CN110009603A - High-voltage cable insulating detection method and high-tension cable maintaining method - Google Patents
High-voltage cable insulating detection method and high-tension cable maintaining method Download PDFInfo
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- CN110009603A CN110009603A CN201910192454.6A CN201910192454A CN110009603A CN 110009603 A CN110009603 A CN 110009603A CN 201910192454 A CN201910192454 A CN 201910192454A CN 110009603 A CN110009603 A CN 110009603A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1218—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing using optical methods; using charged particle, e.g. electron, beams or X-rays
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/12—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing
- G01R31/1227—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials
- G01R31/1263—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation
- G01R31/1272—Testing dielectric strength or breakdown voltage ; Testing or monitoring effectiveness or level of insulation, e.g. of a cable or of an apparatus, for example using partial discharge measurements; Electrostatic testing of components, parts or materials of solid or fluid materials, e.g. insulation films, bulk material; of semiconductors or LV electronic components or parts; of cable, line or wire insulation of cable, line or wire insulation, e.g. using partial discharge measurements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
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- G06T7/10—Segmentation; Edge detection
- G06T7/13—Edge detection
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Abstract
This application involves high-voltage cable insulating detection method and high-tension cable maintaining methods, the following steps are included: four images obtain, instrument is deployed in the same sectional position of high-tension cable to insulation detecting method and four shootings are centrally formed a rectangle, carries out image acquisition simultaneously from respective angle parallel；The concave-convex edge of each surface of insulating layer image is detected respectively, determine whether high-voltage cable insulating layer surface planarization corresponding to each surface of insulating layer image meets the requirements, when it is no that each testing result is any, determine that the profile pattern of the insulating layer of high-tension cable is not up to quality requirement.Realize Automated inspection, avoid latent defect risk caused by artificial detection, detection effect quality is stable and detection efficiency is higher, and the detection sectional plane position of rectangular design, each image, which obtains image acquired in instrument, can more accurately reflect high-voltage cable insulating layer surface, to be conducive to whether subsequent judgement high-voltage cable insulating layer surface planarization meets the requirements, so that detection effect is more accurate.
Description
Technical field
This application involves high-voltage cable insulating detection fields, more particularly to high-voltage cable insulating detection method and high-voltage electricity
Cable maintaining method.
Background technique
High-voltage cable insulating layer shows that out-of-flatness will cause electric field and unevenly cause safety accident, thereby, it is ensured that cable matter
It measures and plays a key effect to the conveying of stablizing of electric power.But due to cable insulation the smoothness of layer surface and planarization detection difficulty compared with
Greatly, it is unfavorable for digital image acquisition, therefore currently relies on desk checking, there has been no mature application technology, but by artificial inspection
It surveys, more manpower can be expended, detection effect quality is not sufficiently stable and detection efficiency is low.
Summary of the invention
Based on this, it is necessary to provide a kind of high-voltage cable insulating detection method and high-tension cable maintaining method.
A kind of high-voltage cable insulating detection method comprising following steps:
S1000, builds detection platform, and the detection platform includes digital image processing apparatus and an at least image capture
Group, each described image capture group include that four images obtain instrument, and four described images obtain instrument for being uniformly deployed in
The shooting that the quadrangle of the same sectional position of high-tension cable and four described images obtain instrument is centrally formed a rectangle and respectively position
In the quadrangle of the rectangle, the digital image processing apparatus is separately connected each described image and obtains instrument, the digital picture
Processing equipment is also connected with detection judgment module；
S2000 extracts high-voltage cable insulating layer surface image information by the detection platform；Wherein, for each institute
Image acquisition group is stated, four described images obtain instrument and carry out image acquisition to high-tension cable simultaneously from respective angle parallel, point
Surface of insulating layer image is not obtained and is transmitted to the digital image processing apparatus；
S3000, the digital image processing apparatus detect the concave-convex edge of each surface of insulating layer image respectively, determine each exhausted
Whether high-voltage cable insulating layer surface planarization corresponding to edge layer surface image meets the requirements, and obtains testing result and is transferred to
The detection judgment module；
S4000, the detection judgment module determine the insulating layer of high-tension cable when it is no that each testing result is any
Profile pattern be not up to quality requirement.
Above-mentioned high-voltage cable insulating detection method, by corresponding to design detection platform and each surface of insulating layer image of detection
High-voltage cable insulating layer surface planarization whether meet the requirements, on the one hand realize Automated inspection, save human resources, separately
On the one hand latent defect risk caused by artificial detection is avoided, another further aspect is conducive to quickly and efficiently carry out high-tension cable
Image obtains, and detection effect quality is stable and detection efficiency is higher, and the detection sectional plane position of rectangular design, and each image obtains
Image acquired in instrument can more accurately reflect high-voltage cable insulating layer surface, to be conducive to subsequent judgement high-tension cable
Whether surface of insulating layer planarization meets the requirements, so that detection effect is more accurate.
The detection platform includes at least two described image capture groups, described image capture in one of the embodiments,
Plane where the rectangle that the shooting that four described images of group obtain instrument is centrally formed, with other image capture groups
The shooting center that four images obtain instrument is formed by the plane parallel where rectangle.
The rectangle is square in one of the embodiments,.
The spacing of adjacent two described images capture group is the shooting that described image obtains instrument in one of the embodiments,
Distance；It is 2 meters that described image, which obtains the shooting distance of instrument, in one of the embodiments,.
The detection platform includes two described image capture groups in one of the embodiments,.
The digital image processing apparatus includes several Digital Image Processors, Mei Yisuo in one of the embodiments,
It states Digital Image Processor and is separately connected described image acquisition instrument correspondingly, each Digital Image Processor also connects
Connect the detection judgment module.
The detection platform further includes client in one of the embodiments, and the detection judgment module is set to institute
It states in client.
The high-voltage cable insulating detection method specifically includes following steps in one of the embodiments,；
S1100, builds detection platform, and the detection platform includes multiple images capture group, each described image capture group
Including four industrial cameras, and four industrial cameras be uniformly deployed in the same sectional position of high-tension cable quadrangle and four
The shooting of the industrial camera is centrally formed a rectangle and is located at the quadrangle of the rectangle；
S1200, each industrial camera is connected with a Digital Image Processor respectively, in the Digital Image Processor
Equipped with Image Edge-Detection module；
S1300, each Digital Image Processor are separately connected detection judgment module；
S2000 extracts high-voltage cable insulating layer surface image information by the detection platform；Wherein, for each institute
Image acquisition group is stated, four industrial cameras are parallel to carry out image acquisition to high-tension cable simultaneously, respectively obtains surface of insulating layer figure
As G1、G2、G3、G4, and by G1、G2、G3、G4It is respectively transmitted to the corresponding Digital Image Processor U of each industrial camera1、U2、U3、U4；
G1、G2、G3、G4Size be W × L, W indicates G1、G2、G3、G4Every row pixel number, L indicate G1、G2、G3、G4Each column pixel
Point number, W and L are positive integer；
S3000, U1、U2、U3、U4Image Edge-Detection modular concurrent detect G respectively1、G2、G3、G4Concave-convex edge, sentence
Determine G1、G2、G3、G4Whether corresponding high-voltage cable insulating layer surface planarization meets the requirements, UqImage Edge-Detection software
Detect GqThe step of concave-convex edge, is as follows, wherein 1≤q≤4；
S3100, UqImage Edge-Detection software using Wiener filtering to digital picture GqIt carries out denoising operation and obtains GqA,
GqASize is W × L；
S3200, UqImage Edge-Detection software calculate GqAImage threshold T；
S3300, UqImage Edge-Detection software to GqAIn relief region carry out edge detection, determine GqACorresponding
High-voltage cable insulating layer whether there is true edge, if it exists true edge, then GqACorresponding high-voltage cable insulating layer surface
Planarization is undesirable, if it does not exist true edge, then GqACorresponding high-voltage cable insulating layer surface planarization conforms to
It asks；Carry out edge detection the following steps are included:
G is arranged in S3310qAIn a row b column pixel Pa,bAccess flag Flag be false, Pa,bAccess flag
Flag Flaga,bIt indicates, even Flaga,b=false, initialized pixel point stack S and pixel queue Q are sky respectively, are team
Q setting connection mark Connected is arranged, and defaults Connected=false；
S3320 enables row variable a=1, column variable b=1；
S3321 executes step S33211 if 1≤a < L and 1≤b < W；If b=W and a < L, step S3322 is executed；If a=
L and b < W execution step S3323；If a=L and b=W, entire GqAIt has detected and has finished and be not present true edge, detected
It as a result is GqACorresponding high-voltage cable insulating layer surface planarization meets the requirements, and is transferred to the detection judgment module and execution
Step S4000；
S33211 calculates pixel Pa,bGradient value Ka,b,GxIndicate Pa,bThrough transverse edge
The gray value of image of detection, GyIndicate Pa,bThe gray value of image detected through longitudinal edge；
S33212, if Pa,bGradient value Ka,bMore than or equal to T, then Pa,bFor strong edge point, Flag is enableda,b=false, and b
=b+1 executes step S3321；If Pa,bGradient value Ka,bLess than T, P is determineda,bFor weak marginal point, if Flaga,b=true, if
B=b+1 is set, step S3321 is executed, if Flaga,b=false executes step S33213；
S33213, by Pa,bIt is put into S, as the element S in Sa,b, by Pa,bIt is put into Q, as the element Q in Qa,b；
S33214 successively takes out pixel in Q, empties team if S is empty and Q connection mark Connected=false
Q is arranged, b=b+1 is enabled, step S3321 is executed, if the pixel institute stored in connection the mark Connected=true, Q of Q
Composition curve is true edge, obtains GqAThere are true edges, then obtaining testing result is GqACorresponding high-voltage cable insulating
Layer surface planarization is undesirable, successively takes out the pixel in Q, empties queue Q, will test result and be transferred to the detection
Judgment module and execution step S4000；If S is not empty, the taking-up pixel S from Sa,b, execute step S332141；
S332141, if a=1 and b=1, search for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b+1、
Pa+1,b+1And Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then by the weak edge
Point is respectively put into S and Q and the Flag=true of the pixel is arranged, and step S33214 is executed, if 3 neighborhood territory pixel points are weak
The Flag of marginal point and 3 neighborhood territory pixel points is false, then 3 neighborhood territory pixel points is respectively put into S and Q and 3 neighbours are arranged
The Flag=true of domain pixel, execute step S33214, if in neighborhood territory pixel point all weak marginal points Flag=true, hold
