CN113344908A - Infrared image validity judgment method for electrolytic cell polar plate detection - Google Patents
Infrared image validity judgment method for electrolytic cell polar plate detection Download PDFInfo
- Publication number
- CN113344908A CN113344908A CN202110731906.0A CN202110731906A CN113344908A CN 113344908 A CN113344908 A CN 113344908A CN 202110731906 A CN202110731906 A CN 202110731906A CN 113344908 A CN113344908 A CN 113344908A
- Authority
- CN
- China
- Prior art keywords
- image
- area
- temperature
- quasi
- electrolytic bath
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 45
- 238000000034 method Methods 0.000 title claims abstract description 25
- 239000004744 fabric Substances 0.000 claims abstract description 36
- 238000004458 analytical method Methods 0.000 claims abstract description 7
- 238000012795 verification Methods 0.000 claims description 9
- 238000012549 training Methods 0.000 claims description 4
- 238000000926 separation method Methods 0.000 claims description 3
- 210000004027 cell Anatomy 0.000 description 51
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 10
- 229910052802 copper Inorganic materials 0.000 description 8
- 239000010949 copper Substances 0.000 description 8
- 238000005868 electrolysis reaction Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 4
- 238000012937 correction Methods 0.000 description 3
- 239000003792 electrolyte Substances 0.000 description 3
- 230000009466 transformation Effects 0.000 description 3
- 238000004873 anchoring Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 229910001220 stainless steel Inorganic materials 0.000 description 2
- 239000010935 stainless steel Substances 0.000 description 2
- 239000002253 acid Substances 0.000 description 1
- 230000003321 amplification Effects 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 238000013145 classification model Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001704 evaporation Methods 0.000 description 1
- 230000008020 evaporation Effects 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 230000024121 nodulation Effects 0.000 description 1
- 238000003199 nucleic acid amplification method Methods 0.000 description 1
- 238000007670 refining Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/11—Region-based segmentation
-
- 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
-
- 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
- G06T2207/10048—Infrared image
Landscapes
- Engineering & Computer Science (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Investigating Or Analyzing Materials Using Thermal Means (AREA)
Abstract
The invention belongs to the technical field of fault detection, and particularly relates to an infrared image validity judgment method for electrolytic bath polar plate detection. The invention respectively judges the effectiveness of the covering cloth and the exposed area based on whether the covering cloth is arranged on the electrolytic bath, and can ensure the reliability of the image effectiveness identification. When the device is used, the invalid pictures are removed before the analysis of the fault polar plate is carried out, so that fault false detection and missing detection caused by shielding of foreign matters can be avoided.
Description
Technical Field
The invention belongs to the technical field of fault detection, and particularly relates to an infrared image validity judgment method for electrolytic bath polar plate detection.
Background
The copper electrolysis process is characterized in that crude copper is made into a thick plate as an anode, pure copper or stainless steel is made into a thin plate as a cathode, the thick plate and the pure copper or the stainless steel are alternately inserted into electrolyte, after the anode is electrified, the anode in a tank is dissolved, anode copper enters the electrolyte in an ion form and is diffused to the cathode, electrons are obtained at the cathode to be separated out, and high-purity metal copper is obtained. The pole plates are prone to 'cold plate' and 'short circuit' during the copper electrolysis process. The cold plate is called as a cold plate, because the contact of the polar plate fails due to the reasons of plate arrangement error of workers, pollution of the conductive bars of the electrolytic cell and the like, no current or small current passes through the electrolytic cell, and the working efficiency of electrolysis is reduced; the nodulation of the cathode plate grows due to uneven current distribution between the plates, adhesion of anode mud and the like, and anode-cathode short circuit is caused. The short-circuit electrode not only stops electrolysis, a large amount of current flows through the short-circuit electrode to generate heat, the current is consumed in a heat form, the energy consumption is increased, and meanwhile, the current efficiency is reduced, but also the cathode copper grade is seriously influenced. The timely discovery and elimination of the faults of the electrode plates in the electrolytic cell are key work of cell surface management, and have important economic and technological meanings.
