, Flag ═ true of the 5 neighborhood pixel points is set, step S33214 is executed, if Flag of all weak edge points in the neighborhood pixel points is true, step S33214 is executed, if strong edge points exist in the neighborhood pixel points, Connected ═ true of queue Q is set, and step S33214 is executed; if b is not satisfied, 1 and 1<a<L, go to step S332143;

s332144, if 1<a<L is 1<b<W, then search for S_a,bIn the image G_1ANeighborhood pixel P of middle position (a, b)_a-1,b-1、P_a-1,b、P_a-1,b+1、P_a,b+1、P_a+1,b+1、P_a+1,b、P_a+1,b-1、P_a,b-1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is set to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 8 neighborhood pixels are weak edge points and the flags of 8 neighborhood pixels are set to false, 8 neighborhood pixels are respectively placed into S and Q, and the Flag of 8 neighborhood pixels is set to true, step S33214 is executed, if the flags of all weak edge points in the neighborhood pixels are set to true, step S33214 is executed, and if the flags of all the weak edge points in the neighborhood pixels are set to true, step S33214 is executed, and if the flags of the weak edge points in the neighborhood pixels are set to true, step S33214 is executedIf there is a strong edge point, set the Connected value of the queue Q, and execute step S33214; if not 1<a<W and 1<b<L, go to step S33214;

s3323, search S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b-1、P_a-1,b-1、P_a-1,b、P_a-1,b+1、P_a,b+1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and the Flag of the edge point is equal to true, step S33214 is executed, if 5 neighborhood pixel points are weak edge points and the flags of 5 neighborhood pixel points are equal to false, 5 neighborhood pixel points are respectively placed into S and Q, the Flag of 5 neighborhood pixel points is equal to true, step S33214 is executed, if the Flag of all weak edge points in the neighborhood pixel points is equal to true, step S33214 is executed, if a strong edge point exists in the neighborhood pixel points, the Connected value of queue Q is set, and step S33214 is executed;

s4000, the detection judgment module is connected with the slave U₁、U₂、U₃、U₄Respectively receiving G by the image edge detection module₁、G₂、G₃、G₄The surface smoothness of the corresponding high-voltage cable insulating layer isIf the result meets the requirement, if all 4 results meet the requirement, G is judged₁、G₂、G₃、G₄The surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement, and the surface smoothness of the insulating layer of the high-voltage cable with the corresponding length section meets the quality requirement; if one of the 4 results is not satisfactory, G is determined₁、G₂、G₃、G₄The surface smoothness of the corresponding high-voltage cable insulating layer does not meet the requirement, and the surface smoothness of the insulating layer of the high-voltage cable with the corresponding length section does not meet the quality requirement.

A specific example will be given in the following. In one embodiment, the insulation detection method for the high-voltage cable specifically comprises the following partial or all steps.

1.1 high-voltage cable every interval L2 disposes four industrial cameras, and four industrial cameras evenly dispose in high-voltage cable same cross-sectional position's upper left side, upper right side, left side below and lower right side, and the shooting center of each industrial camera mutually becomes 90 three-dimensional space angles, catches high-voltage cable insulating layer surface image information, and L2 is 2 meters generally. The industrial camera is a CCD (Charge coupled Device) industrial line camera, wherein the parameter requirements are as follows: the video system adopts a PAL system of 768 multiplied by 576, the pixel depth of 12 bits, and a line-by-line exposure mode, the exposure time is consistent with the line period, and the pixel size of the camera is 5 μm.

1.2 each industrial camera is connected to a digital image processor. The digital image processor is an application specific integrated chip or a digital signal processor or a Field Programmable Gate Array (FPGA), and image edge detection software is burnt in the digital image processor.

And 1.3, the four digital image processors are all connected with a client, and result judgment software is installed on the client.

