CN116448666A - Detection device and detection method for lithium battery box based on machine vision - Google Patents
Detection device and detection method for lithium battery box based on machine vision Download PDFInfo
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- CN116448666A CN116448666A CN202310387469.4A CN202310387469A CN116448666A CN 116448666 A CN116448666 A CN 116448666A CN 202310387469 A CN202310387469 A CN 202310387469A CN 116448666 A CN116448666 A CN 116448666A
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- WHXSMMKQMYFTQS-UHFFFAOYSA-N Lithium Chemical compound [Li] WHXSMMKQMYFTQS-UHFFFAOYSA-N 0.000 title claims abstract description 289
- 229910052744 lithium Inorganic materials 0.000 title claims abstract description 289
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/01—Arrangements or apparatus for facilitating the optical investigation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B07—SEPARATING SOLIDS FROM SOLIDS; SORTING
- B07C—POSTAL SORTING; SORTING INDIVIDUAL ARTICLES, OR BULK MATERIAL FIT TO BE SORTED PIECE-MEAL, e.g. BY PICKING
- B07C5/00—Sorting according to a characteristic or feature of the articles or material being sorted, e.g. by control effected by devices which detect or measure such characteristic or feature; Sorting by manually actuated devices, e.g. switches
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- 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
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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
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- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
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- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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- G01N21/84—Systems specially adapted for particular applications
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract
The invention discloses a detection device and a detection method of a lithium battery box based on machine vision, wherein the detection device comprises the following components: the device comprises a machine vision detection module, a positioning calibration module and a detection result output module; the positioning calibration module is used for calibrating the set position of each lithium battery box on the transmission line, determining the calibration position and distinguishing each lithium battery box from the adjacent lithium battery boxes; the machine vision detection module is used for performing machine vision detection on the lithium battery boxes on the transmission line, acquiring the arrangement modes of all the lithium battery modules in the lithium battery boxes based on the calibration setting positions of the positioning calibration module when performing machine vision detection, judging whether the arrangement modes meet preset requirements, and determining a detection result according to a judgment result; the detection result output module is used for outputting the detection result of the machine vision detection module. The sorting efficiency of the lithium battery boxes is improved, and based on the positioning identification, the lithium battery boxes with different specifications can be completely identified and sorted.
Description
Technical Field
The invention relates to the technical field of lithium battery detection, in particular to a detection device and a detection method of a lithium battery box based on machine vision.
Background
The lithium battery box has the advantages of high quality specific capacity, good cycle performance, long service life, good high and low temperature performance, high working voltage, good safety, no memory, environmental friendliness and the like, and rapidly becomes a main driving power source of electronic products, and most lithium battery box manufacturers adopt a manual hand touch and observation method for sorting the lithium battery box at present, and the method depends on the feeling and experience judgment of operators, has low efficiency and depends on human factors.
At present, even when sorting lithium battery cartridges by means of automatic recognition, it is common to sort lithium battery cartridges of one specification by means of fixing, but not to sort lithium battery cartridges of different specifications. In addition, the problem of low recognition efficiency may be caused by the difference in distance between lithium battery cartridges on the transmission line.
Disclosure of Invention
The invention provides a detection device and a detection method for a lithium battery box based on machine vision, which are used for solving the problems in the prior art.
The invention provides a detection device of a lithium battery box based on machine vision, which comprises: the device comprises a machine vision detection module, a positioning calibration module and a detection result output module;
the positioning calibration module is used for calibrating the set position of each lithium battery box on the transmission line, determining the calibration position and distinguishing each lithium battery box from the adjacent lithium battery boxes;
the machine vision detection module is used for performing machine vision detection on the lithium battery boxes on the transmission line, acquiring the arrangement modes of all the lithium battery modules in the lithium battery boxes based on the calibration setting positions of the positioning calibration module when performing machine vision detection, judging whether the arrangement modes meet preset requirements, and determining a detection result according to a judgment result;
the detection result output module is used for outputting the detection result of the machine vision detection module.
Preferably, the positioning calibration module comprises: positioning an electronic tag;
the positioning electronic tag positions a set position of the lithium battery box through positioning equipment, and the electronic tag is stuck to the set position;
before the machine vision detection module performs image acquisition of the lithium battery box, an electronic tag is stuck to the set position, and when the image is processed after the image is acquired, two adjacent lithium battery boxes are distinguished based on the electronic tag;
The detection result output module transmits the detection result to a reader-writer corresponding to the electronic tag on the corresponding lithium battery box, and the reader-writer writes the corresponding detection result into the corresponding electronic tag based on the unique identification of the electronic tag.