In the copper electrolysis process, the electrolytic cell is typically covered with a blanket to reduce heat and acid loss due to evaporation of the electrolyte. The infrared images of the inner cover cloth area and the exposed area of the electrolytic cell groove have obvious difference. Based on the method, a doctor academic paper of Beijing university of science and technology, namely the research on detecting the state of the copper electrolytic refining process based on infrared images, discloses a method for extracting fault cathodes in a cover cloth area and a bare area respectively, and the fault false detection rate of the cover cloth area is high. The article considers false detection and missed detection caused by crown block blocking, influence of groove surface operators, non-standard covering cloth and limitation of the algorithm. In order to further improve the fault detection index, a fault cathode extraction method based on SVM and suitable for a covering cloth area and an exposed area is constructed, although the fault detection rate of the latter is up to 99%, the false detection and the missing detection caused by the conditions that a truss vehicle is shielded and blocked, a tank surface operator enters an image picture and the like cannot be avoided.
Disclosure of Invention
The invention aims to provide an infrared image validity judgment method for electrolytic bath polar plate detection, which can improve the accuracy of fault polar plate detection.
In order to realize the purpose, the invention adopts the technical scheme that: an infrared image validity judgment method for electrolytic bath polar plate detection comprises the following steps:
A. acquiring an electrolytic cell image with a picture of an area in a single electrolytic cell;
B. dividing the image of the electrolytic bath into a quasi-drape area and/or a quasi-bare area;
C. and respectively identifying the validity of each area.
Compared with the prior art, the invention has the following technical effects: and based on the covering cloth on the electrolytic bath and the judgment of the covering cloth on the electrolytic bath, the effectiveness of the covering cloth and the exposed area is respectively judged, so that the reliability of the image effectiveness identification can be ensured. When the device is used, the invalid pictures are removed before the analysis of the fault polar plate is carried out, so that fault false detection and missing detection caused by shielding of foreign matters can be avoided.
Drawings
The contents of the description and the references in the drawings are briefly described as follows:
the contents of the description and the references in the drawings are briefly described as follows:
FIG. 1 is a schematic illustration of a standard image;
FIG. 2 is a schematic view of a test image;
FIG. 3 is a schematic diagram of a calibration standard image of an electrolytic cell and an electrolytic cell image;
FIG. 4 is a schematic view of detecting the edge line of the image temperature region of the electrolytic bath;
FIG. 5 is a schematic view of detecting the high and low temperature regions of the image of the electrolytic cell;
FIG. 6 is a schematic diagram of the division of the quasi-drape area and the quasi-exposed area in FIG. 5;
FIG. 7 is a schematic illustration of verifying the validity of an image of an electrolytic cell;
FIG. 8 is a sample of a valid image;
FIG. 9 is an invalid image sample;
FIG. 10 is a schematic diagram of an analysis block;
FIG. 11 is a schematic diagram of a block to be analyzed;
FIG. 12 is an example of an original thermographic image;
FIG. 13 is an example of a thermographic image resulting from a pseudo-normal tile stitching;
FIG. 14 is an example of a cell image with a faulty plate;
fig. 15 is an example of the temperature characteristic curve of fig. 14.
In the figure: 10. the method comprises the steps of a standard image, 11 positioning anchor frames, 12 corner points, 14 electrolytic cell correction standard images, 15 analysis image blocks, 20 detection images, 21 correction images, 22 electrolytic cell images, 221 to-be-analyzed areas, 23 to-be-analyzed image blocks, 23a current image block, 23b adjacent image blocks, 24 to-be-normal image blocks, 31 to-be-covered cloth areas, 32 to-be-exposed areas and 33 to temperature area edge lines.
Detailed Description
The following description of the embodiments of the present invention will be made in detail with reference to the accompanying drawings.
An infrared image validity judging method for electrolytic bath polar plate detection,
A. acquiring an electrolytic cell image 22 with a picture of an area in a single electrolytic cell;
B. dividing the electrolyzer image 22 into a quasi-drape area 31 and/or a quasi-bare area 32;
C. and respectively identifying the validity of each area.
Dividing the electrolytic cell image 22 into a quasi-covering cloth area 31 and/or a quasi-exposed area 32, and respectively judging the effectiveness of the quasi-covering cloth area 31 and the quasi-exposed area 32; the electrolytic bath image 22 is judged to be an effective image if and only if each area of the electrolytic bath image 22 is an effective image area.
