CN111242938A - Automatic checking method for pressing plate state - Google Patents
Automatic checking method for pressing plate state Download PDFInfo
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- CN111242938A CN111242938A CN202010054417.1A CN202010054417A CN111242938A CN 111242938 A CN111242938 A CN 111242938A CN 202010054417 A CN202010054417 A CN 202010054417A CN 111242938 A CN111242938 A CN 111242938A
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- 238000003825 pressing Methods 0.000 title claims abstract description 21
- 238000000034 method Methods 0.000 title claims abstract description 17
- 238000001914 filtration Methods 0.000 claims abstract description 10
- 238000007689 inspection Methods 0.000 claims abstract description 10
- 238000012937 correction Methods 0.000 claims abstract description 8
- 238000003860 storage Methods 0.000 claims abstract description 4
- 238000012216 screening Methods 0.000 claims description 14
- 230000008859 change Effects 0.000 claims description 4
- 238000005520 cutting process Methods 0.000 claims description 3
- 230000000877 morphologic effect Effects 0.000 claims description 3
- 101100534231 Xenopus laevis src-b gene Proteins 0.000 description 5
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- 230000009466 transformation Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 2
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- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 230000003628 erosive effect Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
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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
- G06T11/00—2D [Two Dimensional] image generation
- G06T11/40—Filling a planar surface by adding surface attributes, e.g. colour or texture
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T3/00—Geometric image transformations in the plane of the image
- G06T3/60—Rotation of whole images or parts thereof
- G06T3/608—Rotation of whole images or parts thereof by skew deformation, e.g. two-pass or three-pass rotation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/20—Image enhancement or restoration using local operators
- G06T5/30—Erosion or dilatation, e.g. thinning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/90—Dynamic range modification of images or parts thereof
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
- G06T2207/10008—Still image; Photographic image from scanner, fax or copier
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
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Abstract
The invention provides a method for automatically checking the state of a pressing plate, which comprises the following steps: s1, scanning the two-dimensional code corresponding to the protection screen cabinet through the handheld scanning equipment, and acquiring the corresponding state of a pressure plate switch on the protection screen cabinet from the server; s2, acquiring the photo of the protection screen cabinet through the handheld scanning equipment and uploading the photo to a server; s3, the server sequentially performs background filtering, rotation correction and pressure plate state recognition on the picture, and returns the recognition result to the handheld scanning equipment; s4, the handheld scanning equipment compares the identification result with the corresponding set state and displays the comparison result on the handheld scanning equipment; and S5, the inspection personnel recheck according to the comparison result, and upload the result to the server for storage after confirming no error.
Description
Technical Field
The invention relates to the technical field of electric power system inspection assistance, in particular to a method for automatically checking the state of a pressing plate based on a protection screen cabinet pressing plate image.
Background
The number of protection screen cabinets in a 110kv substation is usually 10-20, the number of the protection screen cabinets in 220kv and 500kv substations can reach hundreds, the number of the pressure plate switches of each protection screen cabinet can reach fifty-four, and the pressure plate switches need to be checked in the inspection work. However, in the current manual inspection process, the problems of large workload, poor timeliness, materialization of working recording paper and the like exist, and inspection personnel may make mistakes due to factors such as physical and psychological quality, responsibility, technical level, working experience and the like, so that potential safety hazards are left, and even serious safety disasters are caused. Due to the long-term development of the existing machine vision technology and the existing network technology, the pressing plate part of the protection screen cabinet can be photographed through the camera, then the opening and closing state of the pressing plate is recognized through processing the image through the processor, finally the opening and closing state is checked through the pressing plate on-off table, and the checked result and the photographed picture are stored. However, the prior art has not developed a set of automatic checking system and method for the state of the pressing plate aiming at the manual inspection mode.
It is therefore desirable to develop a method for automatically checking the status of the platen. The method can automatically recognize the state of the pressing plate of the photographed picture of the pressing plate of the protection screen cabinet, then compares the state with a pressing plate on-off table in a background, and finally stores the comparison result and the photographed picture in a server in the background.
Disclosure of Invention
The invention provides a method for automatically checking the state of a pressing plate based on a protection screen cabinet pressing plate image, which can effectively solve the problems.