Secondly, the industrial camera extracts the image information of the surface of the high-voltage cable insulation layer, and the method comprises the following steps:

the four industrial cameras positioned at the same section position of the high-voltage cable shoot the high-voltage cable from respective angles in parallel to obtain images G₁、G₂、G₃、G₄And G is₁、G₂、G₃、G₄Respectively transmitted to the digital image processor U corresponding to each industrial camera₁、U₂、U₃、U₄，G₁、G₂、G₃、G₄All the sizes of (A) and (B) are W × L, W represents G₁、G₂、G₃、G₄The number of pixels in each row, L represents G₁、G₂、G₃、G₄The number of pixel points in each column, W and L are positive integers.

Third step, U₁、U₂、U₃、U₄Parallel respective detection G of image edge detection software₁、G₂、G₃、G₄Concave-convex edge of (1), determination G₁、G₂、G₃、G₄Whether the surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement or not, namely U₁Image edge detection software of (G)₁Edge of (U), U₂Image edge detection software of (G)₂Edge of (U), U₃Image edge detection software of (G)₃Edge of (U), U₄Image edge detection software of (G)₄Edge of (U), U₁、U₂、U₃、U₄Image edge detection software pair G₁、G₂、G₃、G₄The edge detection method of (2) is identical. U shape_q(q is more than or equal to 1 and less than or equal to 4) image edge detection software detection G_qThe method of the concave-convex edge comprises the following steps:

3.1 U_qthe image edge detection software adopts wiener filtering to the digital image G_qPerforming denoising operation to obtain G_qAThe method comprises the following steps:

3.1.1 U_qthe image edge detection software adopts wiener filtering to the digital image G_qPerforming denoising operation to obtain G_qA，G_qAThe size is W multiplied by L; for example, for G_qPerforming wiener filtering treatment, and adopting toolbox \ images denoising function [ G ] in Matlab (commercial mathematic software from MathWorks, USA)_qA,noise]＝wiener2(G_q,[3,3]) To the pictureImage G_qImage denoising using a 3 × 3 filter window size, where G_qAFor de-noised images, noise is image G_qThe noise power estimate of (2).

3.2 U_qImage edge detection software of (1) calculates G_qAThe method of (3) is as follows:

adopting a maximum inter-class variance method function graythresh (G) encapsulated under toolbox \ images in Matlab_qA) Determining an image G_qAT, i.e. T ═ graythresh (G)_qA)。

3.3 U_qImage edge detection software pair G_qAPerforming edge detection on the concave and convex area to determine G_qAWhether the corresponding high-voltage cable insulating layer has a real edge or not, and if so, G_qAThe surface smoothness of the corresponding high-voltage cable insulating layer does not meet the requirement, and if no real edge exists, G_qAThe surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement. The real edge is caused by two conditions, one is that a strong edge curve formed by strong edge points is the real edge, and the strong edge points are gradient values K (K) of pixel points

G_xRepresenting the gray value of the image of the pixel point detected by the transverse edge G_yThe gray value of the image of the pixel point detected by the longitudinal edge) is more than or equal to G_qAA pixel point of threshold T; secondly, the weak edge curve (composed of weak edge points, the gradient value K of the weak edge points, i.e. pixel points, is less than G_qAPixel of threshold T) if there is one or more pixels connected to the strong edge point, the weak edge curve is a true edge. The weak edge points are caused by real edges or by external interference, the weak edge points caused by the real edges are often connected with the strong edge points, and the weak edge points caused by the external interference are not connected with the strong edge points. In one embodiment, as shown in FIG. 5, a specific detection method is described as follows.

3.3.1 initialization: setting G_qAMiddle a row and b column pixel point P_a,bThe access Flag of (1) is false,P_a,bflag for access Flag of_a,bIndicating, i.e. commanding Flag_a,bDenotes P ═ false_a,bAnd if not, respectively initializing the pixel stack S and the pixel queue Q to be empty, setting a Connected flag Connected for the queue Q, and defaulting Connected to false (indicating that the pixels in Q do not form a real edge).