Furthermore, in order to avoid the false judgment of the image validity caused by the shielding of the pseudo-cover cloth area 31 or the pseudo-exposed area 32 by the foreign matter and influence the accuracy of the fault detection, when the pseudo-cover cloth area 31 and the pseudo-exposed area 32 of the electrolyzer image 22 are both valid image areas, the validity of the electrolyzer image 22 is verified. Dividing the electrolytic bath image 22 into a plurality of areas 221 to be analyzed, and respectively judging the effectiveness of each area 221 to be analyzed; the electrolytic bath image 22 is judged to be an effective image if and only if each of the areas to be analyzed 221 is an effective image area. After the electrolytic bath image 22 is divided into the area to be analyzed 221 with a smaller picture, the validity of the image in the electrolytic bath image is verified based on the validity verification model.
The image validity judging method of the first embodiment is as follows:
k1, manually selecting an image of the electrolytic cell without shielding and an image of the electrolytic cell with shielding for analysis, and extracting a threshold value of effectiveness judgment characteristics.
K2, manually selecting an image of the electrolytic cell without shielding and an image of the electrolytic cell with shielding for training, and constructing an effectiveness verification model, wherein each sample corresponds to a four-dimensional feature vector F.
A. Acquiring an electrolytic cell image 22 with a picture of an area in a single electrolytic cell;
B. the electrolyzer image 22 is divided into a pseudo-drape area 31 and/or a pseudo-bare area 32.
Whether the electrolytic bath image 22 has a high temperature area and a low temperature area which extend along the length direction of the image is distinguished, the high temperature area is divided into a quasi-covering cloth area 31, the low temperature area is divided into a quasi-exposed area 32,
if there are no obvious high and low temperature areas, the electrolytic cell image 22 is seen to have an exposed area 32.
C. And respectively identifying the validity of each area.
And respectively calculating the temperature characteristic value of the quasi-covering cloth area 31 and/or the quasi-exposed area 32, and if the temperature characteristic value of the quasi-covering cloth area 31 is consistent with the characteristic threshold range of the covering cloth area and the temperature characteristic value of the quasi-exposed area 32 is consistent with the characteristic threshold range of the exposed area, judging the electrolytic bath image 22 to be an effective image.
In this embodiment, the temperature characteristic values are a temperature mean value and a temperature distribution standard deviation in the region. In step K1, the temperature mean value range and the temperature distribution standard deviation range of the drape area and the exposed area are extracted as validity judgment feature thresholds. In step K2, the four-dimensional feature vector F ═ m1，m2， d1，d2]TWherein m is1Is the mean temperature of the drape area; m is2Mean temperature of the bare area, d1Is the standard deviation of the temperature distribution of the drape area, d2The standard deviation of the temperature distribution of the bare area.
In the step C, the temperature characteristic value includes a temperature mean value m of the drape-simulating area 311'; is the mean value m of the temperature of the pseudo-exposed area 322’，d1Is the standard deviation d of the temperature distribution of the pseudo-drape area 311', is the standard deviation d of the temperature distribution of the region 32 to be exposed2’。
In other embodiments, other temperature parameters may be selected as the temperature characteristic value according to the requirement.
The second embodiment is different from the first embodiment in that:
in the step C, when all the areas are effective image areas, the effectiveness of the electrolytic cell image 22 is verified; otherwise, the current cell image 22 is judged to be an invalid image.
Specifically, in the step C, the temperature characteristic values of the quasi-drape area 31 and/or the quasi-exposed area 32 are/is respectively calculated, and if the temperature characteristic value of the quasi-drape area 31 is consistent with the drape area characteristic threshold range and the temperature characteristic value of the quasi-exposed area 32 is consistent with the exposed area characteristic threshold range, the step D is performed to verify the validity of the electrolyzer image 22.
The step D includes the steps of,
d1, dividing the electrolytic bath image 22 into at least 4 areas 221 to be analyzed in a checkerboard mode, and respectively calculating the temperature characteristic value of each area 221 to be analyzed;
d2, inputting the characteristic value of each area 221 to be analyzed into the validity verification model to obtain the image validity result corresponding to the area 221 to be analyzed,
if all the areas 221 to be analyzed are effective image areas, judging the current electrolytic bath image 22 to be an effective image;
if any one of the areas 221 to be analyzed is an invalid image area, the current electrolytic tank image 22 is judged to be an invalid image.