The Connected=true of queue Q is arranged if there are strong edge points in neighborhood territory pixel point in row step S33214, executes step
S33214；If being unsatisfactory for a=1 and b=1, S332142 is thened follow the steps；
S332142 searches for S if b=1 and 1 < a < La,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、
Pa-1,b+1、Pa,b+1、Pa+1,b+1、Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then
The weak marginal point is respectively put into S and Q and the Flag=true of the weak marginal point is set, step S33214 is executed, if 5 neighborhoods
Pixel is that the Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then distinguishes 5 neighborhood territory pixel points
It is put into S and Q and the Flag=true of 5 neighborhood territory pixel points is set, step S33214 is executed, if all weak sides in neighborhood territory pixel point
The Flag=true of edge point executes step S33214, if being arranged queue Q's there are strong edge point in neighborhood territory pixel point
Connected=true executes step S33214；If being unsatisfactory for b=1 and 1 < a < L, S332143 is thened follow the steps；
S332143, if a=1 and 1 <b < W, search for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b-1、
Pa+1,b-1、Pa+1,b、Pa+1,b+1、Pa,b+1If there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then
The weak marginal point is respectively put into S and Q and the Flag=true of the marginal point is set, step S33214 is executed, if 5 neighborhood pictures
Vegetarian refreshments is that the Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then puts 5 neighborhood territory pixel points respectively
Enter S and Q and the Flag=true of 5 neighborhood territory pixel points is set, step S33214 is executed, if all weak edges in neighborhood territory pixel point
The Flag=true of point executes step S33214 if there are strong edge points in neighborhood territory pixel point and is arranged queue Q's
Connected=true executes step S33214；If being unsatisfactory for a=1 and 1 <b < W, S332144 is thened follow the steps；
S332144, if 1 < a < L and 1 <b < W, search for Sa,bIn image G1AThe neighborhood territory pixel point of middle position (a, b)
Pa-1,b-1、Pa-1,b、Pa-1,b+1、Pa,b+1、Pa+1,b+1、Pa+1,b、Pa+1,b-1、Pa,b-1If there are weak marginal points for neighborhood territory pixel point, and should
The weak marginal point is then respectively put into S and Q and the Flag=true of the marginal point is arranged, held by the Flag=false of weak marginal point
Row step S33214, if the Flag that 8 neighborhood territory pixel points are weak marginal point and 8 neighborhood territory pixel points is Flag=false,
8 neighborhood territory pixel points are then respectively put into S and Q and the Flag=true of 8 neighborhood territory pixel points is set, execute step S33214,
If the Flag=true of all weak marginal points in neighborhood territory pixel point, step S33214 is executed, if there are strong sides in neighborhood territory pixel point
The Connected=true of queue Q is then arranged in edge point, executes step S33214；If being unsatisfactory for 1 < a < W and 1 <b < L, step is executed
Rapid S33214；
S3322 searches for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、Pa-1,b-1、Pa,b-1、Pa+1,b-1、
Pa+1,bIf there are weak marginal point and the Flag=false of the weak marginal point for neighborhood territory pixel point, which is respectively put into
S and Q and the Flag=true that the marginal point is arranged enable a=a+1, b=0, step S33214 are executed, if 5 neighborhood territory pixel points are equal
Flag for weak marginal point and 5 neighborhood territory pixel points is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q
And the Flag=true of 5 neighborhood territory pixel points is set, a=a+1, b=0 are enabled, step S33214 is executed, if institute in neighborhood territory pixel point
There is the Flag=true of weak marginal point, enable a=a+1, b=0, step S33214 is executed, if there are strong edges in neighborhood territory pixel point
The Connected=true of queue Q is then arranged in point, enables a=a+1, b=0, executes step S33214；
S3323 searches for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b-1、Pa-1,b-1、Pa-1,b、Pa-1,b+1、
Pa,b+1If the weak marginal point is respectively put into S there are weak marginal point and the weak marginal point Flag=false by neighborhood territory pixel point
With Q and the Flag=true of the marginal point is set, step S33214 is executed, if 5 neighborhood territory pixel points are weak marginal point and 5
The Flag of neighborhood territory pixel point is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q and 5 neighborhood pictures are arranged
The Flag=true of vegetarian refreshments, execute step S33214, if in neighborhood territory pixel point all weak marginal points Flag=true, execute step
The Connected=true of queue Q is arranged if there are strong edge points in neighborhood territory pixel point in rapid S33214, executes step
S33214；
S4000, the detection judgment module is from U1、U2、U3、U4Image Edge-Detection module receive G respectively1、G2、G3、G4
Whether corresponding high-voltage cable insulating layer surface planarization is satisfactory as a result, if 4 results meet the requirements entirely, sentences
Determine G1、G2、G3、G4The profile pattern of corresponding high-voltage cable insulating layer meets the requirements, the high-tension cable of corresponding length section
The profile pattern of insulating layer reach quality requirement；If have in 4 results one it is undesirable, determine G1、G2、G3、G4
The profile pattern of corresponding high-voltage cable insulating layer is undesirable, the insulating layer of the high-tension cable of corresponding length section
Profile pattern is not up to quality requirement.
In one of the embodiments, in step S2000, high-voltage cable insulating layer surface is extracted by the detection platform
Before image information, the high-voltage cable insulating detection method further comprises the steps of: the mobile detection platform；The mobile detection
The distance of platform is L1+L2, wherein L1 is the length of the detection platform, and L2 is the shooting distance that described image obtains instrument.
A kind of high-tension cable maintaining method comprising any one high-voltage cable insulating detection method, the high-voltage electricity
When the profile pattern that cable maintaining method further comprises the steps of: the insulating layer of judgement high-tension cable is not up to quality requirement, to described
Cable is safeguarded.
Above-mentioned high-tension cable maintaining method passes through height corresponding to design detection platform and each surface of insulating layer image of detection
Whether voltage cable surface of insulating layer planarization meets the requirements, and on the one hand realizes Automated inspection, saves human resources, another party
Face avoids latent defect risk caused by artificial detection, and another further aspect is conducive to quickly and efficiently carry out image to high-tension cable
It obtains, detection effect quality is stable and detection efficiency is higher, and the detection sectional plane position of rectangular design, and each image obtains instrument
Acquired image can more accurately reflect high-voltage cable insulating layer surface, to be conducive to subsequent judgement high-voltage cable insulating
Whether layer surface planarization meets the requirements, so that detection effect is more accurate, and then can timely and effectively carry out cable maintenance, keeps away
Exempt from the generation of serious accident.
Detailed description of the invention
Fig. 1 is the flow diagram of one embodiment of the application high-voltage cable insulating detection method.
Fig. 2 is that four images of an image capture group of one embodiment of the application high-voltage cable insulating detection method obtain instrument
Device is formed by the positional diagram of square with high-tension cable.
Fig. 3 is that four images of an image capture group of another embodiment of the application high-voltage cable insulating detection method obtain
Instrument is formed by the positional diagram of square with high-tension cable.
Fig. 4 is that four images of an image capture group of another embodiment of the application high-voltage cable insulating detection method obtain
Instrument is formed by the positional diagram of square with high-tension cable.
Fig. 5 is the flow diagram of another embodiment of the application high-voltage cable insulating detection method.
Fig. 6 is the flow diagram of one embodiment of the application high-tension cable maintaining method.
Specific embodiment
In order to make the above objects, features, and advantages of the present application more apparent, with reference to the accompanying drawing to the application
Specific embodiment be described in detail.Many details are explained in the following description in order to fully understand this Shen
Please.But the application can be implemented with being much different from other way described herein, those skilled in the art can be not
Similar improvement is done in the case where violating the application intension, therefore the application is not limited by the specific embodiments disclosed below.
It should be noted that it can be directly another when element is referred to as " being fixed on " or " being set to " another element
On one element or there may also be elements placed in the middle.When an element is considered as " connection " another element, it can be with
It is directly to another element or may be simultaneously present centering elements.Term as used herein " vertically ", " level
", "left", "right" and similar statement for illustrative purposes only, be not meant to be the only embodiment.
Unless otherwise defined, all technical and scientific terms used herein and the technical field for belonging to the application
The normally understood meaning of technical staff is identical.The term used in the description of the present application is intended merely to description tool herein
The purpose of the embodiment of body, it is not intended that in limitation the application.Term " and or " used herein includes one or more
Any and all combinations of relevant listed item.
As shown in Figure 1, a kind of high-voltage cable insulating detection method comprising following steps: S1000 builds detection platform,
The detection platform includes digital image processing apparatus and an at least image capture group, and each described image capture group includes four
Image obtains instrument, and four described images obtain the quadrangle and four that instrument is used to uniformly be deployed in the same sectional position of high-tension cable
The shooting that platform described image obtains instrument is centrally formed a rectangle and is located at the quadrangle of the rectangle, at the digital picture
Reason equipment is separately connected each described image and obtains instrument, and the digital image processing apparatus is also connected with detection judgment module；
S2000 extracts high-voltage cable insulating layer surface image information by the detection platform；Wherein, each described image is obtained
Group is taken, four described images obtain instrument and carry out image acquisition to high-tension cable simultaneously from respective angle parallel, respectively obtain absolutely
Edge layer surface image and it is transmitted to the digital image processing apparatus；S3000, the digital image processing apparatus detect respectively respectively
The concave-convex edge of surface of insulating layer image determines high-voltage cable insulating layer surface planarization corresponding to each surface of insulating layer image
Whether meet the requirements, obtain testing result and is transferred to the detection judgment module；S4000, the detection judgment module is each
The testing result it is any for it is no when, determine that the profile pattern of the insulating layer of high-tension cable is not up to quality requirement.Above-mentioned height
Voltage cable insulation detecting method passes through high-voltage cable insulating corresponding to design detection platform and each surface of insulating layer image of detection
Whether layer surface planarization meets the requirements, and on the one hand realizes Automated inspection, saves human resources, on the other hand avoids people
Latent defect risk caused by work detects, another further aspect are conducive to quickly and efficiently carry out image acquisition, detection to high-tension cable
Effect quality is stable and detection efficiency is higher, and the detection sectional plane position of rectangular design, and each image obtains acquired in instrument
Image can more accurately reflect high-voltage cable insulating layer surface, so that it is flat to be conducive to subsequent judgement high-voltage cable insulating layer surface
Whether whole property meets the requirements, so that detection effect is more accurate.
