CN111598109A - Intelligent identification method for reading of pointer instrument of transformer substation - Google Patents
Intelligent identification method for reading of pointer instrument of transformer substation Download PDFInfo
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Abstract
The invention relates to an intelligent identification method for reading of a pointer instrument of a transformer substation, which comprises the steps of image acquisition, image correction, graying, median filtering denoising, Gaussian filtering denoising, bilateral filtering denoising, image binarization, canny operator edge detection, corrosion operation, expansion operation, Hough circle transformation detection dial and circle center, Hough linear transformation detection pointer detection and reading output identification. The method can accurately identify the readings of various pointer instruments of the transformer substation in a complex environment, including the lightning arrester ammeter with thin pointers, can automatically identify the instrument type and configure a corresponding identification method after the instrument picture is shot, and accurately identifies the readings of the instrument.
Description
Technical Field
The invention belongs to the technical field of reading of a pointer instrument of a transformer substation, and particularly relates to an intelligent identification method for the reading of the pointer instrument of the transformer substation.
Background
With the development of the times, pointer instruments are replaced by digital instruments in most scenes, but electromagnetic interference usually exists in a transformer substation, and the digital instruments are easily affected, so that the pointer instruments in the transformer substation are still the first choice, and most of the transformer substation conservator oil level meters, the circuit breaker pressure meters, the lightning arrester ampere meters and the like are the pointer instruments. The pointer meter has the defects that manual reading is needed, certain errors exist in the manual reading, and even some accidents can be caused by misjudgment.
In addition, manual recording also requires manual data input into a computer, which is very cumbersome and does not allow real-time display of the meter readings, thereby bringing about some potential hidden dangers.
Application number (CN201610661013.2), this technique provides an image automatic shooting and wireless transmission device, to the image of shooing is carried out the preliminary treatment, is right the picture that has handled carries out the pointer location, carries out automatic interpretation to the pointer instrument value after the location, if the reading exceeds range or can't discern, saves the image in addition to the manual work is read. However, the method has some defects, firstly, the method can only be used for one pointer instrument, a transformer substation usually has a plurality of pointer instruments, an oil conservator oil level meter and a breaker pressure meter belong to common instruments, and a lightning arrester ammeter inputs a thin pointer instrument, so the method has no universality; secondly, only the illumination problem is processed, the pretreatment on the image of the fine pointer instrument is insufficient, and the robustness in a complex environment is poor; thirdly, the problem of reading error when the acquisition angle is inclined is not considered.
Disclosure of Invention
The invention provides a method for accurately identifying the reading of various pointer instruments of a transformer substation under a complex environment by improving and innovating the defects and problems in the background technology, which comprises a lightning arrester ammeter with a thin pointer, can automatically identify the type of the instrument and configure a corresponding identification method after the picture of the instrument is shot, and accurately identifies the reading of the instrument.