The third embodiment is different from the first embodiment in that:
the step B comprises the following steps of,
b1, detecting the temperature area edge line 33 in the electrolytic bath image 22;
b2, detecting whether the electrolytic bath image 22 has a high-temperature area and a low-temperature area;
if a high-temperature region and a low-temperature region exist in the electrolytic bath image 22, and the separation line of the two regions coincides with the temperature region edge line 33 extending in the image length direction in the step B1, dividing the electrolytic bath image 22 into the drape-like region 31 and the bare-like region 32 by taking the temperature region edge line 33 as a boundary;
if only one temperature area exists in the electrolytic bath image 22, the pictures of the electrolytic bath image 22 are all drawn as the bared areas 32.
The electrolytic cell fault polar plate detection method applying the image validity judgment method comprises the following steps:
step 1, acquiring and calibrating a standard image 10;
acquiring a standard image 10 at a preset position by a thermal imager;
step 1.1, manually calibrating a positioning anchor frame 11 in the standard image 10, wherein the frame area of the positioning anchor frame 11 comprises an image of an anchoring object, and the anchoring object is fixedly installed and is wholly or partially positioned on the outer side of the edge of the electrolytic tank opening.
Step 1.2, manually calibrating the angular points 12 of the electrolytic cells in the standard image 10, and simultaneously calibrating the number of the pole plates in each electrolytic cell.
Step 1.1 and step 1.2 can be performed simultaneously.
Step 1.31, obtaining a validity judgment feature threshold;
manually selecting an image of the electrolytic cell without shielding and an image of the electrolytic cell with shielding for analysis, and extracting the temperature mean value range and the temperature distribution standard deviation range of the covering cloth area and the exposed area as characteristic threshold value ranges.
The images for marking training should include images of the electrolytic cell different from the thermal imager in distance and proximity, including images of the electrolytic cell without shielding and images of the electrolytic cell with shielding, wherein the images of the electrolytic cell with shielding should include the conditions of covering cloth shielding, truss vehicle shielding, operator shielding and the like, and the shielding ranges are different.
Step 1.32, establishing an effectiveness verification model;
manually selecting an image without the shielding of the electrolytic cell and an image with the shielding of the electrolytic cell for training, constructing an effectiveness verification model, wherein each sample corresponds to a four-dimensional characteristic vector F,
F＝[m1，m2，d1，d2]T
m1is the mean temperature of the drape area; m is2Mean temperature of the bare area, d1Is the standard deviation of the temperature distribution of the drape area, d2The standard deviation of the temperature distribution of the bare area.
In this embodiment, the temperature characteristic values used for determining the effectiveness of the image are the temperature mean value and the temperature distribution standard deviation in each region. In other embodiments, other temperature parameters may be selected as the temperature characteristic value according to the requirement.
Step 2, obtaining a detection image 20, and obtaining an electrolytic bath image 22 based on calibration information;
and (3) during detection operation, adjusting the thermal imager to the preset position in the step (1), and acquiring to obtain a detection image 20.
And 2.1, respectively calculating the brightness distribution maps of the detected image 20 and the standard image 10, respectively calculating the enhancement coefficients according to the brightness distribution maps of the detected image and the standard image, and respectively carrying out image enhancement processing on the two images based on the enhancement coefficients. Namely, during the detection operation, the standard image 10 saved in the step 1 and the newly acquired detection image 20 are processed simultaneously, so that two images with more similar brightness distribution after contrast enhancement can be obtained, and the reliability of registration of the two images is ensured.
Step 2.2, registering the detection image 20 and the standard image 10 according to the calibration information to obtain a corrected image 21;
and respectively analyzing and matching the images in the frame areas of the positioning anchor frames 11 in the detection image 20 and the standard image 10 to generate projective transformation matrixes, and generating a correction image 21 by the detection image 20 according to the projective transformation matrixes. The detection image 20 is shifted, rotated or scaled according to the projective transformation matrix, and then the deviation between the two is eliminated to obtain a corrected image 21.
