CN117053687A - Cell height level difference detection method based on laser line scanning 3D camera - Google Patents
Cell height level difference detection method based on laser line scanning 3D camera Download PDFInfo
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Classifications
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/002—Measuring arrangements characterised by the use of optical techniques for measuring two or more coordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/02—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness
- G01B11/06—Measuring arrangements characterised by the use of optical techniques for measuring length, width or thickness for measuring thickness ; e.g. of sheet material
- G01B11/0608—Height gauges
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
Abstract
The application relates to the technical field of cell detection and discloses a cell height level difference detection method based on a laser line scanning 3D camera.
Description
Technical Field
The application relates to the technical field of battery cell detection, in particular to a battery cell height level difference detection method based on a laser line scanning 3D camera.
Background
As power cells develop, the assembly requirements are also becoming increasingly stringent. The battery cell is used as the minimum unit in the battery pack, and the battery pack cannot be used normally due to damage, so that the process quality of the battery cell directly influences the quality of the final product of the battery pack. The flatness and the height distance of the positive electrode and the negative electrode of the battery core are one of the important index data; in addition, the insulating film on the battery core is required to be detected whether to be correctly attached or not, so that the phenomena of short circuit and the like are prevented; meanwhile, the two-dimension code of the product on the battery core needs to be identified, so that tracking and tracing are facilitated. In the production line with high speed and full detection, the traditional manual detection is insufficient, the 3D camera is used for vision to replace manual measurement, and the flatness and the height level difference of the battery cell, the position measurement of the insulating film and the reading of the two-dimensional code can be realized.
Disclosure of Invention
The application aims to provide a cell height level difference detection method based on a laser line scanning 3D camera, so as to realize high-efficiency detection of a cell in a high-speed full-detection production line.
In order to achieve the above purpose, the present application discloses the following technical solutions:
a cell height level difference detection method based on a laser line scanning 3D camera comprises the following steps:
s101: collecting an image of the current core;
s102: converting the acquired image into a 3D depth map and a 2D gray map;
s103: establishing a standard template, calculating gradient values of the template edge points in the x and y directions, calculating gradient strength and gradient angles of the edge points according to data of the gradient values, traversing the edge points, storing x gradients and y gradients corresponding to the edge points, normalizing the gradient strength to obtain values in a 0-1 interval, and converting coordinates of the edge points into relative coordinates relative to a center;
s104: performing template matching on the 3D depth map and the 2D gray scale map in the region of interest, wherein the template matching specifically comprises the following steps: calculating gradient values of the edge points in the x and y directions, calculating gradient strength and gradient angle of the edge points according to data of the gradient values in the x and y directions, and calculating a score of correlation between template edge gradients and target image edge gradients through a normalized cross correlation algorithm, wherein the score range of the score is 0-1;
s105: placing a plurality of measuring points on the anode and the cathode of the battery core and the plane of the battery core respectively, and recording three-dimensional coordinate information of each measuring point;
s106: calculating the positive and negative electrodes of the battery cell and the optimal plane of the surface of the battery cell by using a least square method based on the three-dimensional coordinate information of the measuring points;
s107: respectively calculating the height values from the measurement points on the positive electrode and the negative electrode of the battery cell to the respective optimal planes;
s108: taking the calculated height value as the flatness, taking a least square plane of an actual measured surface as an evaluation reference plane, and taking the distance between two containing planes which are parallel to the least square plane and have the minimum distance as a flatness error value, wherein the least square plane is a plane which enables the square sum of the distances between each point on the actual measured surface and the plane to be minimum;
s109: comparing the flatness with corresponding preset upper and lower limit parameter values, if the result is within the upper and lower limit parameter ranges, the flatness of the anode and the cathode of the battery cell is qualified, otherwise, the flatness is not qualified, and the battery cell is recovered;
s110: calculating the distance between each measuring point on the positive electrode and the negative electrode of the battery cell and the optimal plane of the battery cell as a Height value, comparing the Height value corresponding to each measuring point with a corresponding preset upper and lower limit parameter value, and if the Height result is within the upper and lower limit parameter range, determining the positive electrode and the negative electrode of the battery cell as qualified, and continuing the next test; otherwise, the battery cell is unqualified and recovered;
s111: setting interested areas on the edges of the insulating film and the edges of the positive electrode and the negative electrode of the battery cell, fitting out a line segment through an edge finding tool, and taking the line segment as the line segment on the insulating film and the positive electrode and the negative electrode of the battery cell;
s112: obtaining a starting point, an ending point and a middle point of a line segment on the positive electrode and the negative electrode of the battery cell;
s113: calculating the distances from the starting point, the ending point and the middle point of the line segment on the positive electrode and the negative electrode of the battery cell to the line segment of the insulating film to obtain 3 Dis values respectively;
s114: respectively comparing the Dis value with corresponding preset upper and lower limit parameter values, if the result is within the upper and lower limit parameter ranges, the interval from the edge of the insulating film to the edge of the anode and the cathode is qualified, and continuing the next test; otherwise, the battery cell is unqualified and recovered;
s115: using a gray level diagram to read two-dimensional code information on the battery cell;
s116: the cell flows into the next process.
