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CN-121994645-A - Positioning method, device, storage medium and equipment for poor coating material area

CN121994645ACN 121994645 ACN121994645 ACN 121994645ACN-121994645-A

Abstract

The invention discloses a positioning method, a positioning device, a storage medium and positioning equipment for a poor coating material area, and belongs to the technical field of lithium ion battery production. The method comprises the steps of collecting coating surface density data in real time, extracting material area data from the coating surface density data collected in real time, identifying the edge of a material area according to preset coating surface density process parameters, obtaining the range of the material area, calculating the sequence of bad points of the edge of the material area beyond a normal range according to a set surface density process parameter threshold value, and calculating the transverse and longitudinal coordinate positions of the bad data points on a coating material by analyzing the sequence of the bad points and the sequence of data operation encoder points and detection points to obtain two-dimensional coordinate information of a bad area.

Inventors

  • LI SHAN

Assignees

  • 合肥国轩高科动力能源有限公司

Dates

Publication Date
20260508
Application Date
20260120

Claims (10)

  1. 1. A method of locating a defective area of coating, the method comprising: Collecting density data of a coating surface in real time; extracting material area data from the real-time acquired coating surface density data, and identifying the edge of the material area according to preset coating surface density process parameters to obtain the material area range; According to the set surface density process parameter threshold, calculating the bad number point sequence of the edge of the material area beyond the normal range; And calculating the transverse coordinate position and the longitudinal coordinate position of the defective data point on the coating material by analyzing the defective number point sequence and the data operation encoder point and detection point sequence, so as to obtain the two-dimensional coordinate information of the defective area.
  2. 2. The method for locating a defective coating area according to claim 1, wherein the collected surface density data of the coating is collected in real time by a direct connection detecting instrument, and a locally stored CSV log file is used as a standby data source.
  3. 3. The method of claim 1, wherein the coating area density process parameters include: A material zone transition point threshold W, a material zone advancing value P, a surface density maximum allowable value max, a surface density minimum allowable value min, a material zone quantity n and a total material web quantity m; the technological parameters are respectively and independently configured for single-sided coating and double-sided coating, wherein the parameter field structures are the same.
  4. 4. The method of claim 1, wherein the detection data is an array data Q of Q data points collected each time, each data point corresponds to an areal density detection value of 0.5-1mm width, and Q is the number of data points collected.
  5. 5. The method of claim 4, wherein identifying the edge of the material region and obtaining the material region range comprises: Traversing the detection data array data [ Q ] to find a data interval with continuous values larger than a material region transition point threshold W; for each continuous interval, the leftmost data point meeting the condition is taken to be right-pushed by P data points to be used as a left edge Lx of the material area, and the rightmost data point meeting the condition is taken to be left-pushed by P data points to be used as a right edge Rx of the material area.
  6. 6. The method for positioning a defective coating material according to claim 1, wherein the calculating the defective number point order of the edge of the material beyond the normal range includes: Extracting data of each group of material areas of data [ Q ], wherein left material areas Ld1, ld2, ld 3..Lda, right material areas Rd1, rd2, rd3.. Rda, equally dividing the material area array into n sections, and obtaining each section array of Ld1_1, ld1_2, ld 1_3..Ld1_n; ld2_1, ld2_2, ld2_3..Ld2_n; ld2_2, ld2_3. Ld2_n; calculating the average value Dm of each interval, comparing the threshold value of the standard surface density, and when the surface density max is more than or equal to Dm > surface density min, indicating normal and other defects, thereby obtaining the index value Lda_n or Rda _n of the defective points to obtain the sequence of the defective points, wherein Q is the number of the collected data points.
  7. 7. The method of claim 1, wherein calculating the lateral and longitudinal coordinate positions of the defective data points on the coating material comprises: When the detection direction D is forward: the longitudinal coordinate Y is calculated according to the formula: Y = P*△m - (T / Q) × (Q - Lda_n) × V; the transverse coordinate is Lda_n, and the unit is mm; Outputting bad point coordinates as (Y, lda_n); When the detection direction D is reverse: the longitudinal coordinate Y is calculated according to the formula: Y = P*△m - (T / Q) × Rda_n × V; the transverse coordinate is Rda _n, and the unit is mm; outputting bad point coordinates as (Y, rda _n); wherein P is the current value of the PLC encoder, deltam is the moving distance of the encoder value, m and T are the detection period, s is the running speed, m/s is the unit, rda _n and Lda_n are the position indexes of bad data points in the detection width direction, and Q is the number of the acquired data points.
  8. 8. A positioning device for a defective coating area, the device comprising: The data acquisition module is configured to acquire the coating surface density data in real time; the material area identification module is configured to extract material area data from the real-time acquired coating surface density data, and identify the edge of the material area according to preset coating surface density process parameters to obtain the range of the material area; the calculating module is configured to calculate the bad number point sequence of the edge of the material area beyond the normal range according to the set surface density process parameter threshold; And the coordinate calculation module is configured to calculate the transverse and longitudinal coordinate positions of the bad data points on the coating material by analyzing the bad data point sequence and the data operation encoder point and detection point sequence, so as to obtain the two-dimensional coordinate information of the bad area.
  9. 9. A computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 7.
  10. 10. An electronic device comprising a processor and a memory, wherein the memory has stored therein an executable program, which when executed by the processor implements the method of any of claims 1 to 7.