Preferably, the positioning calibration module further comprises: laser positioning identification;
the laser positioning mark outputs a laser beam through laser positioning equipment, and the set position of the lithium battery box is calibrated through the laser beam;
when the machine vision detection module performs image acquisition of the lithium battery boxes, the laser positioning equipment generates laser beams to position the set positions, and when the images are acquired, light spots generated by the laser beams irradiating the lithium battery boxes are used as positioning calibration to distinguish two adjacent lithium battery boxes.
Preferably, the machine vision detection module includes: an industrial camera assembly, a stationary assembly, and an image processing assembly;
the industrial camera component is arranged above the transmission line through the fixing component, after the setting position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component performs image acquisition on the lithium battery box, acquires first images of all lithium battery modules in the lithium battery box, the image processing component acquires the first images, processes the first images, determines the first position of the first images corresponding to the calibration position of the lithium battery box, performs identification and judgment on the first images of the lithium battery box by taking the first position as a reference, and determines whether the arrangement mode of the lithium battery modules in the lithium battery box meets preset requirements, if the arrangement mode meets the preset requirements, the judgment result is a qualified product, and if the arrangement mode does not meet the preset requirements, the judgment result is a disqualified product;
When the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
Preferably, the preset requirements include: the positive electrodes and the negative electrodes of the lithium battery modules are in accordance with the set arrangement, the interval between two lithium batteries in the lithium battery modules is in accordance with the set distance, the length and the width of the lithium battery modules are in accordance with the set size, the number and the sorting mode of the lithium batteries in the lithium battery modules are in accordance with the set requirement, and the electrode size of the lithium batteries in the lithium battery modules is in accordance with the set size.
Preferably, the image processing assembly includes: the image noise reduction processing module is used for carrying out noise reduction processing on the acquired first image;
the image noise reduction processing module includes:
the judging unit is used for judging all the pixel points under the largest filtering template when determining the size of the filtering template of the first image and judging whether the pixel points are effective pixel points or not; setting a noise gray level range in a first image and an initial center pixel during filtering, if the noise gray level range is not processed for effective pixel points, setting an initial maximum value of a filtering template if the noise gray level range is not processed for effective pixel points;
The distance recording unit is used for recording the effective pixel points and calculating the distance between the effective pixel points and the central pixel point; setting coordinates of effective pixel points, traversing all the pixel points except for the middle point in the filtering template, if the effective pixel points are the effective pixel points, recording the coordinate information of the effective pixel points, and calculating the distance between the effective pixel points and the pixel points of the central point;
the optimal filtering template unit is used for determining the size of the optimal filtering template through the distances between all the effective pixel points and the central pixel point; counting the values of the distances between all the effective pixel points and the pixel points of the central point, taking out the value of the distance which enables the effective pixel points at the edge of the filtering template to be the most, and carrying out odd calculation according to the distance to determine the size of the filtering template;
the computing unit is used for carrying out sequencing computation on the effective pixel points of the template corresponding to the optimal filtering template in size, setting a sequenced effective pixel point set, and taking median filtering computation on the effective pixel point set to obtain a filtering result of the first image.
Preferably, the image processing assembly further comprises:
a center point determining unit for determining a center point of the acquired first image; calculating the center point coordinates of the first image based on all the edge points with gray values of 1 on the first image, and taking the center point coordinates as initial center coordinates of the center points of the first image;
An initial diagonal determining unit, configured to find four points farthest from the initial center coordinates in an area where four vertex angles of the first image are located, and determine positions where initial diagonals are located by using the four points as initial four vertex angles of the first image;
a new center point determination unit configured to take an intersection point of the initial diagonal lines as a new center point coordinate of the first image;
and the lithium battery module size determining unit is used for calculating the current diagonal size when the distance between the determined diagonal intersection point and the central point obtained by the previous calculation is less than or equal to 1 pixel point, and determining the length and the width of the lithium battery module based on the current diagonal size.