The technical scheme of the invention is to construct an intelligent reading identification method for a pointer instrument of a transformer substation, which comprises the following steps:
s1: acquiring a pointer instrument image of a transformer substation;
s2, detecting the dial frame based on Hough transformation, obtaining inclination angle and correcting the image, selecting polar coordinates, selecting rho ═ cos (theta) × x + sin (theta) × y ═ A sin (α + theta), carrying out threshold control on the extracted straight line, removing the inclination angle outside the threshold range, obtaining a proper angle by using a least square method for the inclination angle within the threshold, and setting the remained inclination angle theta1，θ2θ3θ4...θnThe most suitable angle is theta, (theta-theta)1)2+(θ-θ2)2+(θ-θn)2Minimum, using least square method to find the most suitable angle
S3: identifying a pointer instrument in the image;
s4: graying, median filtering denoising and Gaussian filtering denoising are carried out on the image, if the image is identified as a thin pointer, bilateral filtering denoising is also needed,
graying: gray ═ R0.299 + G0.587 + B0.114;
median filtering and denoising: sorting the gray levels of all pixels in a small window taking a current pixel as a center from small to large, and taking the middle value of a sorting result as the gray level of the pixel;
adding bilateral filtering denoising:
wherein, ω isijIs the current pixel weight, PijFor current pixel information, PiIs the current pixel neighborhood mean, CijAs current pixel position information, CiFor the current pixel mean position information, σ1And σ2Respectively representing the current pixel information and the standard deviation of the current pixel position;
and (3) Gaussian filtering denoising:
wherein, sigma is the standard deviation of normal distribution, the value of which determines the variation amplitude of the Gaussian function, and the corresponding value is the weight of the filter;
s5: image binarization, canny operator edge detection (x, y);
s6: opening operation is carried out on the image aiming at the problem of reading error when the collection angle is inclined;
s7: and (3) carrying out Hough circle transformation, detecting a dial and a circle center, and adopting polar coordinates:
y＝y0+r sinθ
y＝y0+r sinθ，
converting each pixel point to the center of a circle corresponding to the polar coordinate, accumulating the intensity of the polar coordinate, normalizing the intensity value in a polar coordinate space to make the intensity range between 0 and 255, searching the point with the maximum intensity, and drawing a detection result according to the center point.
S8: and (3) carrying out Hough linear transformation, detecting a pointer and acquiring an angle, and adopting a polar coordinate:
r＝x cosθ+y sinθ，
wherein r is the distance from the straight line to the origin, theta is the included angle between the straight line and the x axis, the number of curves intersected at one point is searched for on the plane theta-r through the straight line for detection, and a threshold value is set to determine the straight line and the angle.
Preferably, the pointer instrument in the image is identified in S3, and the fine pointer instrument and the non-fine pointer instrument are identified by using the model trained by the artificial neural network.
Preferably, Canny operator edge detection in S5: calculating the gradient strength and direction of each pixel point in the graph, applying non-maximum value inhibition, eliminating stray response caused by edge detection, applying double-threshold detection to determine true and potential edges, and finishing edge detection by inhibiting isolated weak edges.
Preferably, the opening operation in S6 is an erosion operation followed by an expansion operation.
The invention has the beneficial effects that:
the method can accurately read the reading of the pointer instrument of the transformer substation in a complex environment, different identification methods are configured for different pointer instruments, the method has strong universality and robustness, and the problems that the manual reading of the pointer instrument of the transformer substation is complicated and the existing reading method is not intelligent are solved.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is an original view of a meter;
FIG. 3 is a grayed image;
FIG. 4 is a median filtered denoised image;
FIG. 5 is a bilateral filtered denoised image;
FIG. 6 is a Gaussian filtered denoised image;
FIG. 7 is a post-edge detection image;
FIG. 8 shows a Hough circle transformation detection disk and the center of the circle;
fig. 9 shows a hough line transformation detection pointer.
Detailed Description
The present invention will be described in further detail with reference to fig. 1 to 9 of the drawings of the examples and the specification, but the embodiments of the present invention are not limited thereto. The embodiments of the present invention are not limited to the embodiments described above, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and they are included in the scope of the present invention.
The invention provides an intelligent identification method for reading of a pointer instrument of a transformer substation. An engineer in the field can write a program according to the method disclosed by the invention, and the written program is downloaded to intelligent equipment such as a computer to realize accurate intelligent reading with stronger universality and robustness, and the flow chart of the invention is shown in fig. 1.