Description

Positioning method, device, storage medium and equipment for poor coating material area Technical Field The invention relates to a positioning method, a positioning device, a storage medium and positioning equipment for a poor coating material area, and belongs to the technical field of cell production. Background In existing coating process production, identification and localization of defective areas face a series of challenges, mainly manifested in the following aspects: firstly, the detection and positioning of the poor coating material area in the production of the battery cell have a plurality of defects in the common method. Some traditional manual detection methods rely on experience and visual judgment of workers, have low efficiency and are easy to cause the conditions of missed detection and misjudgment, and part of the existing automatic detection positioning technology still needs to be improved in detection precision and positioning accuracy, and cannot meet the increasingly strict production quality requirements. First, the detection accuracy is insufficient, and it is difficult to identify minute or hidden defects. The prior art (such as traditional visual detection and contact sensors) is limited by resolution and has insufficient recognition capability on coating defects (such as thickness deviation of extremely thin areas, tiny bubbles and shallow surface scratches). For example, when the coating thickness deviation is smaller than 5 μm, part of optical detection equipment may be missed due to low signal-to-noise ratio, and for bubbles embedded in the slurry or defects similar to the color of a substrate, the traditional vision algorithm is easy to generate 'misjudgment' or 'missed judgment', so that the bad material area is positioned inaccurately, and the defective battery cells flow into subsequent processes. Secondly, the real-time performance is poor, the coating process which cannot be matched with the high-speed production rhythm is usually carried out in a high-speed production line (such as the coating speed of tens of meters per minute), and if the off-line sampling inspection or the low-speed scanning inspection is adopted in the prior art, the full-width fabric belt is difficult to cover in real time. For example, a CCD camera detection system based on progressive scanning may cause image blurring due to insufficient frame rate under high-speed operation, or delay in data processing (such as excessively long time consumption of a defect analysis algorithm), so that a defective area cannot be marked in time in the moving process of a material belt, and finally, the defective material area is missed to be positioned, which affects on-line sorting efficiency. In addition, the compatibility is insufficient, and the method is difficult to adapt to multi-specification products and complex process scenes. The existing detection technology is designed for single product specification (such as pole pieces with fixed width and thickness), and when the product is changed (such as pole piece size and coating material change corresponding to different battery cell models), detection parameters (such as threshold setting and image recognition templates) need to be debugged again, so that time and labor are wasted. For example: When the coating material is changed from lithium iron phosphate to a ternary material, the color and surface texture difference of the slurry is obvious, the traditional template matching-based algorithm needs to be retrained, otherwise, the identification of a bad material area is failed due to the failure of feature extraction; For complex processes such as multilayer coating, special-shaped coating (such as edge margin and local thickening), the prior art lacks an adaptive adjustment mechanism, and is easy to generate excessive detection or detection blind areas, so that positioning deviation is caused. In view of the above, these problems of the conventional defective positioning in the coating process not only severely restrict the improvement of the coating yield but also increase the defective probability of the battery, and the problem is urgently needed to be solved by technical innovation. Disclosure of Invention The invention aims to overcome the defects of the prior art and provide a positioning method, a device, a storage medium and equipment for a poor coating material area, which can realize the real-time identification and positioning of poor coating by detecting the density of a coating surface in real time and configuring related process parameters, and bring remarkable and profound benefits for improving the quality of a battery cell. In order to achieve the above purpose/solve the above technical problems, the present invention is realized by adopting the following technical scheme: in a first aspect, a method for locating a defective coating area, the method comprising: Collecting density data of a coating surface in real time; extracting materi