In the application one embodiment, a kind of high-voltage cable insulating detection method comprising the part of following embodiment
Step or Overall Steps；That is, the high-voltage cable insulating detection method includes that some technical characteristics below or whole technologies are special
Sign.
S1000 in one of the embodiments, builds detection platform, and the detection platform includes that Digital Image Processing is set
A standby and at least image capture group, each described image capture group include that four images obtain instrument, and four described images obtain
Instrument is used to uniformly be deployed in the quadrangle of the same sectional position of high-tension cable, and four described images obtain the shooting center of instrument
It forms a rectangle and is located at the quadrangle of the rectangle, the digital image processing apparatus is separately connected each described image and obtains
Instrument, the digital image processing apparatus are also connected with detection judgment module；That is the shooting center that four described images obtain instrument
Positioned at the quadrangle of rectangle.The rectangle is square in one of the embodiments, i.e. the bat that four described images obtain instrument
Take the photograph the quadrangle that center is located at square.As shown in Fig. 2, each described image capture group includes four in one of the embodiments,
Platform image obtains instrument 100, and four described images obtain instrument 100 and are uniformly deployed in the same sectional position of high-tension cable 200
The shooting center 110 that quadrangle and four described images obtain instrument forms a square and is located at the four of the square
Angle, i.e. four described images obtain the shooting center of instrument or are located at 200 same sections of high-tension cable for the center for position of finding a view
The quadrangle of face position and form a square 300.As shown in figure 3, a described image capture group in one of the embodiments,
The shooting center 110 that four images obtain instrument (one of them is blocked by high-tension cable 200) is located at 200 same sections of high-tension cable
The quadrangle of face position and a square is formed, the shooting direction at the shooting center 110 that four images obtain instrument 100 converges at height
At the same position of voltage cable 200, the spacing of adjacent two described images capture group is L2.As shown in figure 4, an implementation wherein
In example, the shooting center 110 that four images of a described image capture group obtain instrument is located at the same section of high-tension cable 200 position
The quadrangle and one square of formation, the shooting direction at the shooting center 110 that four images obtain instrument 100 set converge at high-voltage electricity
At the same position of cable 200, the spacing of adjacent two described images capture group is L2.The detection in one of the embodiments,
Platform includes at least two described image capture groups, and four described images of described image capture group obtain heart-shaped in the shooting of instrument
At the rectangle where plane, the shooting center for obtaining instrument with four images of other image capture groups is formed by square
Plane parallel where shape；Four images of i.e. each image capture group obtain instrument and are arranged in a one-to-one correspondence respectively, spatially
A cuboid is integrally formed；That is, the shooting center of four described images acquisition instrument of each described image capture group is uniform
It is deployed in the section of the same sectional position of high-tension cable, obtains instrument with four described images of other described image capture groups
Shooting center be uniformly deployed in the same sectional position of high-tension cable correspondence section it is parallel.In one of the embodiments,
The spacing of adjacent two described images capture group is 2 meters, i.e., the spacing in two parallel sections is 2 meters, that is, L2 is 2 meters, can
With understanding, the length of L2 is depending on the precision that image obtains instrument such as industrial camera or camera etc..Wherein one
In a embodiment, described image obtains instrument and is or including industrial camera.Further, each in one of the embodiments,
Four described images of described image capture group obtain instrument and form a square.The detection in one of the embodiments,
Platform includes two described image capture groups.The spacing of two described image capture groups is described image in one of the embodiments,
Obtain the shooting distance of instrument；It is 2 meters that described image, which obtains the shooting distance of instrument, in one of the embodiments,.Wherein
In one embodiment, the digital image processing apparatus includes several Digital Image Processors, each Digital Image Processing
Device is separately connected a described image correspondingly and obtains instrument, and each Digital Image Processor is also connected with the detection judgement
Module.Also that is, how many platform image, which obtains instrument, is arranged same amount of Digital Image Processor with regard to Corresponding matching.Wherein one
In a embodiment, the detection platform further includes client and the detection judgment module is set in the client.Into one
Step ground, the client includes mobile terminal, PC or plate etc. in one of the embodiments,.Such design, by figure
As obtaining instrument such as industrial camera and surface of insulating layer planarization detection algorithm hereafter, crosslinked polyetylene insulated layer table is solved
The big problem of bright planarization detection difficulty, cooperates the detection sectional plane position of rectangular design, and it is exhausted to be conducive to subsequent judgement high-tension cable
Whether edge layer profile pattern meets the requirements, so that detection effect is more accurate.
S2000 in one of the embodiments, extracts high-voltage cable insulating layer surface image letter by the detection platform
Breath；Wherein, for each described image acquisition group, four described images obtain instrument parallel from respective angle simultaneously to high-voltage electricity
Cable carries out image acquisition, respectively obtains surface of insulating layer image and is transmitted to the digital image processing apparatus；One wherein
It is described before extracting high-voltage cable insulating layer surface image information by the detection platform in step S2000 in embodiment
High-voltage cable insulating detection method further comprises the steps of: the mobile detection platform；Wherein, the distance of the mobile detection platform is
L1+L2, wherein L1 is the length of the detection platform, shooting distance that is, adjacent two institute of the L2 for described image acquisition instrument
State the spacing of image capture group.Further, the detection platform is translated in one of the embodiments, i.e., the described detection is flat
The moving direction of platform is parallel to high-tension cable.The length of the detection platform is positioned at both ends in one of the embodiments,
Described image capture group spacing, i.e., the length of the described detection platform is the overall length of the image capture group of the detection platform
Degree.Such design by translating the detection platform, can constantly detect the surfacing of the insulating layer of high-tension cable
Property, to really realize the automatic detection of long cable.Further, in one of the embodiments, for each figure
As capture group, positioned at the same sectional position of high-tension cable four industrial cameras parallel from respective angle simultaneously to high-tension cable into
Row is taken pictures, and respectively obtains four images, four images are respectively transmitted to the corresponding Digital Image Processor of each industrial camera.Figure
Picture as surface of insulating layer image.
S3000 in one of the embodiments, the digital image processing apparatus detect each surface of insulating layer image respectively
Concave-convex edge, determine whether high-voltage cable insulating layer surface planarization corresponding to each surface of insulating layer image meets the requirements,
It obtains testing result and is transferred to the detection judgment module；Further, in one of the embodiments, in detection image
Before, image is denoised first, improves processing speed, using image threshold, strong edge point/weak marginal point of image is carried out
Judgement is conducive to the accuracy for improving marginal point judgement.Further, in one of the embodiments, at the digital picture
Reason equipment detects the concave-convex edge of each surface of insulating layer image respectively by the way of breadth first traversal.Such design, has
Conducive to showing that the syntople between strong edge point improves detection efficiency and edge detection conducive to the judgement of boundary curve
Accuracy.The Image Edge-Detection module of each Digital Image Processor, the module can be with softwares in one of the embodiments,
Changing is Image Edge-Detection software, and the concave-convex edge of parallel detection image respectively determines high-tension cable corresponding to each image
Whether surface of insulating layer planarization meets the requirements.
S4000 in one of the embodiments, the detection judgment module each testing result it is any for it is no when,
Determine that the profile pattern of the insulating layer of high-tension cable is not up to quality requirement.Matching step S3000, using image processor pair
After image is handled, then the mode that each image result is determined is integrated, reduces image processor and handle every picture
The workload of information improves the processing speed of image processor.It is understood that if thering is one not to be inconsistent in each testing result
It closes and requires, then determine that the profile pattern of the insulating layer of high-tension cable is not up to quality requirement.
Such design, the detection platform built can obtain instrument by four images with the side of the multiple conjunction of an angle of 90 degrees
Formula realizes that 360 degree carry out information capture to high-voltage cable insulating layer surface image without dead angle and obtain instrument especially by image
The image processor of industrial camera connection, detects surface of insulating layer planarization in image；To realize automation inspection
It tests, save human resources and avoids latent defect risk caused by artificial detection；Be conducive to quickly and efficiently to high-tension cable
Image acquisition is carried out, detection effect quality is stable and detection efficiency is higher, and the detection sectional plane position of rectangular design, each image
High-voltage cable insulating layer surface can more accurately be reflected by obtaining image acquired in instrument, to be conducive to subsequent judgement high pressure
Whether cable insulation profile pattern meets the requirements, so that detection effect is more accurate.
Provide a specific embodiment again below.The high-voltage cable insulating detection side in one of the embodiments,
Method specifically includes following part or all of step.