The invention is realized by the following steps:
a method for automatically checking the state of a pressing plate comprises the following steps:
s1, scanning the two-dimensional code corresponding to the protection screen cabinet through the handheld scanning equipment, and acquiring the corresponding state of a pressure plate switch on the protection screen cabinet from the server;
s2, acquiring the photo of the protection screen cabinet through the handheld scanning equipment and uploading the photo to a server;
s3, the server sequentially performs background filtering, rotation correction and pressure plate state recognition on the picture, and returns the recognition result to the handheld scanning equipment;
s4, the handheld scanning equipment compares the identification result with the corresponding set state and displays the comparison result on the handheld scanning equipment;
and S5, the inspection personnel recheck according to the comparison result, and upload the result to the server for storage after confirming no error.
The invention has the beneficial effects that: 1. the invention utilizes machine vision to identify and check the pressing plate of the protection screen cabinet, thereby improving the inspection efficiency of an inspector on the protection screen cabinet; 2. according to the invention, the background filtering and the rotation correction are carried out on the picture, and then the pressing plate state identification is carried out, so that the identification accuracy can be improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 to 23 are process images of background filtering, rotation correction, and platen state identification processing in the platen state automatic checking method according to the embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings of the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention.
Referring to fig. 1 to 23, an embodiment of the present invention provides a method for automatically checking a pressing plate state, including the following steps:
s1, scanning the two-dimensional code corresponding to the protection screen cabinet through the handheld scanning equipment, and acquiring the corresponding state of a pressure plate switch on the protection screen cabinet from the server;
s2, acquiring the photo of the protection screen cabinet through the handheld scanning equipment and uploading the photo to a server;
s3, the server sequentially performs background filtering, rotation correction and pressure plate state recognition on the picture, and returns the recognition result to the handheld scanning equipment;
s4, the handheld scanning equipment compares the identification result with the corresponding set state and displays the comparison result on the handheld scanning equipment;
and S5, the inspection personnel recheck according to the comparison result, and upload the result to the server for storage after confirming no error.
Referring to fig. 1, in step S3, the step of background filtering the photo includes:
s311, obtaining an S channel in an HSV color space, carrying out binarization on a threshold value 80 and a maximum value 255, and obtaining a picture as shown in FIG. 2:
s312, performing morphological operations using morphologyEx function, selecting a rectangle with a size of 9 × 9 by kernel, performing an operation on the image (erosion and then expansion), and obtaining a picture as shown in fig. 3:
opening operation:
img_open＝open(img_THR，element)＝dilate(erode(img_THRelement))
firstly, corrosion:
re-expansion:
s313, finding the contour by using a findContours function, storing all the found Contours, and obtaining the picture as shown in FIG. 4:
Contours＝findContours(img_open)。
s314, taking the minimum bounding rectangle bounding rect for each element of the contents, and obtaining a picture as shown in fig. 5:
BoundRects＝{boundRect|boundRect
＝Rect(min(contour.x)，min(contour.y)，max(contour.x)
-min(contour.x)，max(contour.y)-min(contour.y))contour∈Contours}。
s315, calculating the median of the areas of all BoundRects (instead of area boundary screening, so that the algorithm is suitable for distribution boards with various pixel sizes), and performing first screening on each element of BoundRects to define a deviation domain of BoundRects and screening out TarRects1, as shown in FIG. 6:
the area size set after the area size increasing sorting according to BoundRects is terms
terms(BoundRects)＝Ascendingorder(BoundRects.area)
Calculating median of terms
First screening
S316, screening out TarRects2 for the second time of screening each element of TarRects1 with the length-width ratio limited, as shown in FIG. 7;
TarRects2＝{rect|2*rect.height＞rect.width.rect∈TarRects1}。
s317, calculating and normalizing the histogram H of each element of the TarRect 2 by using calcHist function, comparing the histogram with the previously prepared red and yellow pressboard templates by using the composehist function, limiting the upper limit of the score, filtering the non-red and yellow pressboards, and performing a third screening of TarRect3, as shown in fig. 9:
the comparison histogram is as follows:
s318, calculating four corner points for each element of the TarRect3, and merging and storing the four corner points into a point container;
s319, taking the minimum bounding rectangle filter _ rect of all the points in the point container, adjusting the boundary range, and filling the portion outside the area in the input photo with white, to obtain the photo with filtered background, as shown in fig. 10.
As a further improvement, in step S3, the step of performing rotation correction on the photograph includes:
s321, taking a minimum area rectangle (minAreaRect) from the picture of the filtered background, and then finding a two-dimensional box (CvBox2D) to obtain a single rotation angle, as shown in fig. 11;
the average rotation angle avg _ angle is calculated.