3.3.2 let row variable a be 1 and column variable b be 1;

3.3.2.1 if 1 is less than or equal to a<L is 1. ltoreq. b<W, execution 3.3.2.1.1; if b is W and a<L, execute 3.3.2.2; if a is L and b<W execution 3.3.2.3; if a ═ L and b ═ W, the whole G is stated_qADetected and no true edge, G_qAThe corresponding cable meets the requirement and outputs G to the client_qAAnd (4) the corresponding cable meets the conclusion of the requirement, and the fourth step is executed.

3.3.2.1.1 calculating a pixel P_a,bGradient value K of_a,b，

G_xRepresents P_a,bGray value of the image detected by the transverse edge, G_yRepresents P_a,bImage gray values detected by the longitudinal edges; for example, Sobel operator is adopted to calculate pixel point P_a,bGradient value K of_a,bThe Sobel Operator was first proposed by Irwin Sobel in 1968 at the Stanford university Artificial Intelligence laboratory as "A3X 3Isotropic Gradient Operator for Image Processing", described in detail by Pingle in the documents Pingle, K.K., "Visual Perception by a Computer, in Automatic Interpretation and Classification of Images, A.Graelli (Ed.), Academic Press, New York,1969, pp.277-284",

G_x＝[F(a+1,b-1)+2×F(a+1,b)+F(a+1,b+1)]-

[F(a-1,b-1)+2×F(a-1,b)+F(a-1,b+1)]

G_y＝[F(a-1,b-1)+2×F(a,b-1)+F(a+1,b-1)]-

[F(a-1,b+1)+2×F(a,b+1)+F(a+1,b+1)]

f (a, b) represents the gray value of the pixel point (a, b),

if a is 1, let F (a-1, b-1) be 0, F (a-1, b +1) be 0;

if b is 1, let F (a +1, b-1) be 0, F (a-1, b-1) be 0, F (a, b-1) be 0;

if a is equal to L, let F (a +1, b-1) be 0, F (a +1, b +1) be 0;

if b is W, F (a +1, b +1) is 0, F (a-1, b +1) is 0, and F (a, b +1) is 0.

In one embodiment, the pixel point P_a,bGradient value K of_a,bAdopting Prewitt operator to calculate, the method is:

K_a,b＝max[G_x,G_y]，

wherein F (a, b) represents the gray value of the pixel (a, b), and similarly,

if a is 1, let F (a-1, b-1) be 0, F (a-1, b +1) be 0;

if b is 1, let F (a +1, b-1) be 0, F (a-1, b-1) be 0, F (a, b-1) be 0;

if a is equal to L, let F (a +1, b-1) be 0, F (a +1, b +1) be 0;

if b is W, F (a +1, b +1) is 0, F (a-1, b +1) is 0, and F (a, b +1) is 0.

3.3.2.1.2 if P_a,bGradient value K of_a,bGreater than or equal to T, then P_a,bFor strong edge points, let Flag_a,bFalse, and b +1, transition 3.3.2.1; if P_a,bGradient value K of_a,bLess than T, P is determined_a,bWeak edge points, if Flag_a,bSet b to b +1, go to 3.3.2.1 if Flag_a,b3.3.2.1.3 is performed ═ false;

3.3.2.1.3 mixing P_a,bPut S as element S in stack S_a,bA 1 is to P_a,bPut Q as element Q in queue Q_a,b；

3.3.2.1.4 if S is empty and the Connected flag Connected of Q is false, sequentially fetching the pixels in Q, emptying the queue Q, making b equal to b +1, executing 3.3.2.1, and if the Connected flag Connected of Q is true, indicating that the curve formed by the pixels stored in Q is a real edge, i.e. G_qAExistence of true edge, description G_qAThe corresponding cable does not meet the requirement, pixel points in Q are sequentially taken out, the queue Q is emptied, and G is output to the client_qAThe corresponding cable does not meet the conclusion of the requirement, and the fourth step is executed; if S is not empty, taking out pixel point S from S_a,bAnd 3.3.2.1.4.1 is executed.