S1100, builds detection platform, and the detection platform includes multiple images capture group, each described image capture group
Including four industrial cameras, and four industrial cameras be uniformly deployed in the same sectional position of high-tension cable quadrangle and four
The shooting of the industrial camera is centrally formed a rectangle, and the shooting center of four industrial cameras is located at the square
The quadrangle of shape；
S1200, each industrial camera is connected with a Digital Image Processor respectively, in the Digital Image Processor
Equipped with Image Edge-Detection module；
S1300, each Digital Image Processor are separately connected detection judgment module；
Further, in one of the embodiments, high-tension cable every distance L (length) dispose four industrial cameras,
Four industrial cameras are uniformly deployed in upper left side, upper right side, lower left and the lower right of the same sectional position of high-tension cable, each work
Mutual solid space angle in 90 °, captures high-voltage cable insulating layer surface image information between industry camera；L (length) is 2 meters
To 3 meters, such as L (length) is 2 meters or 3 meters, and when industrial camera precision is higher, L (length) can be higher.The industrial camera
CCD (Charge Couple Device, charge coupled cell) industrial line-scan digital camera is selected, wherein parameter request are as follows: video system
It is 768 × 576, pixel depth 12Bit that formula, which selects PAL system, selects the mode exposed line by line, time for exposure and row period keep
Unanimously, camera pixel dimension selects 5 μm.Each industrial camera is connected with a Digital Image Processor respectively, at digital picture
Reason device is special integrated chip or digital signal processor or on-site programmable gate array FPGA, and interior burn has Image Edge-Detection
Software is as Image Edge-Detection module；Four Digital Image Processors are connected with client, and detection is equipped in client
Judgment module for example detects judgment module software implementation and is set as result judgement software.
S2000 extracts high-voltage cable insulating layer surface image information by the detection platform；One embodiment wherein
In, high-voltage cable insulating layer surface image information is extracted using industrial camera.Wherein, for each described image acquisition group, four
Platform industrial camera is parallel to carry out image acquisition to high-tension cable simultaneously, that is, four works positioned at the same sectional position of high-tension cable
Industry camera parallel simultaneously takes pictures to high-tension cable from respective angle, respectively obtains surface of insulating layer image G1、G2、G3、G4,
And by G1、G2、G3、G4It is respectively transmitted to the corresponding Digital Image Processor U of each industrial camera1、U2、U3、U4；G1、G2、G3、G4's
Size is W × L, and W indicates G1、G2、G3、G4Every row pixel number, L indicate G1、G2、G3、G4Each column pixel number, W and L
It is positive integer；High-voltage cable insulating layer surface image information is extracted by the detection platform in one of the embodiments,
Before or after, the high-voltage cable insulating detection method further comprises the steps of: the mobile detection platform；The mobile detection is flat
The distance of platform is L1+L2, wherein L1 is the length of the detection platform, and L2 is the shooting distance that described image obtains instrument.
S3000, U1、U2、U3、U4Image Edge-Detection modular concurrent detect G respectively1、G2、G3、G4Concave-convex edge, sentence
Determine G1、G2、G3、G4Whether corresponding high-voltage cable insulating layer surface planarization meets the requirements, i.e. U1Image Edge-Detection it is soft
Part detects G1Edge, U2Image Edge-Detection software detection G2Edge, U3Image Edge-Detection software detection G3Side
Edge, U4Image Edge-Detection software detection G4Edge, U1、U2、U3、U4Image Edge-Detection software to G1、G2、G3、G4's
Edge detection method is identical.UqImage Edge-Detection software detection GqThe step of concave-convex edge, is as follows, wherein and 1≤q≤
4.Wherein, the concave-convex edge of each surface of insulating layer image is detected respectively by the way of breadth first traversal.Such design, has
Conducive to showing that the syntople between strong edge point improves detection efficiency and edge detection conducive to the judgement of boundary curve
Accuracy.
S3100, UqImage Edge-Detection software using Wiener filtering to digital picture GqIt carries out denoising operation and obtains GqA,
GqASize is W × L；Further, step S3100 includes: to G in one of the embodiments,qWiener filtering denoising is carried out,
Using denoising function [G in MatlabqA, noise] and=wiener2 (Gq, [3,3]) and to image GqIt is big using 3 × 3 filtering windows
Small carry out image denoising, wherein GqAFor image after denoising, noise is image GqNoise power estimation value.
S3200, UqImage Edge-Detection software calculate GqAImage threshold T；Further, one embodiment wherein
In, step S3200 includes: using the maximum variance between clusters function graythresh (G in MatlabqA) find out image GqA's
Threshold value T, i.e. T=graythresh (GqA)。
S3300, UqImage Edge-Detection software to GqAIn relief region carry out edge detection, determine GqACorresponding
High-voltage cable insulating layer whether there is true edge, if it exists true edge, then GqACorresponding high-voltage cable insulating layer surface
Planarization is undesirable, if it does not exist true edge, then GqACorresponding high-voltage cable insulating layer surface planarization conforms to
It asks；Carry out edge detection the following steps are included:
S3310 is initialized, comprising: setting GqAIn a row b column pixel Pa,bAccess flag Flag be
False, Pa,bAccess flag Flag Flaga,bIt indicates, even Flaga,b=false, difference initialized pixel point stack S and picture
Vegetarian refreshments queue Q is sky, is connected to mark Connected for queue Q setting, and default Connected=false；
S3320 enables row variable a=1, column variable b=1；
S3321 executes step S33211 if 1≤a < L and 1≤b < W；If b=W and a < L, step S3322 is executed；If a=
L and b < W execution step S3323；If a=L and b=W, entire GqAIt has detected and has finished and be not present true edge, detected
It as a result is GqACorresponding high-voltage cable insulating layer surface planarization meets the requirements, and is transferred to the detection judgment module and execution
Step S4000；Wherein, if a=L and b=W, that is, illustrate entire GqAIt has detected and has finished and be not present true edge, it is defeated to client
" G outqACorresponding cable meets the requirements " conclusion, execute step S4000；
S33211 calculates pixel Pa,bGradient value Ka,b,GxIndicate Pa,bThrough transverse edge
The gray value of image of detection, GyIndicate Pa,bThe gray value of image detected through longitudinal edge；Further, an implementation wherein
In example, in step S33211, the pixel Pa,bGradient value Ka,bIt is calculated using Prewitt operator, comprising:
Ka,b=max [Gx,Gy]
Wherein, F (a, b) indicate pixel (a, b) gray value, if a=1, enable F (a-1, b-1)=0, F (a-1, b)=
0, F (a-1, b+1)=0；If b=1, F (a+1, b-1)=0, F (a-1, b-1)=0, F (a, b-1)=0 is enabled；If a=L, F (a is enabled
+ 1, b-1)=0, F (a+1, b)=0, F (a+1, b+1)=0；If b=W, F (a+1, b+1)=0, F (a-1, b+1)=0, F
(a, b+1)=0.
S33212, if Pa,bGradient value Ka,bMore than or equal to T, then Pa,bFor strong edge point, Flag is enableda,b=false, and b
=b+1 executes step S3321；If Pa,bGradient value Ka,bLess than T, P is determineda,bFor weak marginal point, if Flaga,b=true, if
B=b+1 is set, step S3321 is executed, if Flaga,b=false executes step S33213；
S33213, by Pa,bIt is put into S, as the element S in Sa,b, by Pa,bIt is put into Q, as the element Q in Qa,b；
S33214 successively takes out pixel in Q, empties team if S is empty and Q connection mark Connected=false
Q is arranged, b=b+1 is enabled, step S3321 is executed, if the pixel institute stored in connection the mark Connected=true, Q of Q
Composition curve is true edge, obtains GqAThere are true edges, then obtaining testing result is GqACorresponding high-voltage cable insulating
Layer surface planarization is undesirable, successively takes out the pixel in Q, empties queue Q, will test result and be transferred to the detection
Judgment module and execution step S4000；If S is not empty, the taking-up pixel S from Sa,b, execute step S332141；For example,
GqAThere are when true edge, illustrate GqACorresponding cable is undesirable, successively takes out the pixel in Q, empties queue Q,
" G is exported to clientqACorresponding cable is undesirable " conclusion, execute step S4000.