Background filtered three screened platens were lined with the profile under the index:
Contours2＝{contour}contour＝Contours[rect.index]，rect∈TarRect3}
average rotation angle:
s322, selecting the larger number of the input graph in the longer width
Setting the times as canvas, taking a square with the length and the width as canvas, and filling the gap between the input graph and the canvas with copymakeBorder function to be black, as shown in FIG. 12;
side length of square canvas:
length and width of upper, lower, left and right filling areas:
dx＝(canvas_length-img_BGFilter.cols)/2
dy＝(canvas_length-img_BGFilter.rows)/2
thus, the canvas after filling:
canvas＝Rect(0，0，canvas_length，canvas_length)。
s323, the input graph is rotated by using a warpAffene function, the rotation angle is avg _ angle, and the center of the canvas is recorded as center, as shown in FIG. 13.
The original coordinates (x, y) are transformed into new coordinates (x ', y'), the middle transformation matrix is denoted as M.
The basic formula for transformation of warpAffine,
shift conversion if
x′＝x+tx
v′＝y+ty
Then
And (4) performing rotation conversion if the rotation angle is theta.
In opencv image processing, all image processing is performed from the origin, the origin of an image is defaulted to be the upper left corner of the image, and when we rotate the image, the center of the image is generally used as the axis, so the following processing is required: the axis is moved to the original point to do rotation transformation, and finally the upper left corner is set as the original point of the image.
src2(x′，y′)＝M3ximg_BGFilter(x，y)。
S324, calculating the size of the minimum bounding rectangle img _ Recor of the rotated image, and cutting off redundant frames of the canvas, as shown in FIG. 14:
output img _ Recor length and width:
img_Recor.width＝src2.cols*abs(cos(avg_angle))+src2.rowws*abs(sin(avg_angle))ig_Recor.height＝src2.cols*abs(sin(avg_angle))+src2.rows*abs(cos(avg_angle))
cutting the length and the width of a canvas area:
dx2＝(canvas_length-img_Recor.width)/2
dy2＝(canvas_length-img_Recor，height)/2
thus, the output img _ Recor:
img_Recor＝canvas(dx2，dy2，img_Recor.width.img_Recor.height)。
as a further improvement, in step S3, the step of performing platen state recognition on the photo includes:
S331-S336 are similar to S311-S316, please refer to FIGS. 15-20.
S337, judging the opening and closing state of a pressure plate according to the length-width ratio of each element of Tar curves 2; referring to fig. 21:
opening:
TarRects_on＝{rect|2*rect.width＞rect.height，rect∈TarRects2}
turning off:
TarRects_off＝{rect}2*rect.width≤rect.height，rect∈TarRects2}。
s338, sorting the x coordinates of each element of the TarRects2 in an increasing mode, calculating the difference between adjacent elements, and converting the difference into percentage change diff; s339, sorting the y coordinate of each element of tarreturns 2 in an increasing manner, calculating the difference between adjacent elements, and converting the difference into a percentage change diff, please refer to fig. 22 and 23:
and setting a threshold diffVal, and entering the next cluster when diffVal is larger than diffVal.
TarRects2＝Ascendibg order(TarRects2)
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (4)
1. A method for automatically checking the state of a pressing plate is characterized by comprising the following steps:
s1, scanning the two-dimensional code corresponding to the protection screen cabinet through the handheld scanning equipment, and acquiring the corresponding state of a pressure plate switch on the protection screen cabinet from the server;
s2, acquiring the photo of the protection screen cabinet through the handheld scanning equipment and uploading the photo to a server;
s3, the server sequentially performs background filtering, rotation correction and pressure plate state recognition on the picture, and returns the recognition result to the handheld scanning equipment;
s4, the handheld scanning equipment compares the identification result with the corresponding set state and displays the comparison result on the handheld scanning equipment;
and S5, the inspection personnel recheck according to the comparison result, and upload the result to the server for storage after confirming no error.
2. The platen status automatic checking method according to claim 1, wherein in step S3, the step of background-filtering the photograph includes:
s311, acquiring an S channel in an HSV color space, and carrying out binarization on a threshold value of 80 and a maximum value of 255;
s312, performing morphological operation by using a morphologoEx function, selecting a rectangle with the size of 9x9 by a kernel, and performing operation on the image;
s313, searching for Contours by using a findContours function, and storing all the found Contours;
s314, taking the minimum bounding rectangle for each element of the contigs;
s315, calculating the median of the areas of all BoundRects, limiting a deviation domain of each element of the BoundRects and carrying out first screening on the BoundRects and the deviation domain of the BoundRects, and screening out TarRects 1;
s316, limiting the length-width ratio of each element of the TarRects1 to carry out secondary screening, and screening out TarRects 2;
s317, calculating a histogram H of each element of the TarRects2 by using a calcHist function and normalizing, comparing the histogram with a red and yellow pressing plate template made in advance by using a composeHist function, limiting a score upper limit, filtering non-red and yellow pressing plates, and screening TarRect3 for the third time;
s318, calculating four corner points for each element of the TarRect3, and merging and storing the four corner points into a point container;
s319, taking the minimum circumscribed rectangle filter _ rect of all the points in the point container, adjusting the boundary range, and filling the parts outside the area in the input picture into white to obtain the picture with the filtered background.