Step 2.3, processing the corrected image 21 based on the calibration information to obtain an electrolytic cell image 22;
the corrected images 21 are cut along the connecting lines of the adjacent corner points 12 of the same electrolytic cell to obtain the original images of the electrolytic cell, and the original images of each electrolytic cell are corrected to obtain rectangular electrolytic cell images 22 shown in the attached figure 3.
Step 3, judging the effectiveness of the electrolytic bath image 22;
step 3.1, detecting a temperature area edge line 33 in the electrolytic bath image 22;
the edge lines include lines extending in the length direction and in the width direction of the image, and as shown in FIG. 4, the transversely extending temperature zone edge lines 33 divide the cell image 22 into 3 zones from top to bottom. Typically, the temperature zone edge lines 33, which extend in the image width direction, i.e., vertically arranged, are the outline of the bare zone plates.
Step 3.2, detecting whether a high-temperature area and a low-temperature area exist in the electrolytic bath image 22;
if a high temperature region and a low temperature region exist in the electrolytic cell image 22, and the separation line of the two regions coincides with the temperature region edge line 33 extending along the length direction of the image in step 3.1, the electrolytic cell image 22 is divided into the quasi-drape region 31 and the quasi-exposed region 32 by taking the temperature region edge line 33 as the boundary. Wherein the high temperature area is a quasi-drape area 31, and the low temperature area is a quasi-exposed area 32.
If only one temperature area exists in the electrolytic bath image 22, the pictures of the electrolytic bath image 22 are all drawn as the bared areas 32.
For example, when the grayscale histogram of the electrolyzer image 22 is used to analyze the high and low temperature regions, if there are two large peaks in the grayscale histogram, the two large peaks can be divided into the quasi-drape region 31 and the quasi-exposure region 32, and if there is only one large peak in the grayscale histogram, the electrolyzer image 22 is considered to have only the quasi-exposure region 32.
3.3, respectively identifying the validity of each area;
and (3) respectively calculating the temperature characteristic values of the quasi-covering cloth area 31 and/or the quasi-exposed area 32, and if the temperature characteristic value of the quasi-covering cloth area 31 is consistent with the characteristic threshold range of the covering cloth area and the temperature characteristic value of the quasi-exposed area 32 is consistent with the characteristic threshold range of the exposed area, namely when all the areas are effective image areas, entering step 3.4.
Otherwise, the current cell image 22 is judged to be an invalid image.
Step 3.4, verifying the validity of the electrolytic cell image 22 by using a detection model;
step 3.41, dividing the electrolytic bath image 22 into at least 4 areas 221 to be analyzed in a checkerboard manner, and respectively calculating the temperature characteristic value of each area 221 to be analyzed;
the temperature characteristic value comprises a mean value m of the temperature of the drape-simulating region 311'; is the mean value m of the temperature of the pseudo-exposed area 322’，d1Is the standard deviation d of the temperature distribution of the pseudo-drape area 311', is the standard deviation d of the temperature distribution of the region 32 to be exposed2’。
As shown in FIG. 7, the cell image 22 was divided into 8 regions to be analyzed 221. In other embodiments, the cell image 22 may be divided into a plurality of regions to be analyzed 221 having the same size.
And 3.42, inputting the temperature characteristic values of the areas 221 to be analyzed into the validity verification model to obtain the image validity results corresponding to the areas 221 to be analyzed, and if any area 221 to be analyzed is invalid, judging that the current electrolytic tank image 22 is an invalid image.
In this embodiment, the validity verification model is a classification model based on an SVM.
And 4, analyzing the effective electrolytic tank image 22, judging whether the corresponding electrolytic tank has a fault polar plate or not and positioning the fault polar plate.
Step 4.1, dividing the electrolytic bath image 22 into a plurality of blocks 23 to be analyzed;
according to the size of the electrolytic bath image 22 and the number of the electrolytic bath pole plates marked in the step 1, the size of the blocks 23 to be analyzed is determined, and the electrolytic bath image 22 is divided or divided into a plurality of blocks 23 to be analyzed.