In one embodiment, the S101 specifically includes:
and (5) after clamping the battery cell, carrying out image acquisition on the battery cell.
In one embodiment, in S103, the template object in the standard template is composed of edge information of a template area.
In one embodiment, in the step S105, the distribution of the plurality of measurement points includes:
respectively placing 9 measuring points arranged according to 3*3 on the anode and cathode of the battery core, wherein the corresponding 9 measuring points cover the surfaces of the anode and the cathode respectively;
placing 30 measurement points arranged according to 3 x 10 on the plane of the battery cell, wherein the 30 measurement points cover the plane of the battery cell;
wherein the size of each point measurement point is a dot with a diameter of 3 pixels.
In one embodiment, in S107, the height value of the measurement point is obtained by calculation in a weighted average mode, and the weighted mode is an arithmetic average value, and when calculating, the height of each point is detected and averaged in a specified area range.
In one embodiment, in S111, the fitting line segment specifically includes:
randomly selecting two points from the point set, defining a straight line by the two points, and re-selecting the two points if the two points are too close to each other or the direction of the straight line deviates from the parameter-specified direction too much; calculating the distance between the line and all other points, selecting all points with the distance smaller than the abnormal value threshold value, and if the number of the points is larger than the minimum boundary percentage, replacing the origin set by the points;
using all points for the line estimation model;
calculating the vertical line distance from each point to the line, if the distance is greater than the current abnormal value threshold value, neglecting the line, and updating the abnormal value threshold value after each iteration; gradually amplifying the edge model attachment points, wherein other points are ignored as noise points or part of other edges; the iteration continues until either the maximum number of iterations is exceeded or the percentage of remaining points is less than the minimum number of retained iterations, the resulting line model will be returned as a result.
In one embodiment, the step S115 specifically includes:
and placing the region of interest in a two-dimensional code range on the battery cell, and using a two-dimensional code reading tool to read, record and store the two-dimensional code information of the battery cell. .
The beneficial effects are that: according to the battery cell height level difference detection method based on the laser line scanning 3D camera, the flatness of the positive electrode and the negative electrode on the battery cell and the height level difference relative to the plane of the battery cell are detected in real time through the 2D+3D visual detection system, the edge position spacing between the insulating film and the positive electrode and the negative electrode of the battery cell can be detected, and the two-dimensional code information on the battery cell is read, so that the process quality of the battery cell is guaranteed, the defects of low speed and poor accuracy of the conventional manual detection are well overcome, the time cost caused by manual detection is solved, and the production efficiency is improved.
Detailed Description
The following description of the technical solutions in the embodiments of the present application will be clear and complete, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
In the description of the present disclosure, it should be noted that the terms "center," "upper," "lower," "left," "right," and the like indicate an orientation or a positional relationship as shown, and are merely for convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the apparatus or element in question must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present disclosure. In this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
A cell height level difference detection method based on a laser line scanning 3D camera comprises the following steps:
s101: and when the image of the battery core is acquired, the battery core needs to be clamped so as to prevent shaking of a product and deformation of the image.
S102: and converting the acquired image into a 3D depth map and a 2D gray scale map.