3.3.2.1.4.1 if a is 1 and b is 1, search for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,_b+1、P_a+1,b+1And P_a+1,bIf a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, the Flag of the pixel point is set to true, 3.3.2.1.4 is executed, if 3 neighborhood pixel points are weak edge points and the flags of 3 neighborhood pixel points are false, 3 neighborhood pixel points are respectively placed into S and Q, the Flag of 3 neighborhood pixel points is equal to true, 3.3.2.1.4 is executed, if the flags of all weak edge points in the neighborhood pixel points are equal to true, 3.3.2.1.4 is switched, if a strong edge point exists in the neighborhood pixel points, the Connected of the queue Q is set to true, and 3.3.2.1.4 is switched. If a is not satisfied and b is 1, 3.3.2.1.4.2 is performed;

3.3.2.1.4.2 if b is 1 and 1<a<L, search S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a-1,b、P_a-1,b+1、P_a,b+1、P_a+1,b+1、P_a+1,bIf a weak edge point exists in the neighborhood pixel points and the Flag of the weak edge point is equal to false, the weak edge points are respectively placedAnd entering S and Q, setting Flag of the weak edge point to true, executing 3.3.2.1.4, if 5 neighborhood pixels are weak edge points and Flag of the 5 neighborhood pixels are Flag to false, respectively putting the 5 neighborhood pixels into S and Q, setting Flag of the 5 neighborhood pixels to true, turning to 3.3.2.1.4, if Flag of all weak edge points in the neighborhood pixels to true, turning to 3.3.2.1.4, and if strong edge points exist in the neighborhood pixels, setting Connected of the queue Q to true, and turning to 3.3.2.1.4. If b is not satisfied, 1 and 1<a<L, then 3.3.2.1.4.3 is executed;

3.3.2.1.4.3 if a is 1 and 1<b<W, then search for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b-1、P_a+1,b-1、P_a+1,b、P_a+1,b+1、P_a,b+1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and Flag of the weak edge point is set to true, 3.3.2.1.4 is switched, if 5 neighborhood pixel points are weak edge points and the Flag of 5 neighborhood pixel points is equal to false, 5 neighborhood pixel points are respectively placed into S and Q, the Flag of 5 neighborhood pixel points is set to true, 3.3.2.1.4 is switched, if the Flag of all weak edge points in the neighborhood pixel points is equal to true, 3.3.2.1.4 is switched, and if a strong edge point exists in the neighborhood pixel points, the Connected value of the queue Q is set to true, and 3.3.2.1.4 is switched. If a is not 1 and 1<b<W, 3.3.2.1.4.4 is executed;

3.3.2.1.4.4 if 1<a<L is 1<b<W, then search for S_a,bIn the image G_1ANeighborhood pixel P of middle position (a, b)_a-1,b-1、P_a-1,b、P_a-1,b+1、P_a,b+1、P_a+1,b+1、P_a+1,b、P_a+1,b-1、P_a,b-1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, the Flag of the edge point is set to true, 3.3.2.1.4 is turned, if 8 neighborhood pixels are weak edge points and the Flag of 8 neighborhood pixels is equal to false, 8 neighborhood pixels are respectively placed into S and Q, the Flag of 8 neighborhood pixels is set to true, 3.3.2.1.4 is turned, and if the Flag of all weak edge points in the neighborhood pixels is equal to trueAnd turning to 3.3.2.1.4, if a strong edge point exists in a neighborhood pixel point, setting Connected of the queue Q to true, and turning to 3.3.2.1.4. If not 1<a<W and 1<b<L, also turn 3.3.2.1.4;