Step 4.2, calculating to obtain a simulated normal block 24 in the step 1 of the current block 23 according to the temperature information in the step 2 of the adjacent block 23, wherein the simulated normal block 24 is a characteristic block when the polar plate in the current block is in a normal working state;
calculating a simulated normal block 24 in the step 1 of the current block 23 according to the temperature information in the step 2 of the adjacent block 23, wherein the simulated normal block 24 is a characteristic block when the polar plate in the current block is in a normal working state;
the temperature information comprises temperature distribution, longitudinal temperature gradient distribution and transverse temperature gradient distribution information of the block 23 to be analyzed;
the temperature information of n adjacent image blocks 23b positioned at two sides of the current image block 23a is used for fitting a designed normal image block 24 of the current image block 23a, wherein n is more than or equal to 2,
if the number of the blocks 23 to be analyzed on one side of the current block 23a is less than n, adding the blocks 23 to be analyzed on the other side, and making the number of the adjacent blocks 23b for fitting be 2 n;
and 4.3, comparing the fault temperature characteristic values of each block 23 to be analyzed and the block 24 to be normal, and judging whether a fault polar plate exists in the block.
The fault temperature characteristic value comprises a fault temperature characteristic value of an exposed area in an image block and a fault temperature characteristic value of a covering cloth area; the fault temperature characteristic value TFault of＝TExposed part×a+TCovering cloth，
TExposed partThe fault temperature characteristic value of the exposed area is the difference value of the maximum temperature value of the current block 23a and the maximum temperature value of the adjacent block 23 b;
Tcovering clothThe characteristic value of the fault temperature of the covering cloth area is the length value of the high-temperature area of the current image block 23a in the length direction of the image block;
a is an amplification factor of the fault temperature characteristic value of the exposed area and is a constant.
If the difference value of the fault temperature characteristic value of the block 23 to be analyzed and the block 24 to be simulated as normal is within the limited threshold value, the block 23 to be analyzed is determined as a normal working plate,
if the difference value of the fault temperature characteristic values of the two exceeds the limited threshold value, the fault pole plate is judged to exist in the block 23 to be analyzed, and the fault pole plate information is recorded and uploaded in the step 5.
And 5, outputting a detection result and finishing the detection.
Claims (9)
1. An infrared image validity judgment method for electrolytic cell polar plate detection comprises the following steps:
A. acquiring an electrolytic cell image (22) with a picture of an area in a single electrolytic cell;
B. dividing the electrolyzer image (22) into a quasi-drape area (31) and/or a quasi-bare area (32);
C. and respectively identifying the validity of each area.
2. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 1, characterized in that: in the step B, whether the electrolytic bath image (22) has a high-temperature area and a low-temperature area which extend along the length direction of the image is distinguished, the high-temperature area is divided into a quasi-covering cloth area (31), the low-temperature area is divided into a quasi-exposed area (32),
if no obvious high-temperature and low-temperature areas exist, the electrolytic cell image (22) is seen to be an exposed area (32).
3. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 2, characterized in that: the step B comprises the following steps of,
b1, detecting a temperature area edge line (33) in the electrolytic bath image (22);
b2, detecting whether the electrolytic bath image (22) has a high-temperature region and a low-temperature region;
if a high-temperature area and a low-temperature area exist in the electrolytic bath image (22), and the separation line of the two areas is consistent with the temperature area edge line (33) extending along the length direction of the image in the step B1, dividing the electrolytic bath image (22) into a quasi-drape area (31) and a quasi-exposed area (32) by taking the temperature area edge line (33) as a boundary;
if only one temperature area exists in the electrolytic tank image (22), the picture of the electrolytic tank image (22) is divided into the to-be-exposed area (32).
4. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 1, characterized in that: and in the step C, respectively calculating the temperature characteristic value of the quasi-cover cloth area (31) and/or the quasi-exposed area (32), and if the temperature characteristic value of the quasi-cover cloth area (31) is consistent with the cover cloth area characteristic threshold range and the temperature characteristic value of the quasi-exposed area (32) is consistent with the exposed area characteristic threshold range, judging that the electrolytic bath image (22) is an effective image.
5. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 1, characterized in that: in the step C, when all the areas are effective image areas, verifying the effectiveness of the electrolytic cell image (22); otherwise, judging the current electrolytic tank image (22) as an invalid image.
6. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 5, characterized in that: in the step C, the temperature characteristic values of the drape-simulating area (31) and/or the bare-simulating area (32) are respectively calculated,
and D, if the temperature characteristic value of the quasi-cover cloth area (31) is consistent with the characteristic threshold range of the cover cloth area and the temperature characteristic value of the quasi-exposed area (32) is consistent with the characteristic threshold range of the exposed area, entering the step D, and verifying the validity of the electrolytic cell image (22).
7. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 6, characterized in that: and step K, manually selecting an image without the electrolytic cell and an image with the electrolytic cell shielded for analysis, and extracting an effectiveness judgment characteristic threshold value.
8. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 7, characterized in that: the temperature characteristic value is a temperature mean value and a temperature distribution standard deviation in the area; in the step C, the temperature characteristic value comprises a temperature mean value m of the drape-simulating area (31)1'; is the mean value m of the temperature of the area (32) to be exposed2’，d1Is the standard deviation d of the temperature distribution of the pseudo-cover cloth area (31)1', is the standard deviation d of the temperature distribution of the region (32) to be exposed2’；
And step K, extracting the temperature mean value range and the temperature distribution standard deviation range of the covering cloth area and the exposed area as validity judgment characteristic threshold values.
9. The infrared image validity judgment method for electrolytic bath pole plate detection according to claim 7, characterized in that: in the step K, manually selecting an image without the shielding of the electrolytic cell and an image with the shielding of the electrolytic cell for training, constructing an effectiveness verification model, wherein each sample corresponds to a four-dimensional characteristic vector F,
F＝[m1，m2，d1，d2]T
m1is the mean temperature of the drape area; m is2Mean temperature of the bare area, d1Is the standard deviation of the temperature distribution of the drape area, d2The standard deviation of the temperature distribution of the bare area;
the step D includes the steps of,
d1, dividing the electrolytic bath image (22) into at least 4 areas (221) to be analyzed in a checkerboard mode, and respectively calculating the temperature characteristic value of each area (221) to be analyzed;
d2, inputting the characteristic value of each region (221) to be analyzed into the validity verification model to obtain the image validity result corresponding to the region (221) to be analyzed,
if all the areas (221) to be analyzed are effective image areas, judging the current electrolytic bath image (22) to be an effective image;
if any one of the areas (221) to be analyzed is an invalid image area, the current electrolytic tank image (22) is judged to be an invalid image.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110731906.0A CN113344908A (en) | 2021-06-30 | 2021-06-30 | Infrared image validity judgment method for electrolytic cell polar plate detection |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110731906.0A CN113344908A (en) | 2021-06-30 | 2021-06-30 | Infrared image validity judgment method for electrolytic cell polar plate detection |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113344908A true CN113344908A (en) | 2021-09-03 |
Family
ID=77481827
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110731906.0A Pending CN113344908A (en) | 2021-06-30 | 2021-06-30 | Infrared image validity judgment method for electrolytic cell polar plate detection |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113344908A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024045428A1 (en) * | 2022-08-29 | 2024-03-07 | 合肥金星智控科技股份有限公司 | Detection method and apparatus for electrolytic polar plate, and electronic device and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140203815A1 (en) * | 2011-09-12 | 2014-07-24 | Sharp Kabushiki Kaisha | Wiring fault detection method and wiring fault detection apparatus |
| CN107578433A (en) * | 2017-08-17 | 2018-01-12 | 中南大学 | A kind of method for identifying electrolytic bath electrode plate temperature |
| CN107767360A (en) * | 2017-08-17 | 2018-03-06 | 中南大学 | A kind of method for early warning and detection means for electrolytic bath electrode plate failure |