S332141, if a=1 and b=1, search for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b+1、
Pa+1,b+1And Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then by the weak edge
Point is respectively put into S and Q and the Flag=true of the pixel is arranged, and step S33214 is executed, if 3 neighborhood territory pixel points are weak
The Flag of marginal point and 3 neighborhood territory pixel points is false, then 3 neighborhood territory pixel points is respectively put into S and Q and 3 neighbours are arranged
The Flag=true of domain pixel, execute step S33214, if in neighborhood territory pixel point all weak marginal points Flag=true, hold
The Connected=true of queue Q is arranged if there are strong edge points in neighborhood territory pixel point in row step S33214, executes step
S33214；If being unsatisfactory for a=1 and b=1, S332142 is thened follow the steps；
S332142 searches for S if b=1 and 1 < a < La,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、
Pa-1,b+1、Pa,b+1、Pa+1,b+1、Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then
The weak marginal point is respectively put into S and Q and the Flag=true of the weak marginal point is set, step S33214 is executed, if 5 neighborhoods
Pixel is that the Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then distinguishes 5 neighborhood territory pixel points
It is put into S and Q and the Flag=true of 5 neighborhood territory pixel points is set, step S33214 is executed, if all weak sides in neighborhood territory pixel point
The Flag=true of edge point executes step S33214, if being arranged queue Q's there are strong edge point in neighborhood territory pixel point
Connected=true executes step S33214；If being unsatisfactory for b=1 and 1 < a < L, S332143 is thened follow the steps；
S332143, if a=1 and 1 <b < W, search for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b-1、
Pa+1,b-1、Pa+1,b、Pa+1,b+1、Pa,b+1If there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then
The weak marginal point is respectively put into S and Q and the Flag=true of the marginal point is set, step S33214 is executed, if 5 neighborhood pictures
Vegetarian refreshments is that the Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then puts 5 neighborhood territory pixel points respectively
Enter S and Q and the Flag=true of 5 neighborhood territory pixel points is set, step S33214 is executed, if all weak edges in neighborhood territory pixel point
The Flag=true of point executes step S33214 if there are strong edge points in neighborhood territory pixel point and is arranged queue Q's
Connected=true executes step S33214；If being unsatisfactory for a=1 and 1 <b < W, S332144 is thened follow the steps；
S332144, if 1 < a < L and 1 <b < W, search for Sa,bIn image G1AThe neighborhood territory pixel point of middle position (a, b)
Pa-1,b-1、Pa-1,b、Pa-1,b+1、Pa,b+1、Pa+1,b+1、Pa+1,b、Pa+1,b-1、Pa,b-1If there are weak marginal points for neighborhood territory pixel point, and should
The weak marginal point is then respectively put into S and Q and the Flag=true of the marginal point is arranged, held by the Flag=false of weak marginal point
Row step S33214, if the Flag that 8 neighborhood territory pixel points are weak marginal point and 8 neighborhood territory pixel points is Flag=false,
8 neighborhood territory pixel points are then respectively put into S and Q and the Flag=true of 8 neighborhood territory pixel points is set, execute step S33214,
If the Flag=true of all weak marginal points in neighborhood territory pixel point, step S33214 is executed, if there are strong sides in neighborhood territory pixel point
The Connected=true of queue Q is then arranged in edge point, executes step S33214；If being unsatisfactory for 1 < a < W and 1 <b < L, step is executed
Rapid S33214；
S3322 searches for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、Pa-1,b-1、Pa,b-1、Pa+1,b-1、
Pa+1,bIf there are weak marginal point and the Flag=false of the weak marginal point for neighborhood territory pixel point, which is respectively put into
S and Q and the Flag=true that the marginal point is arranged enable a=a+1, b=0, step S33214 are executed, if 5 neighborhood territory pixel points are equal
Flag for weak marginal point and 5 neighborhood territory pixel points is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q
And the Flag=true of 5 neighborhood territory pixel points is set, a=a+1, b=0 are enabled, step S33214 is executed, if institute in neighborhood territory pixel point
There is the Flag=true of weak marginal point, enable a=a+1, b=0, step S33214 is executed, if there are strong edges in neighborhood territory pixel point
The Connected=true of queue Q is then arranged in point, enables a=a+1, b=0, executes step S33214；
S3323 searches for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b-1、Pa-1,b-1、Pa-1,b、Pa-1,b+1、
Pa,b+1If the weak marginal point is respectively put into S there are weak marginal point and the weak marginal point Flag=false by neighborhood territory pixel point
With Q and the Flag=true of the marginal point is set, step S33214 is executed, if 5 neighborhood territory pixel points are weak marginal point and 5
The Flag of neighborhood territory pixel point is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q and 5 neighborhood pictures are arranged
The Flag=true of vegetarian refreshments, execute step S33214, if in neighborhood territory pixel point all weak marginal points Flag=true, execute step
The Connected=true of queue Q is arranged if there are strong edge points in neighborhood territory pixel point in rapid S33214, executes step
S33214；
S4000, the detection judgment module is from U1、U2、U3、U4Image Edge-Detection module receive G respectively1、G2、G3、G4
Whether corresponding high-voltage cable insulating layer surface planarization is satisfactory as a result, if 4 results meet the requirements entirely, sentences
Determine G1、G2、G3、G4The profile pattern of corresponding high-voltage cable insulating layer meets the requirements, the high-tension cable of corresponding length section
The profile pattern of insulating layer reach quality requirement；If have in 4 results one it is undesirable, determine G1、G2、G3、G4
The profile pattern of corresponding high-voltage cable insulating layer is undesirable, the insulating layer of the high-tension cable of corresponding length section
Profile pattern is not up to quality requirement.
It continues with and provides a specific embodiment.The high-voltage cable insulating detection in one of the embodiments,
Method specifically includes following part or all of step.
1.1 high-tension cables dispose four industrial cameras every distance L2, and four industrial cameras are uniformly deployed in high-tension cable
Upper left side, upper right side, lower left and the lower right of same sectional position, mutual solid in 90 ° between the shooting center of each industrial camera
Space angle captures high-voltage cable insulating layer surface image information, and L2 is generally 2 meters.The industrial camera selects CCD
(Charge Couple Device, charge coupled cell) industry line-scan digital camera, wherein parameter request are as follows: video formats are selected
PAL system is 768 × 576, pixel depth 12Bit, selects the mode exposed line by line, and the time for exposure is consistent with the row period,
Camera pixel dimension selects 5 μm.
1.2 each industrial cameras are connected with a Digital Image Processor respectively.Digital Image Processor is dedicated integrated
Chip or digital signal processor or field programmable gate array (FPGA), interior burning have Image Edge-Detection software.
1.3 4 Digital Image Processors are connected with client, and result judgement software is equipped in client.
Second step, industrial camera extract high-voltage cable insulating layer surface image information, method are as follows:
Positioned at the same sectional position of high-tension cable four industrial cameras parallel from respective angle simultaneously to high-tension cable into
Row is taken pictures, and image G is respectively obtained1、G2、G3、G4, and by G1、G2、G3、G4It is respectively transmitted to the corresponding digital picture of each industrial camera
Processor U1、U2、U3、U4, G1、G2、G3、G4Size be W × L, W indicates G1、G2、G3、G4Every row pixel number, L are indicated
G1、G2、G3、G4Each column pixel number, W and L are positive integer.
Third step, U1、U2、U3、U4Image Edge-Detection software parallel detect G respectively1、G2、G3、G4Concave-convex edge, sentence
Determine G1、G2、G3、G4Whether corresponding high-voltage cable insulating layer surface planarization meets the requirements, i.e. U1Image Edge-Detection it is soft
Part detects G1Edge, U2Image Edge-Detection software detection G2Edge, U3Image Edge-Detection software detection G3Side
Edge, U4Image Edge-Detection software detection G4Edge, U1、U2、U3、U4Image Edge-Detection software to G1、G2、G3、G4's
Edge detection method is identical.UqThe Image Edge-Detection software detection G of (1≤q≤4)qThe method at concave-convex edge are as follows:
3.1UqImage Edge-Detection software using Wiener filtering to digital picture GqIt carries out denoising operation and obtains GqA, step
It is rapid as follows:
3.1.1UqImage Edge-Detection software using Wiener filtering to digital picture GqIt carries out denoising operation and obtains GqA,
GqASize is W × L；For example, to GqWiener filtering processing is carried out, using the Matlab (business that MathWorks company, the U.S. produces
Mathematical software) in function [G is denoised under toolbox imagesqA, noise] and=wiener2 (Gq, [3,3]) and to image GqUsing 3
× 3 filtering window sizes carry out image denoising, wherein GqAFor image after denoising, noise is image GqNoise power
Estimated value.
3.2UqImage Edge-Detection software calculate GqAImage threshold T, the method is as follows: using in Matlab
Toolbox the maximum variance between clusters function graythresh (G that encapsulates under imagesqA) find out image GqAThreshold value T, i.e. T
=graythresh (GqA)。
3.3UqImage Edge-Detection software to GqAIn relief region carry out edge detection, determine GqACorresponding height
Voltage cable insulating layer whether there is true edge, if it exists true edge, then GqACorresponding high-voltage cable insulating layer surface is flat
Whole property is undesirable, if it does not exist true edge, then GqACorresponding high-voltage cable insulating layer surface planarization meets the requirements.
The true edge is caused by two kinds of situations, first is that, the strong edge curve that strong edge point is constituted is true edge, and strong edge point is
Pixel gradient value K (GxIndicate the gray value of image that the pixel is detected through transverse edge, GyIt indicates
The gray value of image that the pixel is detected through longitudinal edge) it is more than or equal to GqAThe pixel of threshold value T；Second is that weak boundary curve (by
Weak marginal point is constituted, and the gradient value K of weak marginal point, that is, pixel is less than GqAThe pixel of threshold value T) in it is one or more if it exists
Pixel is connected with strong edge point, then the weak boundary curve is true edge.Weak marginal point is caused by true edge or by outer
Boundary's interference causes, and weak marginal point caused by true edge is often connected with strong edge point, and by weak side caused by external interference
Edge point is not connected then with strong edge point.In one of the embodiments, as shown in figure 5, specific detection method is described as follows.
3.3.1 it initializes: setting GqAIn a row b column pixel Pa,bAccess flag Flag be false, Pa,bVisit
Ask sign of flag Flaga,bIt indicates, even Flaga,b=false indicates Pa,bNot visited mistake, difference initialized pixel point stack S
It is sky with pixel queue Q, is connected to mark Connected for queue Q setting, and default Connected=false (to indicate in Q
Pixel do not constitute true edge).
3.3.2 row variable a=1, column variable b=1 are enabled；
If 3.3.2.1 1≤a < L and 1≤b < W, 3.3.2.1.1 is executed；If b=W and a < L, 3.3.2.2 is executed；If a=L
And b < W executes 3.3.2.3；If a=L and b=W illustrate entire GqAIt has detected and has finished and true edge, G is not presentqAIt is corresponding
Cable meet the requirements, to client export " GqACorresponding cable meets the requirements " conclusion, execute the 4th step.
3.3.2.1.1 calculating pixel Pa,bGradient value Ka,b,GxIndicate Pa,bThrough widthwise edge
The gray value of image of edge detection, GyIndicate Pa,bThe gray value of image detected through longitudinal edge；For example, being calculated using Sobel operator
Pixel Pa,bGradient value Ka,b, Sobel operator is by Irwin Sobel in nineteen sixty-eight in Stanford University Artificial Intelligence Laboratory
Giving a report, " (one kind is at image by A 3 × 3Isotropic Gradient Operator forImage Processing
Reason 3 × 3 isotropism gradient operators) " in be put forward for the first time, by Pingle in document Pingle, K.K., " Visual
Perception by a Computer (computer vision perception) ", in Automatic Interpretation and
Classification of Images,A.Grasselli(Ed.),Academic Press,New York,1969,
Pp.277-284. it is elaborated in, wherein
Gx=[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)]
Gy=[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) indicates the gray value of pixel (a, b),
If a=1, F (a-1, b-1)=0, F (a-1, b)=0, F (a-1, b+1)=0 is enabled；
If b=1, F (a+1, b-1)=0, F (a-1, b-1)=0, F (a, b-1)=0 is enabled；
If a=L, F (a+1, b-1)=0, F (a+1, b)=0, F (a+1, b+1)=0 is enabled；
If b=W, F (a+1, b+1)=0, F (a-1, b+1)=0, F (a, b+1)=0.