3.3.2.2 search for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a-1,b、P_a-1,b-1、P_a,b-1、P_a+1,b-1、P_a+1,bIf a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and Flag of the edge point is set to true, a is equal to a +1, b is equal to 0, and the process goes to 3.3.2.1.4, if 5 neighborhood pixel points are all weak edge points and the Flag of the 5 neighborhood pixel points is equal to false, 5 neighborhood pixel points are respectively placed into S and Q, and Flag of the 5 neighborhood pixel points is equal to true, a is equal to a +1, b is equal to 0, and the process goes to 3.3.2.1.4, if the Flag of all weak edge points in the neighborhood pixel points is equal to true, a is equal to a +1, b is equal to 0, and the process goes to 3.3.2.1.4, and if a strong edge point exists in the neighborhood pixel points, the processed of the queue Q is set to true, a is equal to 1, b is equal to 0, and the process goes to 3.3.2.1.4.

3.3.2.3 search for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b-1、P_a-1,b-1、P_a-1,b、P_a-1,b+1、P_a,b+1If a weak edge point exists in a neighborhood pixel point and the weak edge point Flag is equal to false, the weak edge point is respectively placed into S and Q, and Flag of the edge point is set to true, a is equal to a +1, b is equal to 0, and the process is switched to 3.3.2.1.4, if 5 neighborhood pixel points are all weak edge points and Flag of 5 neighborhood pixel points is equal to false, 5 neighborhood pixel points are respectively placed into S and Q, and Flag of 5 neighborhood pixel points is equal to true, a is equal to a +1, b is equal to 0, and the process is switched to 3.3.2.1.4, if Flag of all weak edge points in the neighborhood pixel points is equal to true, a is equal to a +1, b is equal to 0, and the process is switched to 3.3.2.1.4, if a strong edge point exists in the neighborhood pixel points, the Connected of the queue Q is set to true, a is equal to 1, b is equal to 0, and the process is switched to 3.3.2.1.4.

Fourthly, judging the result of the client by the software slave U₁、U₂、U₃、U₄Respectively receiving G by image edge detection software₁、G₂、G₃、G₄The result of whether the surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement or not is judged, and if all 4 results meet the requirement, G is judged₁、G₂、G₃、G₄The surface smoothness of the corresponding high-voltage cable insulating layer meets the requirement, and the surface smoothness of the corresponding high-voltage cable insulating layer with the length of L meets the quality requirement; if one of the 4 results is not satisfactory, G is determined₁、G₂、G₃、G₄The surface smoothness of the corresponding high-voltage cable insulating layer does not meet the requirement, and the surface smoothness of the corresponding high-voltage cable insulating layer with the length of L does not meet the quality requirement.

Therefore, the insulation detection of the high-voltage cable is completed by detecting the surface smoothness of the cross-linked polyethylene insulating layer, the automatic detection is realized, the human resources are saved, the potential accident risk caused by manual detection is avoided, the quality of the detection effect is stable, the detection efficiency is higher, and the detection effect is more accurate.