( On the production line, the position of each detection of the battery cell has deviation, and the position of the battery cell needs to be accurately positioned in an image. Template localization is then required to achieve, i.e. template matching of the 3D depth map and the 2D gray map in the region of interest. )
S103: establishing a standard template, calculating gradient values of the template edge points in the x and y directions, calculating gradient strength and gradient angle of the edge points according to data of the gradient values, traversing the edge points, storing x gradients and y gradients corresponding to the edge points, normalizing the gradient strength (1 is divided by the gradient strength of the point, and the obtained values are all values in a [0,1] interval) to obtain values in a 0-1 interval, and converting the coordinates of the edge points into relative coordinates relative to the center.
S104: the template matching specifically comprises the following steps: calculating gradient values of the edge points in the x and y directions, calculating gradient strength and gradient angle of the edge points according to data of the gradient values in the x and y directions, and calculating a score of correlation between template edge gradients and target image edge gradients through a normalized cross correlation algorithm, wherein the score range of the score is 0-1.
( The interested region of the edge finding tool can follow the new coordinates to convert the new interested region position, so that the problem of inaccurate detection caused by the deviation of the cell position can be avoided. After the template positioning and matching are successful, the flatness of the positive electrode and the negative electrode on the battery core and the height level difference of the positive electrode and the negative electrode relative to the battery core plane are required to be detected in the next step. )
S105: and respectively placing a plurality of measuring points on the anode and the cathode of the battery cell and the plane of the battery cell, and recording three-dimensional coordinate information of each measuring point. The distribution of the dots is as follows: respectively placing 9 points on the anode and the cathode, and arranging 3*3 to cover the surfaces of the anode and the cathode as much as possible; on the plane of the cell, 30 points are placed, 3×10 are arranged to cover the cell plane as much as possible, and the measuring point is a round point with a diameter of 3 pixels.
S106: and calculating the positive and negative electrodes of the battery cell and the optimal plane of the surface of the battery cell by using a least square method based on the three-dimensional coordinate information of the measurement points.
S107: and respectively calculating the height values from the measurement points on the positive electrode and the negative electrode of the battery core to the respective optimal planes, wherein the height values of the measurement points are in a weighted average mode function, the weighted mode is an arithmetic average value, and the height of each point is detected and averaged in a specified area range.
S108: the calculated height value is taken as the flatness, the least square plane of the actual measured surface is taken as an evaluation reference plane, and the distance between two containing planes which are parallel to the least square plane and have the minimum distance is taken as the flatness error value, wherein the least square plane is the plane which enables the square sum of the distances between each point on the actual measured surface and the plane to be the minimum.
S109: and comparing the flatness with corresponding preset upper and lower limit parameter values, if the result is within the upper and lower limit parameter ranges, the flatness of the anode and the cathode of the battery cell is qualified, otherwise, the flatness is not qualified, and the battery cell is recovered.
S110: and calculating the distance between each measuring point on the anode and cathode of the battery cell and the best plane of the battery cell as a Height value, wherein the distance between the measuring points is a weighted average mode function, the weighted mode is an arithmetic average value, and the distance between each measuring point is detected and averaged in a specified area range. Comparing the Height value corresponding to each measuring point with corresponding preset upper and lower limit parameter values, if the Height result is within the upper and lower limit parameter range, the positive and negative heights of the battery cell are qualified, and continuing to perform the next test; otherwise, the battery core is recovered.
(next, the pitch of the edge of the insulating film to the edge of the positive electrode was detected.)
S111: and setting interested areas on the edges of the insulating film and the edges of the positive electrode and the negative electrode of the battery cell, fitting out a line segment through an edge finding tool, and taking the line segment as the line segment on the insulating film and the positive electrode and the negative electrode of the battery cell. The specific method for fitting the line segments is as follows: two points are randomly chosen from the set of points, with which a straight line is defined. If the two points are too close together, or the line direction deviates too much from the parameter-specified direction, the two points are reselected. The distances between the line and all other points are calculated and all points whose distances are less than the outlier threshold are selected, if the number of points is greater than the minimum boundary percentage, the origin set is replaced with these points and the fitting line is iterated using the least squares method. The points obtained above are used for the line estimation model. In subsequent iterations, the perpendicular distance from each point to the line is calculated. If the distance is greater than the current outlier threshold, the line is ignored. After each iteration, the outlier threshold is updated. We will gradually zoom in on edge model attachment points, other points being ignored as noise points or part of other edges. The iteration continues until either the maximum number of iterations is exceeded or the percentage of remaining points is less than the minimum number of retained iterations. When any of these conditions is met, the wire model (if the conditions are met) will be returned as a result, yielding wire segments on the insulating film and on the positive and negative electrodes of the cell.