Example 1:
a method for intelligently identifying the reading of a pointer instrument of a transformer substation comprises the following steps:
s1: acquiring a pointer instrument image of a transformer substation;
s2, detecting the dial frame based on Hough transformation, obtaining inclination angle and correcting the image, selecting polar coordinates, selecting rho ═ cos (theta) × x + sin (theta) × y ═ A sin (α + theta), carrying out threshold control on the extracted straight line, removing the inclination angle outside the threshold range, obtaining a proper angle by using a least square method for the inclination angle within the threshold, and setting the remained inclination angle theta1，θ2θ3θ4...θnThe most suitable angle is theta, (theta-theta)1)2+(θ-θ2)2+(θ-θn)2Minimum, using least square method to find the most suitable angle
S3: identifying a pointer instrument in the image;
s4: graying, median filtering denoising and Gaussian filtering denoising are carried out on the image, if the image is identified as a thin pointer, bilateral filtering denoising is also needed,
graying: gray ═ R0.299 + G0.587 + B0.114;
median filtering and denoising: sorting the gray levels of all pixels in a small window taking a current pixel as a center from small to large, and taking the middle value of a sorting result as the gray level of the pixel;
bilateral filtering and denoising:
wherein, ω isijIs the current pixel weight, PijFor current pixel information, PiIs the current pixel neighborhood mean, CijAs current pixel position information, CiFor the current pixel mean position information, σ1And σ2Respectively representing the current pixel information and the standard deviation of the current pixel position;
and (3) Gaussian filtering denoising:
wherein, sigma is the standard deviation of normal distribution, the value of which determines the variation amplitude of the Gaussian function, and the corresponding value is the weight of the filter;
s5: image binarization, canny operator edge detection (x, y);
s6: opening operation is carried out on the image aiming at the problem of reading error when the collection angle is inclined;
s7: and (3) carrying out Hough circle transformation, detecting a dial and a circle center, and adopting polar coordinates:
y＝y0+r sinθ
y＝y0+r sinθ，
converting each pixel point to the center of a circle corresponding to the polar coordinate, accumulating the intensity of the polar coordinate, normalizing the intensity value in a polar coordinate space to make the intensity range between 0 and 255, searching the point with the maximum intensity, and drawing a detection result according to the center point.
S8: and (3) carrying out Hough linear transformation, detecting a pointer and acquiring an angle, and adopting a polar coordinate:
r＝x cosθ+y sinθ，
wherein r is the distance from the straight line to the origin, theta is the included angle between the straight line and the x axis, the number of curves intersected at one point is searched for on the plane theta-r through the straight line for detection, and a threshold value is set to determine the straight line and the angle.
S1, providing an image acquisition module for acquiring the image of the pointer instrument of the transformer substation;
the median filtering denoising method in the S4 is a nonlinear filtering method, and can well maintain the image edge while filtering the noise;
the bilateral filtering denoising in the S4 considers not only the pixel information but also the pixel position information;
the purpose of the step of gaussian filtering and denoising in S4 is to expand the edge of the image, so as to reduce the gray scale of the noise point, thereby reducing the noise amount in the edge detection;
s6, aiming at the problem of reading errors when the acquisition angle is inclined, performing opening operation (firstly performing corrosion operation and then performing expansion operation) on the image to reduce the influence caused by the shadow of the pointer when the acquisition angle is inclined;
the point of maximum intensity described in S7 is typically a generally circular center point.
Example 2:
on the basis of the embodiment 1, the pointer instrument in the image is identified in S3, and a fine pointer instrument and a non-fine pointer instrument are identified by using the model trained by the artificial neural network.
Example 3:
based on embodiment 1, Canny operator edge detection in S5: calculating the gradient strength and direction of each pixel point in the graph, applying non-maximum value inhibition, eliminating stray response caused by edge detection, applying double-threshold detection to determine true and potential edges, and finishing edge detection by inhibiting isolated weak edges.
Example 4:
in example 1, the opening operation in S6 is an erosion operation and then an expansion operation. Small and meaningless targets are eliminated through corrosion operation, a target area is enlarged through expansion operation, and the influence caused by pointer shadows when the acquisition angle is inclined can be eliminated.