The pixel P in one of the embodiments,a,bGradient value Ka,bIt is calculated using Prewitt operator, method
Are as follows:
Ka,b=max [Gx,Gy],
Wherein, F (a, b) indicates the gray value of pixel (a, b), similarly,
If a=1, F (a-1, b-1)=0, F (a-1, b)=0, F (a-1, b+1)=0 is enabled；
If b=1, F (a+1, b-1)=0, F (a-1, b-1)=0, F (a, b-1)=0 is enabled；
If a=L, F (a+1, b-1)=0, F (a+1, b)=0, F (a+1, b+1)=0 is enabled；
If b=W, F (a+1, b+1)=0, F (a-1, b+1)=0, F (a, b+1)=0.
If 3.3.2.1.2 Pa,bGradient value Ka,bMore than or equal to T, then Pa,bFor strong edge point, Flag is enableda,b=false, and
B=b+1 turns 3.3.2.1；If Pa,bGradient value Ka,bLess than T, P is determineda,bFor weak marginal point, if Flaga,bB is arranged in=true
=b+1, turns 3.3.2.1, if Flaga,b=false executes 3.3.2.1.3；
3.3.2.1.3 by Pa,bIt is put into S, as the element S in stack Sa,b, by Pa,bIt is put into Q, as the element in queue Q
Qa,b；
If 3.3.2.1.4 S is empty and Q connection mark Connected=false, pixel in Q is successively taken out, is emptied
Queue Q enables b=b+1,3.3.2.1 is executed, if the connection mark Connected=true of Q, illustrates the pixel stored in Q
Constituted curve is true edge, i.e. GqAThere are true edges, illustrate GqACorresponding cable is undesirable, successively takes out Q
In pixel, empty queue Q, to client export " GqACorresponding cable is undesirable " conclusion, execute the 4th step；
If S is not empty, the taking-up pixel S from Sa,b, execute 3.3.2.1.4.1.
If 3.3.2.1.4.1 a=1 and b=1, search for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a
,b+1、Pa+1,b+1And Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then this is weak
Marginal point is respectively put into S and Q and the Flag=true of the pixel is arranged, and 3.3.2.1.4 is executed, if 3 neighborhood territory pixel points are equal
Flag for weak marginal point and 3 neighborhood territory pixel points is false, then 3 neighborhood territory pixel points is respectively put into S and Q and is arranged 3
The Flag=true of a neighborhood territory pixel point, execute 3.3.2.1.4, if in neighborhood territory pixel point all weak marginal points Flag=
True turns 3.3.2.1.4, if the Connected=true of queue Q is arranged there are strong edge point in neighborhood territory pixel point, turns
3.3.2.1.4.If being unsatisfactory for a=1 and b=1,3.3.2.1.4.2 is executed；
If 3.3.2.1.4.2 b=1 and 1 < a < L, S is searched fora,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、
Pa-1,b+1、Pa,b+1、Pa+1,b+1、Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then
The weak marginal point is respectively put into S and Q and the Flag=true of the weak marginal point is set, 3.3.2.1.4 is executed, if 5 neighborhoods
Pixel is that the Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then distinguishes 5 neighborhood territory pixel points
It is put into S and Q and the Flag=true of 5 neighborhood territory pixel points is set, turn 3.3.2.1.4, if all weak edges in neighborhood territory pixel point
The Flag=true of point, turns 3.3.2.1.4, if there are strong edge points in neighborhood territory pixel point, the Connected of queue Q is arranged
=true, turns 3.3.2.1.4.If being unsatisfactory for b=1 and 1 < a < L, 3.3.2.1.4.3 is executed；
If 3.3.2.1.4.3 a=1 and 1 <b < W, search for Sa,bIn image GqAThe neighborhood territory pixel point of middle position (a, b)
Pa,b-1、Pa+1,b-1、Pa+1,b、Pa+1,b+1、Pa,b+1If there are weak marginal points for neighborhood territory pixel point, and the Flag=of the weak marginal point
The weak marginal point is then respectively put into S and Q and the Flag=true of the marginal point is arranged, turns 3.3.2.1.4 by false, if 5
Neighborhood territory pixel point is that the Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then by 5 neighborhood territory pixel points
It is respectively put into S and Q and the Flag=true of 5 neighborhood territory pixel points is set, turn 3.3.2.1.4, if all weak in neighborhood territory pixel point
The Flag=true of marginal point, turns 3.3.2.1.4, if being arranged queue Q's there are strong edge point in neighborhood territory pixel point
Connected=true turns 3.3.2.1.4.If being unsatisfactory for a=1 and 1 <b < W, 3.3.2.1.4.4 is executed；
If 3.3.2.1.4.4 1 < a < L and 1 <b < W, search for Sa,bIn image G1AThe neighborhood territory pixel point of middle position (a, b)
Pa-1,b-1、Pa-1,b、Pa-1,b+1、Pa,b+1、Pa+1,b+1、Pa+1,b、Pa+1,b-1、Pa,b-1If there are weak marginal points for neighborhood territory pixel point, and should
The weak marginal point is then respectively put into S and Q and the Flag=true of the marginal point is arranged by the Flag=false of weak marginal point, is turned
3.3.2.1.4, if the Flag that 8 neighborhood territory pixel points are weak marginal point and 8 neighborhood territory pixel points is Flag=false,
8 neighborhood territory pixel points are respectively put into S and Q and the Flag=true of 8 neighborhood territory pixel points is set, turn 3.3.2.1.4, if neighborhood
The Flag=true of all weak marginal points, turns 3.3.2.1.4 in pixel, if setting in neighborhood territory pixel point there are strong edge point
The Connected=true for setting queue Q, turns 3.3.2.1.4.If being unsatisfactory for 1 < a < W and 1 <b < L, equally turn 3.3.2.1.4；
3.3.2.2 S is searched fora,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、Pa-1,b-1、Pa,b-1、Pa+1,b-1、
Pa+1,bIf there are weak marginal point and the Flag=false of the weak marginal point for neighborhood territory pixel point, which is respectively put into
S and Q and the Flag=true that the marginal point is arranged, enable a=a+1, b=0, turn 3.3.2.1.4, if 5 neighborhood territory pixel points are
The Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q simultaneously
The Flag=true of 5 neighborhood territory pixel points is set, enables a=a+1, b=0, turns 3.3.2.1.4, if all weak in neighborhood territory pixel point
The Flag=true of marginal point, enables a=a+1, b=0, turns 3.3.2.1.4, if setting in neighborhood territory pixel point there are strong edge point
The Connected=true for setting queue Q, enables a=a+1, b=0, turns 3.3.2.1.4.
3.3.2.3 S is searched fora,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b-1、Pa-1,b-1、Pa-1,b、Pa-1,b+1、
Pa,b+1If the weak marginal point is respectively put into S there are weak marginal point and the weak marginal point Flag=false by neighborhood territory pixel point
With Q and the Flag=true of the marginal point is set, enables a=a+1, b=0, turns 3.3.2.1.4, if 5 neighborhood territory pixel points are weak
The Flag of marginal point and 5 neighborhood territory pixel points is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q and set
The Flag=true for setting 5 neighborhood territory pixel points, enables a=a+1, b=0, turns 3.3.2.1.4, if all weak sides in neighborhood territory pixel point
The Flag=true of edge point, enables a=a+1, b=0, turns 3.3.2.1.4, if being arranged in neighborhood territory pixel point there are strong edge point
The Connected=true of queue Q, enables a=a+1, b=0, turns 3.3.2.1.4.
4th step, the result judgement software of client is from U1、U2、U3、U4Image Edge-Detection software receive G respectively1、
G2、G3、G4Whether corresponding high-voltage cable insulating layer surface planarization is satisfactory as a result, if 4 results conform to entirely
It asks, then determines G1、G2、G3、G4The profile pattern of corresponding high-voltage cable insulating layer meets the requirements, and corresponding length is L
The profile pattern of insulating layer of high-tension cable reach quality requirement；If have in 4 results one it is undesirable, determine
G1、G2、G3、G4The profile pattern of corresponding high-voltage cable insulating layer is undesirable, and corresponding length is the high pressure of L
The profile pattern of the insulating layer of cable is not up to quality requirement.
So far, by being detected to crosslinked polyetylene insulated layer surface planarization, high-voltage cable insulating detection is completed, is realized
Automated inspection saves human resources and avoids latent defect risk caused by artificial detection, and detection effect quality is stablized
And detection efficiency is higher, detection effect is more accurate.
A kind of high-tension cable maintaining method in one of the embodiments, comprising high-tension cable described in any embodiment
Insulation detecting method, the high-tension cable maintaining method further comprise the steps of: the profile pattern for determining the insulating layer of high-tension cable
Not up to quality requirement when, the cable is safeguarded.Further, in one of the embodiments, according to each described recessed
Flange and its testing result carry out differentiation maintenance to the cable.It is in one of the embodiments, as shown in fig. 6, a kind of
High-tension cable maintaining method comprising following steps: S1000 builds detection platform, and the detection platform includes at digital picture
Equipment and an at least image capture group are managed, each described image capture group includes that four images obtain instrument, four described images
It obtains instrument and is used to uniformly be deployed in the quadrangle of the same sectional position of high-tension cable and the shooting of four described images acquisition instruments
It is centrally formed a rectangle and is located at the quadrangle of the rectangle, the digital image processing apparatus is separately connected each described image
Instrument is obtained, the digital image processing apparatus is also connected with detection judgment module；S2000 is extracted high by the detection platform
Voltage cable surface of insulating layer image information；Wherein, for each described image acquisition group, it is parallel that four described images obtain instrument
Image acquisition is carried out to high-tension cable simultaneously from respective angle, surface of insulating layer image is respectively obtained and is transmitted to the digitized map
As processing equipment；S3000, the digital image processing apparatus detect the concave-convex edge of each surface of insulating layer image respectively, determine
Whether high-voltage cable insulating layer surface planarization corresponding to each surface of insulating layer image meets the requirements, and obtains testing result and biography
It is defeated by the detection judgment module；S4000, the detection judgment module determine high when it is no that each testing result is any
The profile pattern of the insulating layer of voltage cable is not up to quality requirement；S5000 determines the surfacing of the insulating layer of high-tension cable
When property is not up to quality requirement, the cable is safeguarded.Remaining embodiment and so on.Above-mentioned high-tension cable maintenance side
Whether method by design detection platform and detects high-voltage cable insulating layer surface planarization corresponding to each surface of insulating layer image
It meets the requirements, on the one hand realizes Automated inspection, save human resources, on the other hand avoid potential caused by artificial detection
Accident risk, another further aspect are conducive to quickly and efficiently carry out image acquisition to high-tension cable, and detection effect quality is stable and examines
It is higher to survey efficiency, and the detection sectional plane position of rectangular design, each image obtains image acquired in instrument can be more accurately
Reflect high-voltage cable insulating layer surface, to be conducive to whether subsequent judgement high-voltage cable insulating layer surface planarization conforms to
It asks, so that detection effect is more accurate, and then can timely and effectively carry out cable maintenance, avoids the generation of serious accident.