S112: and obtaining the starting point, the end point and the middle point of the line segment on the positive electrode and the negative electrode of the battery cell.
S113: and calculating the distances from the starting point, the ending point and the middle point of the line segment on the positive electrode and the negative electrode of the battery cell to the line segment of the insulating film to obtain 3 Dis values respectively.
S114: respectively comparing the Dis value with corresponding preset upper and lower limit parameter values, if the result is within the upper and lower limit parameter ranges, the interval from the edge of the insulating film to the edge of the anode and the cathode is qualified, and continuing the next test; otherwise, the battery core is recovered.
(finally, using a gray scale, two-dimensional code information on the cell is read.)
S115: and using the gray level diagram to read the two-dimensional code information on the battery cell. The method specifically comprises the following steps: and (3) placing the range of the two-dimensional code of the region of interest on the battery cell, and using a two-dimensional code reading tool to read, record and store the two-dimensional code information of the battery cell.
S116: after the detection, the battery cell flows into the next working procedure.
In summary, according to the method for detecting the height level difference of the battery cell based on the laser scanning 3D camera of the embodiment, the flatness of the positive electrode and the negative electrode on the battery cell and the height level difference relative to the plane of the battery cell are detected in real time through the 2d+3d visual detection system, the edge position spacing between the insulating film and the positive electrode and the negative electrode of the battery cell can be detected, and the two-dimensional code information on the battery cell is read, so that the process quality of the battery cell is ensured, the defects of low speed and poor accuracy of the existing manual detection are well overcome, the time cost caused by manual work is solved, and the production efficiency is improved.
Finally, it should be noted that: the foregoing description is only illustrative of the preferred embodiments of the present application, and although the present application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described, or equivalents may be substituted for elements thereof, and any modifications, equivalents, improvements or changes may be made without departing from the spirit and principles of the present application.
Claims (7)
1. The battery cell height level difference detection method based on the laser line scanning 3D camera is characterized by comprising the following steps of:
s101: collecting an image of the current core;
s102: converting the acquired image into a 3D depth map and a 2D gray map;
s103: establishing a standard template, calculating gradient values of the template edge points in the x and y directions, calculating gradient strength and gradient angles of the edge points according to data of the gradient values, traversing the edge points, storing x gradients and y gradients corresponding to the edge points, normalizing the gradient strength to obtain values in a 0-1 interval, and converting coordinates of the edge points into relative coordinates relative to a center;
s104: performing template matching on the 3D depth map and the 2D gray scale map in the region of interest, wherein the template matching specifically comprises the following steps: calculating gradient values of the edge points in the x and y directions, calculating gradient strength and gradient angle of the edge points according to data of the gradient values in the x and y directions, and calculating a score of correlation between template edge gradients and target image edge gradients through a normalized cross correlation algorithm, wherein the score range of the score is 0-1;
s105: placing a plurality of measuring points on the anode and the cathode of the battery core and the plane of the battery core respectively, and recording three-dimensional coordinate information of each measuring point;
s106: calculating the positive and negative electrodes of the battery cell and the optimal plane of the surface of the battery cell by using a least square method based on the three-dimensional coordinate information of the measuring points;
s107: respectively calculating the height values from the measurement points on the positive electrode and the negative electrode of the battery cell to the respective optimal planes;
s108: taking the calculated height value as the flatness, taking a least square plane of an actual measured surface as an evaluation reference plane, and taking the distance between two containing planes which are parallel to the least square plane and have the minimum distance as a flatness error value, wherein the least square plane is a plane which enables the square sum of the distances between each point on the actual measured surface and the plane to be minimum;
s109: comparing the flatness with corresponding preset upper and lower limit parameter values, if the result is within the upper and lower limit parameter ranges, the flatness of the anode and the cathode of the battery cell is qualified, otherwise, the flatness is not qualified, and the battery cell is recovered;