Preferably, the image processing assembly further comprises:
an electrode image obtaining unit for obtaining an electrode image of each lithium battery in the lithium battery module based on the first image; threshold segmentation is carried out on the first image, a gray value is set to divide the gray value of the electrode image into two parts, when the inter-class variance of the training drum part is the maximum value, the set gray value is used as the segmentation threshold of the electrode image, and the electrode image is obtained based on threshold segmentation;
an electrode image contour obtaining unit, configured to perform feature extraction on an edge of the electrode image to obtain a contour of the electrode image; detecting from the lower left corner of the electrode image along the anticlockwise direction, if the pixel point at the lower left corner is detected to be a black point, then tracking along the boundary is started; if the pixel point at the lower left corner is not a black point, rotating the detection direction by 45 degrees along the anticlockwise direction until the first black point in the image is detected, and performing tracking along the boundary; rotating the electrode image along the clockwise direction by 90 degrees on the basis of the current exploration direction, repeating the steps until the original detection point is detected, completing the boundary tracking of the whole electrode image, and determining the outline of the electrode image;
The abnormal point identification unit is used for identifying whether an abnormal point exists in the outline based on the outline of the electrode image.
The invention also provides a detection method of the lithium battery box based on machine vision, which comprises the following steps:
s100, calibrating the set position of each lithium battery box on the transmission line, determining the calibrated position, and distinguishing each lithium battery box from the adjacent lithium battery boxes;
s200, calibrating the set position of each lithium battery box on a transmission line through a machine vision detection module, determining the calibrated position, and distinguishing each lithium battery box from the adjacent lithium battery boxes;
s300, outputting a detection result of the machine vision detection module.
Preferably, the S200 includes:
s201, the machine vision detection module comprises: an industrial camera assembly, a stationary assembly, and an image processing assembly;
s202, the industrial camera component is arranged above a transmission line through the fixing component, after the setting position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component acquires images of the lithium battery box, first images of all lithium battery modules in the lithium battery box are acquired, and the image processing component acquires the first images;
S203, processing the first image, determining a first position in the first image corresponding to a calibration position of the lithium battery box, identifying and judging the first image of the lithium battery box by taking the first position as a reference, and determining whether the arrangement mode of the lithium battery modules in the lithium battery box meets the preset requirement, if so, judging the lithium battery modules as qualified products, and if not, judging the lithium battery modules as unqualified products;
when the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
Compared with the prior art, the invention has the following advantages:
the invention provides a detection device and a detection method of a lithium battery box based on machine vision, wherein the detection device comprises the following components: the device comprises a machine vision detection module, a positioning calibration module and a detection result output module; the positioning calibration module is used for calibrating the set position of each lithium battery box on the transmission line, determining the calibration position and distinguishing each lithium battery box from the adjacent lithium battery boxes; the machine vision detection module is used for performing machine vision detection on the lithium battery boxes on the transmission line, acquiring the arrangement modes of all the lithium battery modules in the lithium battery boxes based on the calibration setting positions of the positioning calibration module when performing machine vision detection, judging whether the arrangement modes meet preset requirements, and determining a detection result according to a judgment result; the detection result output module is used for outputting the detection result of the machine vision detection module. The sorting efficiency of the lithium battery boxes is improved, and based on the positioning identification, the lithium battery boxes with different specifications can be completely identified and sorted.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a schematic structural diagram of a detection device for a lithium battery case based on machine vision according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an image processing component according to an embodiment of the present invention;
fig. 3 is a flowchart of a method for detecting a lithium battery case based on machine vision according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides a detection device of a lithium battery box based on machine vision, please refer to fig. 1, the detection device comprises: the device comprises a machine vision detection module, a positioning calibration module and a detection result output module;
the positioning calibration module is used for calibrating the set position of each lithium battery box on the transmission line, determining the calibration position and distinguishing each lithium battery box from the adjacent lithium battery boxes;
the machine vision detection module is used for performing machine vision detection on the lithium battery boxes on the transmission line, acquiring the arrangement modes of all the lithium battery modules in the lithium battery boxes based on the calibration setting positions of the positioning calibration module when performing machine vision detection, judging whether the arrangement modes meet preset requirements, and determining a detection result according to a judgment result;
the detection result output module is used for outputting the detection result of the machine vision detection module.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted by the embodiment comprises the following steps: the device comprises a machine vision detection module, a positioning calibration module and a detection result output module; the positioning calibration module is used for calibrating the set position of each lithium battery box on the transmission line, determining the calibration position and distinguishing each lithium battery box from the adjacent lithium battery boxes; the machine vision detection module is used for performing machine vision detection on the lithium battery boxes on the transmission line, acquiring the arrangement modes of all the lithium battery modules in the lithium battery boxes based on the calibration setting positions of the positioning calibration module when performing machine vision detection, judging whether the arrangement modes meet preset requirements, and determining a detection result according to a judgment result; the detection result output module is used for outputting the detection result of the machine vision detection module.