In one embodiment, a high voltage cable maintenance method includes the high voltage cable insulation detection method of any one of the embodiments, and the high voltage cable maintenance method further includes the steps of: and when the surface smoothness of the insulating layer of the high-voltage cable is judged not to meet the quality requirement, maintaining the cable. Further, in one embodiment, the cables are maintained differentially according to the concave-convex edges and the detection results thereof. In one embodiment, as shown in fig. 6, a high voltage cable maintenance method includes the steps of: s1000, a detection platform is set up, the detection platform comprises digital image processing equipment and at least one image capturing group, each image capturing group comprises four image acquiring instruments, the four image acquiring instruments are uniformly arranged at four corners of the same section of the high-voltage cable, photographing centers of the four image acquiring instruments form a rectangle and are respectively positioned at the four corners of the rectangle, the digital image processing equipment is respectively connected with each image acquiring instrument, and the digital image processing equipment is also connected with a detection judgment module; s2000, extracting image information of the surface of the high-voltage cable insulation layer through the detection platform; for each image capturing group, the four image acquiring instruments parallelly acquire images of the high-voltage cable from respective angles at the same time, respectively obtain surface images of the insulating layer and transmit the surface images to the digital image processing equipment; s3000, the digital image processing equipment respectively detects the concave-convex edges of the surface images of the insulating layers, determines whether the surface smoothness of the insulating layer of the high-voltage cable corresponding to the surface images of the insulating layers meets the requirements or not, obtains a detection result and transmits the detection result to the detection judgment module; s4000, when any one of the detection results is negative, the detection judgment module judges that the surface smoothness of the insulating layer of the high-voltage cable does not meet the quality requirement; and S5000, when the surface smoothness of the insulating layer of the high-voltage cable is judged not to meet the quality requirement, maintaining the cable. The rest of the examples are analogized. According to the high-voltage cable maintenance method, whether the flatness of the surface of the high-voltage cable insulating layer corresponding to the surface images of the insulating layers meets the requirements or not is detected through designing the detection platform, on one hand, automatic detection is achieved, human resources are saved, on the other hand, potential accident risks caused by manual detection are avoided, on the other hand, image acquisition on the high-voltage cable is facilitated rapidly and efficiently, the detection effect quality is stable, the detection efficiency is high, the detection cross section position is designed in a rectangular mode, the image acquired by each image acquisition instrument can reflect the surface of the high-voltage cable insulating layer more accurately, and accordingly, whether the flatness of the surface of the high-voltage cable insulating layer meets the requirements or not is favorably judged subsequently, the detection effect is more accurate, cable maintenance can be carried out timely and effectively.

In addition, other embodiments of the present application include a high-voltage cable insulation detection method and a high-voltage cable maintenance method, which are implemented by combining technical features of the above embodiments.

The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.

The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the claims. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.

Claims

1. A high-voltage cable insulation detection method is characterized by comprising the following steps;

s2000, extracting image information of the surface of the high-voltage cable insulation layer through the detection platform; for each image capturing group, four industrial cameras are used for simultaneously acquiring images of the high-voltage cable in parallel to respectively obtain an image G of the surface of the insulating layer₁、G₂、G₃、G₄And G is₁、G₂、G₃、G₄Respectively transmitted to the digital image processor U corresponding to each industrial camera₁、U₂、U₃、U₄；G₁、G₂、G₃、G₄All the sizes of (A) and (B) are W × L, W represents G₁、G₂、G₃、G₄The number of pixels in each row, L represents G₁、G₂、G₃、G₄The number of pixels in each row, W and L are positiveAn integer number;

s3310, set G_qAMiddle a row and b column pixel point P_a,bAccess Flag of (1) is false, P_a,bFlag for access Flag of_a,bIndicates, let Flag_a,bRespectively initializing a pixel stack S and a pixel queue Q to be empty, setting a Connected flag Connected for the queue Q, and defaulting Connected to be false;

s3320, let row variable a be 1 and column variable b be 1;

s3321, if 1 is less than or equal to a<L is 1. ltoreq. b<W, executing the step S33211; if b is W and a<L, executing the step S3322; if a is L and b<W performs step S3323; if a is L and b is W, then the whole G_qAAfter the detection is finished and no real edge exists, the detection result is G_qAThe surface smoothness of the corresponding high-voltage cable insulating layer is in accordance withThe request is transmitted to the detection judgment module and the step S4000 is executed;