s110: calculating the distance between each measuring point on the positive electrode and the negative electrode of the battery cell and the optimal plane of the battery cell as a Height value, comparing the Height value corresponding to each measuring point with a corresponding preset upper and lower limit parameter value, and if the Height result is within the upper and lower limit parameter range, determining the positive electrode and the negative electrode of the battery cell as qualified, and continuing the next test; otherwise, the battery cell is unqualified and recovered;
s111: setting interested areas on the edges of the insulating film and the edges of the positive electrode and the negative electrode of the battery cell, fitting out a line segment through an edge finding tool, and taking the line segment as the line segment on the insulating film and the positive electrode and the negative electrode of the battery cell;
s112: obtaining a starting point, an ending point and a middle point of a line segment on the positive electrode and the negative electrode of the battery cell;
s113: calculating the distances from the starting point, the ending point and the middle point of the line segment on the positive electrode and the negative electrode of the battery cell to the line segment of the insulating film to obtain 3 Dis values respectively;
s114: respectively comparing the Dis value with corresponding preset upper and lower limit parameter values, if the result is within the upper and lower limit parameter ranges, the interval from the edge of the insulating film to the edge of the anode and the cathode is qualified, and continuing the next test; otherwise, the battery cell is unqualified and recovered;
s115: using a gray level diagram to read two-dimensional code information on the battery cell;
s116: the cell flows into the next process.
2. The method for detecting the height level difference of the battery cell based on the laser line scanning 3D camera according to claim 1, wherein the step S101 specifically comprises:
and (5) after clamping the battery cell, carrying out image acquisition on the battery cell.
3. The method for detecting a cell height level difference based on a laser line scanning 3D camera according to claim 1, wherein in S103, the template object in the standard template is composed of edge information of a template area.
4. The method for detecting a level difference of a cell based on a laser line scanning 3D camera according to claim 1, wherein in S105, the distribution of the plurality of measurement points includes:
respectively placing 9 measuring points arranged according to 3*3 on the anode and cathode of the battery core, wherein the corresponding 9 measuring points cover the surfaces of the anode and the cathode respectively;
placing 30 measurement points arranged according to 3 x 10 on the plane of the battery cell, wherein the 30 measurement points cover the plane of the battery cell;
wherein the size of each point measurement point is a dot with a diameter of 3 pixels.
5. The method for detecting the height level difference of the battery cell based on the laser line scanning 3D camera according to claim 1, wherein in S107, the height value of the measurement point is obtained by calculation in a weighted average mode, and the weighting mode is an arithmetic average value, and when calculating, the height of each point is detected and averaged in a specified area range.
6. The method for detecting a height level difference of a cell based on a laser line scanning 3D camera according to claim 1, wherein in S111, the fitting line segment specifically includes:
randomly selecting two points from the point set, defining a straight line by the two points, and re-selecting the two points if the two points are too close to each other or the direction of the straight line deviates from the parameter-specified direction too much; calculating the distance between the line and all other points, selecting all points with the distance smaller than the abnormal value threshold value, and if the number of the points is larger than the minimum boundary percentage, replacing the origin set by the points;
using all points for the line estimation model;
calculating the vertical line distance from each point to the line, if the distance is greater than the current abnormal value threshold value, neglecting the line, and updating the abnormal value threshold value after each iteration; gradually amplifying the edge model attachment points, wherein other points are ignored as noise points or part of other edges; the iteration continues until either the maximum number of iterations is exceeded or the percentage of remaining points is less than the minimum number of retained iterations, the resulting line model will be returned as a result.
7. The method for detecting a height level difference of a battery cell based on a laser line scanning 3D camera according to claim 1, wherein the step S115 specifically comprises:
and placing the region of interest in a two-dimensional code range on the battery cell, and using a two-dimensional code reading tool to read, record and store the two-dimensional code information of the battery cell.
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