It should be noted that the other embodiments of the application further include, the mutually group of the technical characteristic in the various embodiments described above
Close be formed by, the high-voltage cable insulating detection method that can implement and high-tension cable maintaining method.
Each technical characteristic of embodiment described above can be combined arbitrarily, for simplicity of description, not to above-mentioned reality
It applies all possible combination of each technical characteristic in example to be all described, as long as however, the combination of these technical characteristics is not deposited
In contradiction, all should be considered as described in this specification.
The several embodiments of the application above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
The limitation to claim therefore cannot be interpreted as.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the concept of this application, various modifications and improvements can be made, these belong to the protection of the application
Range.Therefore, the scope of patent protection of the application should be determined by the appended claims.
Claims (10)
1. a kind of high-voltage cable insulating detection method, which comprises the following steps:
S1000, builds detection platform, and the detection platform includes digital image processing apparatus and an at least image capture group, often
One described image capture group includes that four images obtain instrument, and four described images obtain instrument for being uniformly deployed in high-voltage electricity
The shooting that the quadrangle of the same sectional position of cable and four described images obtain instrument is centrally formed a rectangle and is located at described
The quadrangle of rectangle, the digital image processing apparatus are separately connected each described image and obtain instrument, and the Digital Image Processing is set
It is standby to be also connected with detection judgment module；
S2000 extracts high-voltage cable insulating layer surface image information by the detection platform；Wherein, for each figure
As acquisition group, four described images obtain instrument and carry out image acquisition to high-tension cable simultaneously from respective angle parallel, respectively
To surface of insulating layer image and it is transmitted to the digital image processing apparatus；
S3000, the digital image processing apparatus detect the concave-convex edge of each surface of insulating layer image respectively, determine each insulating layer
Whether high-voltage cable insulating layer surface planarization corresponding to surface image meets the requirements, and obtains testing result and is transferred to described
Detect judgment module；
S4000, the detection judgment module determine the table of the insulating layer of high-tension cable when it is no that each testing result is any
Face planarization is not up to quality requirement.
2. high-voltage cable insulating detection method according to claim 1, which is characterized in that the detection platform includes at least two
Described image capture group, four described images of described image capture group obtain the rectangle institute that the shooting of instrument is centrally formed
Plane, the shooting center for obtaining instrument with four images of other image capture groups is formed by the plane phase where rectangle
In parallel.
3. high-voltage cable insulating detection method according to claim 2, which is characterized in that adjacent two described images capture group
Spacing is the shooting distance that described image obtains instrument.
4. high-voltage cable insulating detection method described according to claim 1, which is characterized in that the rectangle is square.
5. high-voltage cable insulating detection method according to claim 1, which is characterized in that the detection platform includes described in two
Image capture group.
6. high-voltage cable insulating detection method according to claim 1, which is characterized in that the digital image processing apparatus packet
Several Digital Image Processors are included, each Digital Image Processor is separately connected a described image correspondingly and obtains instrument
Device, each Digital Image Processor are also connected with the detection judgment module.
7. high-voltage cable insulating detection method according to claim 1, which is characterized in that the detection platform further includes client
It holds and the detection judgment module is set in the client.
8. high-voltage cable insulating detection method according to claim 1, which is characterized in that specifically include following steps；
S1100 builds detection platform, and the detection platform includes multiple images capture group, and each described image capture group includes
Four industrial cameras, and four industrial cameras be uniformly deployed in the same sectional position of high-tension cable quadrangle and four described in
The shooting of industrial camera is centrally formed a rectangle and is located at the quadrangle of the rectangle；
S1200, each industrial camera are connected with a Digital Image Processor respectively, are equipped in the Digital Image Processor
Image Edge-Detection module；
S1300, each Digital Image Processor are separately connected detection judgment module；
S2000 extracts high-voltage cable insulating layer surface image information by the detection platform；Wherein, for each figure
As acquisition group, four industrial cameras are parallel to carry out image acquisition to high-tension cable simultaneously, respectively obtains surface of insulating layer image G1、
G2、G3、G4, and by G1、G2、G3、G4It is respectively transmitted to the corresponding Digital Image Processor U of each industrial camera1、U2、U3、U4；G1、
G2、G3、G4Size be W × L, W indicates G1、G2、G3、G4Every row pixel number, L indicate G1、G2、G3、G4Each column pixel
Number, W and L are positive integer；
S3000, U1、U2、U3、U4Image Edge-Detection modular concurrent detect G respectively1、G2、G3、G4Concave-convex edge, determine G1、
G2、G3、G4Whether corresponding high-voltage cable insulating layer surface planarization meets the requirements, UqImage Edge-Detection software detection Gq
The step of concave-convex edge, is as follows, wherein 1≤q≤4；
S3100, UqImage Edge-Detection software using Wiener filtering to digital picture GqIt carries out denoising operation and obtains GqA, GqAGreatly
Small is W × L；
S3200, UqImage Edge-Detection software calculate GqAImage threshold T；
S3300, UqImage Edge-Detection software to GqAIn relief region carry out edge detection, determine GqACorresponding high pressure
Cable insulation whether there is true edge, if it exists true edge, then GqACorresponding high-voltage cable insulating layer surface is smooth
Property is undesirable, if it does not exist true edge, then GqACorresponding high-voltage cable insulating layer surface planarization meets the requirements；Into
Row edge detection the following steps are included:
G is arranged in S3310qAIn a row b column pixel Pa,bAccess flag Flag be false, Pa,bAccess flag Flag
Use Flaga,bIt indicates, even Flaga,b=false, initialized pixel point stack S and pixel queue Q are sky respectively, are set for queue Q
Connection mark Connected is set, and defaults Connected=false；
S3320 enables row variable a=1, column variable b=1；
S3321 executes step S33211 if 1≤a < L and 1≤b < W；If b=W and a < L, step S3322 is executed；If a=L and b
< W executes step S3323；If a=L and b=W, entire GqAIt has detected and has finished and be not present true edge, obtained testing result
For GqACorresponding high-voltage cable insulating layer surface planarization meets the requirements, and is transferred to the detection judgment module and executes step
S4000；
S33211 calculates pixel Pa,bGradient value Ka,b,GxIndicate Pa,bIt is detected through transverse edge
Gray value of image, GyIndicate Pa,bThe gray value of image detected through longitudinal edge；
S33212, if Pa,bGradient value Ka,bMore than or equal to T, then Pa,bFor strong edge point, Flag is enableda,b=false, and b=b+
1, execute step S3321；If Pa,bGradient value Ka,bLess than T, P is determineda,bFor weak marginal point, if Flaga,bB is arranged in=true
=b+1 executes step S3321, if Flaga,b=false executes step S33213；
S33213, by Pa,bIt is put into S, as the element S in Sa,b, by Pa,bIt is put into Q, as the element Q in Qa,b；
S33214 successively takes out pixel in Q, empties queue Q if S is empty and Q connection mark Connected=false,
B=b+1 is enabled, step S3321 is executed, if the pixel stored in connection the mark Connected=true, Q of Q is constituted
Curve is true edge, obtains GqAThere are true edges, then obtaining testing result is GqACorresponding high-voltage cable insulating layer table
Face planarization is undesirable, successively takes out the pixel in Q, empties queue Q, will test result and is transferred to the detection judgement
Module and execution step S4000；If S is not empty, the taking-up pixel S from Sa,b, execute step S332141；
S332141, if a=1 and b=1, search for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b+1、Pa+1,b+1
And Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then the weak marginal point is distinguished
It is put into S and Q and the Flag=true of the pixel is set, step S33214 is executed, if 3 neighborhood territory pixel points are weak marginal point
And the Flag of 3 neighborhood territory pixel points is false, then 3 neighborhood territory pixel points is respectively put into S and Q and 3 neighborhood territory pixels are arranged
Point Flag=true, execute step S33214, if in neighborhood territory pixel point all weak marginal points Flag=true, execute step
The Connected=true of queue Q is arranged if there are strong edge points in neighborhood territory pixel point in S33214, executes step
S33214；If being unsatisfactory for a=1 and b=1, S332142 is thened follow the steps；
S332142 searches for S if b=1 and 1 < a < La,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、Pa-1,b+1、
Pa,b+1、Pa+1,b+1、Pa+1,bIf there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then this is weak
Marginal point is respectively put into S and Q and the Flag=true of the weak marginal point is arranged, and step S33214 is executed, if 5 neighborhood territory pixel points
The Flag for being weak marginal point and 5 neighborhood territory pixel points is Flag=false, then by 5 neighborhood territory pixel points be respectively put into S and