s33211, calculating a pixel P_a,bGradient value K of_a,b，

s332141, if a is 1 and b is 1, searches for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b+1、P_a+1,b+1And P_a+1,bIf a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is false, the weak edge point is respectively placed into S and Q, and the Flag of the pixel point is set to true, then step S33214 is executed, and if so, the pixel point is set to false3 neighborhood pixel points are weak edge points, and Flag of the 3 neighborhood pixel points is false, the 3 neighborhood pixel points are respectively put into S and Q, Flag of the 3 neighborhood pixel points is set to be true, step S33214 is executed, if Flag of all weak edge points in the neighborhood pixel points is set to be true, step S33214 is executed, if strong edge points exist in the neighborhood pixel points, Connected of queue Q is set to be true, and step S33214 is executed; if a is not 1 and b is 1, performing step S332142;

s332143, if a is 1 and 1<b<W, then search for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a,b-1、P_a+1,b-1、P_a+1,b、P_a+1,b+1、P_a,b+1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is set to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 5 neighborhood pixels are weak edge points and the Flag of the 5 neighborhood pixels is set to false, the 5 neighborhood pixels are respectively placed into S and Q and the Flag of the 5 neighborhood pixels is set to true, step S33214 is executed, if the Flag of all weak edge points in the neighborhood pixels is set to true, step S33214 is executed, and if a strong edge point exists in the neighborhood pixels, the Connected of the queue Q is set to truetrue, go to step S33214; if a is not 1 and 1<b<W, go to step S332144;

s332144, if 1<a<L is 1<b<W, then search for S_a,bIn the image G_qANeighborhood pixel P of middle position (a, b)_a-1,b-1、P_a-1,b、P_a-1,b+1、P_a,b+1、P_a+1,b+1、P_a+1,b、P_a+1,b-1、P_a,b-1If a weak edge point exists in a neighborhood pixel point and the Flag of the weak edge point is equal to false, the weak edge point is respectively placed into S and Q, and the Flag of the weak edge point is set to true, step S33214 is executed, if 8 neighborhood pixels are weak edge points and the flags of 8 neighborhood pixels are equal to false, the 8 neighborhood pixels are respectively placed into S and Q and the flags of 8 neighborhood pixels are set to true, step S33214 is executed, if the flags of all weak edge points in the neighborhood pixels are equal to true, step S33214 is executed, if a strong edge point exists in the neighborhood pixels, the Connected value of queue Q is set to true, and step S33214 is executed; if not 1<a<W and 1<b<L, go to step S33214;

2. The method for detecting the insulation of the high-voltage cable according to claim 1, wherein a plane in which the rectangle formed by the shooting centers of the four industrial cameras of each image capturing group is located is parallel to a plane in which a rectangle formed by the shooting centers of the four industrial cameras of the other image capturing group is located.

3. The method for detecting the insulation of the high-voltage cable according to claim 2, wherein the distance between two adjacent image capturing groups is the shooting distance of the industrial camera.

4. The method of claim 1, wherein the rectangle is a square.

5. The method for detecting the insulation of the high-voltage cable according to claim 1, wherein the concave-convex edges of the surface image of each insulation layer are respectively detected in a breadth-first traversal mode.

6. The insulation detection method for the high-voltage cable according to claim 1, wherein the detection platform further comprises a client and the detection judgment module is disposed in the client.

7. The method for detecting insulation of a high-voltage cable according to claim 6, wherein the client comprises a mobile terminal, a PC or a tablet.

8. The method for detecting insulation of a high-voltage cable according to any one of claims 1 to 7, wherein before the image information of the surface of the insulation layer of the high-voltage cable is extracted by the detection platform in step S2000, the method for detecting insulation of a high-voltage cable further comprises the steps of: moving the detection platform; the distance for moving the detection platform is L1+ L2, wherein L1 is the length of the detection platform, and L2 is the shooting distance of the image acquisition instrument.

9. The method of claim 8, wherein the direction of movement of the testing platform is parallel to the high voltage cable.

10. A high voltage cable maintenance method comprising the high voltage cable insulation detection method of any one of claims 1 to 9, further comprising the steps of: and when the surface smoothness of the insulating layer of the high-voltage cable is judged not to meet the quality requirement, maintaining the cable.