Claims (4)
1. The intelligent identification method for the reading of the pointer instrument of the transformer substation is characterized by comprising the following steps:
s1: acquiring a pointer instrument image of a transformer substation;
s2, detecting the dial frame based on Hough transformation, obtaining inclination angle and correcting the image, selecting polar coordinates, selecting rho ═ cos (theta) × x + sin (theta) × y ═ A sin (α + theta), carrying out threshold control on the extracted straight line, removing the inclination angle outside the threshold range, obtaining a proper angle by using a least square method for the inclination angle within the threshold, and setting the remained inclination angle theta1，θ2θ3θ4...θnThe most suitable angle is theta, the minimum variance is stable, and the variance is
Then, the least square method is utilized to obtain the most suitable angle
S3: identifying a pointer instrument in the image;
s4: graying, median filtering denoising and Gaussian filtering denoising are carried out on the image, if the image is identified as a thin pointer, bilateral filtering denoising is also needed,
graying: gray ═ R0.299 + G0.587 + B0.114;
median filtering and denoising: sorting the gray levels of all pixels in a small window taking a current pixel as a center from small to large, and taking the middle value of a sorting result as the gray level of the pixel;
adding bilateral filtering denoising:
wherein, ω isijIs the current pixel weight, PijFor current pixel information, PiIs the current pixel neighborhood mean, CijAs current pixel position information, CiFor the current pixel mean position information, σ1And σ2Respectively representing the current pixel information and the standard deviation of the current pixel position;
and (3) Gaussian filtering denoising:
wherein, sigma is the standard deviation of normal distribution, the value of which determines the variation amplitude of the Gaussian function, and the corresponding value is the weight of the filter;
s5: image binarization, canny operator edge detection (x, y);
s6: opening operation is carried out on the image aiming at the problem of reading error when the collection angle is inclined;
s7: and (3) carrying out Hough circle transformation, detecting a dial and a circle center, and adopting polar coordinates:
y＝y0+r sinθ
y＝y0+r sinθ，
converting each pixel point to the center of a circle corresponding to the polar coordinate, accumulating the intensity of the polar coordinate, normalizing the intensity value in a polar coordinate space to make the intensity range between 0 and 255, searching the point with the maximum intensity, and drawing a detection result according to the center point.
S8: and (3) carrying out Hough linear transformation, detecting a pointer and acquiring an angle, and adopting a polar coordinate:
r＝x cosθ+y sinθ，
wherein r is the distance from the straight line to the origin, theta is the included angle between the straight line and the x axis, the number of curves intersected at one point is searched for on the plane theta-r through the straight line for detection, and a threshold value is set to determine the straight line and the angle.
2. The intelligent substation pointer instrument reading identification method according to claim 1, wherein the pointer instrument in the identification image in S3 is identified by using a model trained by an artificial neural network, so as to identify a fine pointer instrument and a non-fine pointer instrument.
3. The intelligent identification method for the reading of the substation pointer instrument according to claim 1, characterized in that in S5, Canny operator edge detection: calculating the gradient strength and direction of each pixel point in the graph, applying non-maximum value inhibition, eliminating stray response caused by edge detection, applying double-threshold detection to determine true and potential edges, and finishing edge detection by inhibiting isolated weak edges.
4. The intelligent identification method for the reading of the pointer instrument of the substation as claimed in claim 1, wherein the opening operation in S6 is a corrosion operation followed by an expansion operation.
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| CN112836726A (en) * | 2021-01-12 | 2021-05-25 | 云南电网有限责任公司电力科学研究院 | Pointer instrument indication reading method and device based on video information |
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| CN113449599A (en) * | 2021-05-27 | 2021-09-28 | 国网河北省电力有限公司行唐县供电分公司 | Intelligent operation and maintenance auxiliary device of indoor substation based on image recognition technology |
| CN113792616A (en) * | 2021-08-26 | 2021-12-14 | 南方电网深圳数字电网研究院有限公司 | Remote meter reading system based on edge calculation and working method thereof |
| CN113837312A (en) * | 2021-09-30 | 2021-12-24 | 南方电网电力科技股份有限公司 | Method and device for evaluating running state of zinc oxide arrester |
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