Q and the Flag=true that 5 neighborhood territory pixel points are arranged execute step S33214, if all weak marginal points in neighborhood territory pixel point
Flag=true executes step S33214, if the Connected=of queue Q is arranged there are strong edge point in neighborhood territory pixel point
True executes step S33214；If being unsatisfactory for b=1 and 1 < a < L, S332143 is thened follow the steps；
S332143, if a=1 and 1 <b < W, search for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b-1、
Pa+1,b-1、Pa+1,b、Pa+1,b+1、Pa,b+1If there are weak marginal points for neighborhood territory pixel point, and the Flag=false of the weak marginal point, then
The weak marginal point is respectively put into S and Q and the Flag=true of the marginal point is set, step S33214 is executed, if 5 neighborhood pictures
Vegetarian refreshments is that the Flag of weak marginal point and 5 neighborhood territory pixel points is Flag=false, then puts 5 neighborhood territory pixel points respectively
Enter S and Q and the Flag=true of 5 neighborhood territory pixel points is set, step S33214 is executed, if all weak edges in neighborhood territory pixel point
The Flag=true of point executes step S33214 if there are strong edge points in neighborhood territory pixel point and is arranged queue Q's
Connected=true executes step S33214；If being unsatisfactory for a=1 and 1 <b < W, S332144 is thened follow the steps；
S332144, if 1 < a < L and 1 <b < W, search for Sa,bThe neighborhood territory pixel point P of position (a, b) in image G1Aa-1,b-1、
Pa-1,b、Pa-1,b+1、Pa,b+1、Pa+1,b+1、Pa+1,b、Pa+1,b-1、Pa,b-1If there are weak marginal points for neighborhood territory pixel point, and the weak edge
The Flag=false of point, then be respectively put into S and Q for the weak marginal point and the Flag=true of the marginal point be arranged, and executes step
S33214, if the Flag that 8 neighborhood territory pixel points are weak marginal point and 8 neighborhood territory pixel points is Flag=false, by 8
A neighborhood territory pixel point is respectively put into S and Q and the Flag=true of 8 neighborhood territory pixel points is arranged, and step S33214 is executed, if neighborhood
The Flag=true of all weak marginal points in pixel executes step S33214, if there are strong edge point in neighborhood territory pixel point,
The Connected=true of queue Q is set, step S33214 is executed；If being unsatisfactory for 1 < a < W and 1 <b < L, step is executed
S33214；
S3322 searches for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a-1,b、Pa-1,b-1、Pa,b-1、Pa+1,b-1、Pa+1,b,
If there are weak marginal point and the Flag=false of the weak marginal point for neighborhood territory pixel point, which is respectively put into S and Q
And the Flag=true of the marginal point is set, a=a+1, b=0 are enabled, step S33214 is executed, if 5 neighborhood territory pixel points are weak
The Flag of marginal point and 5 neighborhood territory pixel points is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q and set
The Flag=true for setting 5 neighborhood territory pixel points enables a=a+1, b=0, step S33214 is executed, if all weak in neighborhood territory pixel point
The Flag=true of marginal point, enables a=a+1, b=0, executes step S33214, if there are strong edge point in neighborhood territory pixel point,
The Connected=true of queue Q is set, a=a+1, b=0 are enabled, executes step S33214；
S3323 searches for Sa,bIn image GqAThe neighborhood territory pixel point P of middle position (a, b)a,b-1、Pa-1,b-1、Pa-1,b、Pa-1,b+1、Pa,b+1,
If the weak marginal point is respectively put into S and Q simultaneously there are weak marginal point and the weak marginal point Flag=false by neighborhood territory pixel point
The Flag=true of the marginal point is set, step S33214 is executed, if 5 neighborhood territory pixel points are weak marginal point and 5 neighborhoods
The Flag of pixel is Flag=false, then 5 neighborhood territory pixel points is respectively put into S and Q and 5 neighborhood territory pixel points are arranged
Flag=true, execute step S33214, if in neighborhood territory pixel point all weak marginal points Flag=true, execute step
The Connected=true of queue Q is arranged if there are strong edge points in neighborhood territory pixel point in S33214, executes step
S33214；
S4000, the detection judgment module is from U1、U2、U3、U4Image Edge-Detection module receive G respectively1、G2、G3、G4Institute is right
Whether the high-voltage cable insulating layer surface planarization answered is satisfactory as a result, if 4 results meet the requirements entirely, determines
G1、G2、G3、G4The profile pattern of corresponding high-voltage cable insulating layer meets the requirements, the high-tension cable of corresponding length section
The profile pattern of insulating layer reaches quality requirement；If have in 4 results one it is undesirable, determine G1、G2、G3、G4Institute
The profile pattern of corresponding high-voltage cable insulating layer is undesirable, the table of the insulating layer of the high-tension cable of corresponding length section
Face planarization is not up to quality requirement.
9. according to claim 1 to high-voltage cable insulating detection method described in any one of 8, which is characterized in that step S2000
In, before extracting high-voltage cable insulating layer surface image information by the detection platform, the high-voltage cable insulating detection side
Method further comprises the steps of: the mobile detection platform；The distance of the mobile detection platform is L1+L2, wherein L1 is the detection
The length of platform, L2 are the shooting distance that described image obtains instrument.
10. a kind of high-tension cable maintaining method, which is characterized in that exhausted including high-tension cable described in any one of claims 1 to 9
Edge detection method further comprises the steps of: when determining that the profile pattern of insulating layer of high-tension cable is not up to quality requirement, to described
Cable is safeguarded.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102141381A (en) * | 2010-12-23 | 2011-08-03 | 苏州天准精密技术有限公司 | Thickness and dimension automatic measuring instrument for insulation layer and protective sleeve of image type cable |
| CN103323463A (en) * | 2012-06-18 | 2013-09-25 | 戚景赞 | Automatic detection method and system for characteristics of enhanced composite carbon fiber wire core |
| CN104101613A (en) * | 2013-04-10 | 2014-10-15 | 苏州华觉智能科技有限公司 | Cable online detection system |
| CN104764407A (en) * | 2015-02-11 | 2015-07-08 | 盐城工学院 | Method for measuring thickness of cable protecting bush accurately |
| CN104820986A (en) * | 2015-04-28 | 2015-08-05 | 电子科技大学 | Machine vision-based cable on-line detection method |
| WO2016107408A1 (en) * | 2014-12-30 | 2016-07-07 | 江苏科技大学 | Infrared vision sensing detection method and device for narrow-gap weld seam deviation |
| CN105911067A (en) * | 2016-05-17 | 2016-08-31 | 无锡赛默斐视科技有限公司 | Cable protective jacket surface defect detector and detection method thereof |
| CN205721986U (en) * | 2015-04-28 | 2016-11-23 | 电子科技大学 | A kind of cable visual defects detection and character recognition device |
| US9665932B2 (en) * | 2013-09-03 | 2017-05-30 | Thales Transport & Security, Inc. | Camera based cable inspection system |
| CN106780357A (en) * | 2016-11-14 | 2017-05-31 | 国网天津市电力公司 | XLPE cable insulation degree of purity appraisal procedure based on image treating |
| CN107703148A (en) * | 2017-10-10 | 2018-02-16 | 贵州大学 | A kind of cable strand quality detecting system and its detection method based on machine vision |
| CN107957534A (en) * | 2017-10-13 | 2018-04-24 | 国网山东省电力公司济南供电公司 | A kind of cable connector detection device and method based on x-ray scanning |
| CN108280823A (en) * | 2017-12-29 | 2018-07-13 | 南京邮电大学 | The detection method and system of the weak edge faults of cable surface in a kind of industrial production |
| CN108961251A (en) * | 2018-07-24 | 2018-12-07 | 武汉纺织大学 | A kind of raw cotton fault and defects inspecting and recognition methods and system |
| CN109215020A (en) * | 2018-08-30 | 2019-01-15 | 国网黑龙江省电力有限公司佳木斯供电公司 | Ultra-high-tension power transmission line fault recognition method based on computer vision |
-
2019
- 2019-03-14 CN CN201910192454.6A patent/CN110009603B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102141381A (en) * | 2010-12-23 | 2011-08-03 | 苏州天准精密技术有限公司 | Thickness and dimension automatic measuring instrument for insulation layer and protective sleeve of image type cable |
| CN103323463A (en) * | 2012-06-18 | 2013-09-25 | 戚景赞 | Automatic detection method and system for characteristics of enhanced composite carbon fiber wire core |
| CN104101613A (en) * | 2013-04-10 | 2014-10-15 | 苏州华觉智能科技有限公司 | Cable online detection system |
| US9665932B2 (en) * | 2013-09-03 | 2017-05-30 | Thales Transport & Security, Inc. | Camera based cable inspection system |
| WO2016107408A1 (en) * | 2014-12-30 | 2016-07-07 | 江苏科技大学 | Infrared vision sensing detection method and device for narrow-gap weld seam deviation |
| CN104764407A (en) * | 2015-02-11 | 2015-07-08 | 盐城工学院 | Method for measuring thickness of cable protecting bush accurately |
| CN104820986A (en) * | 2015-04-28 | 2015-08-05 | 电子科技大学 | Machine vision-based cable on-line detection method |
| CN205721986U (en) * | 2015-04-28 | 2016-11-23 | 电子科技大学 | A kind of cable visual defects detection and character recognition device |
| CN105911067A (en) * | 2016-05-17 | 2016-08-31 | 无锡赛默斐视科技有限公司 | Cable protective jacket surface defect detector and detection method thereof |
| CN106780357A (en) * | 2016-11-14 | 2017-05-31 | 国网天津市电力公司 | XLPE cable insulation degree of purity appraisal procedure based on image treating |
| CN107703148A (en) * | 2017-10-10 | 2018-02-16 | 贵州大学 | A kind of cable strand quality detecting system and its detection method based on machine vision |
| CN107957534A (en) * | 2017-10-13 | 2018-04-24 | 国网山东省电力公司济南供电公司 | A kind of cable connector detection device and method based on x-ray scanning |
| CN108280823A (en) * | 2017-12-29 | 2018-07-13 | 南京邮电大学 | The detection method and system of the weak edge faults of cable surface in a kind of industrial production |
| CN108961251A (en) * | 2018-07-24 | 2018-12-07 | 武汉纺织大学 | A kind of raw cotton fault and defects inspecting and recognition methods and system |
| CN109215020A (en) * | 2018-08-30 | 2019-01-15 | 国网黑龙江省电力有限公司佳木斯供电公司 | Ultra-high-tension power transmission line fault recognition method based on computer vision |
Non-Patent Citations (1)
| Title |
|---|
| 张俊: "基于机器视觉的线缆表观缺陷在线检测系统的研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
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