3. The platen state automatic checking method according to claim 1, wherein in step S3, the step of performing rotation correction on the photograph includes:
s321, taking a minimum area rectangle from the picture of the filtered background, and then solving a two-dimensional box to obtain a single rotation angle;
s322, selecting the larger number of the input graph in the longer width
Double as canvas, let length and width be canvas squares are used as canvas, and the gap between the input graph and the canvas is filled with black by a copymakeBorder function;
s323, rotating the input graph by using a warpAffine function, wherein the rotating angle is avg _ angle, and the center of the canvas is recorded as center;
s324, calculating the size of the minimum circumscribed rectangle img _ Recor of the rotated image, and cutting off redundant frames of the canvas.
4. The platen state automatic collation method according to claim 1, wherein in step S3, said step of performing platen state recognition on said photograph includes:
s331, taking out an S channel in an input map HSV color space, and carrying out binarization on a threshold value of 80 and a maximum value of 255;
s332, performing morphological operation by using a morphologoEx function, selecting a rectangle with the size of 9x9 by a kernel, and performing operation on the image;
s333, searching Contours by using a findContours function, and storing all the found Contours;
s334, selecting a minimum bounding rectangle for each element of the contigs;
s335, calculating the median of the areas of all BoundRects, limiting the deviation domain of each element of the BoundRects and the BoundRects for the first time, and screening out TarRects 1;
s336, limiting the length-width ratio of each element of the TarRects1 for the second screening to screen out TarRects 2;
s337, judging the opening and closing state of a pressure plate according to the length-width ratio of each element of Tar curves 2;
s338, sorting the x coordinates of each element of the TarRects2 in an increasing mode, calculating the difference between adjacent elements, and converting the difference into percentage change diff;
s339, sorts each element' S y coordinate of tarreturns 2 incrementally, calculates neighboring element differences, and converts the neighboring differences into percentage change diff.
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Cited By (7)
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| CN112089148A (en) * | 2020-07-30 | 2020-12-18 | 许继集团有限公司 | Intelligent helmet system and pressing plate state identification method |
| CN112528742A (en) * | 2020-11-06 | 2021-03-19 | 广东电网有限责任公司中山供电局 | State checking method and device for transformer substation pressure plate |
| CN112564291A (en) * | 2020-12-14 | 2021-03-26 | 国网陕西省电力公司汉中供电公司 | Power equipment pressing plate state monitoring system and monitoring method |
| CN112949425A (en) * | 2021-02-05 | 2021-06-11 | 广东驰行电力设备有限公司 | Automatic identification method beneficial to improving accuracy of identifying on-off state of pressing plate |
| CN113158751A (en) * | 2021-02-05 | 2021-07-23 | 广东驰行电力设备有限公司 | Method for conveniently and rapidly processing on-off state of pressing plate |
| CN113159097A (en) * | 2021-02-05 | 2021-07-23 | 广东驰行电力设备有限公司 | Method for realizing automatic identification system of pressing plate switch state under network-free condition |
| CN117541028A (en) * | 2024-01-09 | 2024-02-09 | 国网山东省电力公司菏泽供电公司 | Management system for protecting pressing plate |
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| CN113158751A (en) * | 2021-02-05 | 2021-07-23 | 广东驰行电力设备有限公司 | Method for conveniently and rapidly processing on-off state of pressing plate |
| CN113159097A (en) * | 2021-02-05 | 2021-07-23 | 广东驰行电力设备有限公司 | Method for realizing automatic identification system of pressing plate switch state under network-free condition |
| CN117541028A (en) * | 2024-01-09 | 2024-02-09 | 国网山东省电力公司菏泽供电公司 | Management system for protecting pressing plate |
| CN117541028B (en) * | 2024-01-09 | 2024-04-12 | 国网山东省电力公司菏泽供电公司 | Management system for protecting pressing plate |
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| CN111242938B (en) | 2023-11-03 |
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