| CN109402667A (en) * | 2018-12-20 | 2019-03-01 | 昆明理工大学 | A kind of device and method improving cupric electrolysis pole plate fault message accuracy of judgement degree |
| CN111321429A (en) * | 2019-05-13 | 2020-06-23 | 杭州海康威视***技术有限公司 | Method and device for detecting temperature of electrode plate of electrolytic cell |
-
2021
- 2021-06-30 CN CN202110731906.0A patent/CN113344908A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140203815A1 (en) * | 2011-09-12 | 2014-07-24 | Sharp Kabushiki Kaisha | Wiring fault detection method and wiring fault detection apparatus |
| CN107578433A (en) * | 2017-08-17 | 2018-01-12 | 中南大学 | A kind of method for identifying electrolytic bath electrode plate temperature |
| CN107767360A (en) * | 2017-08-17 | 2018-03-06 | 中南大学 | A kind of method for early warning and detection means for electrolytic bath electrode plate failure |
| CN109402667A (en) * | 2018-12-20 | 2019-03-01 | 昆明理工大学 | A kind of device and method improving cupric electrolysis pole plate fault message accuracy of judgement degree |
| CN111321429A (en) * | 2019-05-13 | 2020-06-23 | 杭州海康威视***技术有限公司 | Method and device for detecting temperature of electrode plate of electrolytic cell |
Non-Patent Citations (2)
| Title |
|---|
| 王一丁;贺文强;贾瑞明;: "铜电解槽极板短路红外检测***", 现代计算机(专业版), no. 15, 25 May 2016 (2016-05-25), pages 1 - 6 * |
| 王一丁;马晓蕾;贺文强;: "基于红外图像的铜电解短路检测", 北方工业大学学报, no. 03, 15 September 2016 (2016-09-15), pages 1 - 5 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2024045428A1 (en) * | 2022-08-29 | 2024-03-07 | 合肥金星智控科技股份有限公司 | Detection method and apparatus for electrolytic polar plate, and electronic device and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113549958B (en) | Method for detecting fault polar plate of electrolytic cell | |
| CN113313677B (en) | Quality detection method for X-ray image of wound lithium battery | |
| CN112381796B (en) | Wire defect identification and detection method based on infrared data | |
| CN106680285A (en) | Infrared image-assisted method of recognizing contamination condition of insulator by visible light image | |
| CN112577421A (en) | Battery cell detection method, device and equipment | |
| CN113344908A (en) | Infrared image validity judgment method for electrolytic cell polar plate detection | |
| CN107578433A (en) | A kind of method for identifying electrolytic bath electrode plate temperature | |
| CN115049645B (en) | Solar cell panel surface defect detection method | |
| CN103925893A (en) | Quality detection method of battery cells | |
| CN113554601B (en) | Positioning method of electrolytic tank polar plate | |
| CN115790859A (en) | Abnormal electrolysis condition identification method | |
| CN110132978A (en) | Resistor disc full wafer detection device and detection method | |
| CN114581446B (en) | Battery core abnormity detection method and system of laminated battery | |
| Liu et al. | An automatic defects detection scheme for lithium-ion battery electrode surface | |
| CN110363749A (en) | Stockbridge damper corrosion degree evaluation method based on image procossing | |
| CN113554600B (en) | Method for detecting electrolytic tank polar plate based on infrared image | |
| CN113554600A (en) | Electrolytic cell polar plate detection method based on infrared image | |
| CN112113667B (en) | Current transformer fault diagnosis method based on infrared thermal image information | |
| CN115115630B (en) | Detection method, detection device, electronic device, and storage medium | |
| US20040173453A1 (en) | Method for improving the quality of cathodes in electrolysis | |
| CN111553376B (en) | Cultural relic contour monitoring method | |
| CN113362275A (en) | Electrolytic tank fault polar plate identification method | |
| CN114841971A (en) | Method, system and device for detecting pit defects of metal block | |
| CN109885029B (en) | Electric smelting magnesium oxide process fault detection method based on projection non-negative matrix decomposition | |
| Jia et al. | Infrared short-circuit detection for electrolytic copper refining |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| CB02 | Change of applicant information | ||
| CB02 | Change of applicant information |
Address after: No. 228, Wanshui Road, high tech Zone, Hefei City, Anhui Province, 230088 Applicant after: Hefei Jinxing Intelligent Control Technology Co.,Ltd. Applicant after: Tongling Nonferrous Metals Group Co., Ltd Address before: No. 228, Wanshui Road, high tech Zone, Hefei City, Anhui Province, 230088 Applicant before: HEFEI GOLD STAR MECHATRONICS TECHNICAL DEVELOPMENT Co.,Ltd. Applicant before: Tongling Nonferrous Metals Group Co., Ltd |