First, each lithium battery box is calibrated through a positioning calibration module, when machine vision detection is carried out, two adjacent lithium battery boxes can be distinguished quickly, and the problem that the recognition efficiency is reduced due to the fact that the lithium battery boxes move on a transmission line or the distance between the adjacent lithium battery boxes is relatively close or relatively far is prevented. In this embodiment, a positioning identifier is set on each lithium battery box, and the positioning identifier can be further identified by a machine vision detection module, so that each lithium battery box can be distinguished quickly by the machine vision detection module through the positioning identifier in the identification process, and further, the lithium battery modules in each lithium battery box are identified and judged whether to meet the arrangement mode of preset requirements, the sorting efficiency of the lithium battery boxes is improved, and based on the positioning identifier, the lithium battery boxes with different specifications can be completely identified and sorted.
In another embodiment, the positioning calibration module includes: positioning an electronic tag;
the positioning electronic tag positions a set position of the lithium battery box through positioning equipment, and the electronic tag is stuck to the set position;
before the machine vision detection module performs image acquisition of the lithium battery box, an electronic tag is stuck to the set position, and when the image is processed after the image is acquired, two adjacent lithium battery boxes are distinguished based on the electronic tag;
The detection result output module transmits the detection result to a reader-writer corresponding to the electronic tag on the corresponding lithium battery box, and the reader-writer writes the corresponding detection result into the corresponding electronic tag based on the unique identification of the electronic tag.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted by the embodiment is that the positioning calibration module comprises: positioning an electronic tag; the positioning electronic tag positions a set position of the lithium battery box through positioning equipment, and the electronic tag is stuck to the set position; before the machine vision detection module performs image acquisition of the lithium battery box, an electronic tag is stuck to the set position, and when the image is processed after the image is acquired, two adjacent lithium battery boxes are distinguished based on the electronic tag; the detection result output module transmits the detection result to a reader-writer corresponding to the electronic tag on the corresponding lithium battery box, and the reader-writer writes the corresponding detection result into the corresponding electronic tag based on the unique identification of the electronic tag.
The detection result can be written into the corresponding electronic tag when the electronic tag is used for positioning, so that the problem that lithium battery boxes with different specifications cannot be sorted can be solved, the subsequent problem of sorting can be optimized, and the fact that the battery modules in the lithium battery boxes do not meet preset requirements can be identified by scanning the electronic tag. The equipment for automatically scanning the electronic tag can be added subsequently, and if the scanned electronic tag shows that the lithium battery module does not meet the requirements, the corresponding lithium battery box can be removed directly through the automatic control equipment. Realize full-automatic separation of lithium battery box, and promoted separation efficiency.
In another embodiment, the positioning calibration module further includes: laser positioning identification;
the laser positioning mark outputs a laser beam through laser positioning equipment, and the set position of the lithium battery box is calibrated through the laser beam;
when the machine vision detection module performs image acquisition of the lithium battery boxes, the laser positioning equipment generates laser beams to position the set positions, and when the images are acquired, light spots generated by the laser beams irradiating the lithium battery boxes are used as positioning calibration to distinguish two adjacent lithium battery boxes.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted by the embodiment is that the positioning calibration module further comprises: laser positioning identification; the laser positioning mark outputs a laser beam through laser positioning equipment, and the set position of the lithium battery box is calibrated through the laser beam; when the machine vision detection module performs image acquisition of the lithium battery boxes, the laser positioning equipment generates laser beams to position the set positions, and when the images are acquired, light spots generated by the laser beams irradiating the lithium battery boxes are used as positioning calibration to distinguish two adjacent lithium battery boxes.
Although laser equipment is added through laser positioning, positioning is accurate, no additional label or accessory product is generated on the lithium battery box, and the laser positioning equipment assists the machine vision detection module to identify each lithium battery box. The laser beam forms a light spot on an image imaged by the machine vision detection module, and the light spot can be set as a positioning mark so as to distinguish each lithium battery box and facilitate positioning identification of each lithium battery box.
In another embodiment, the machine vision inspection module includes: an industrial camera assembly, a stationary assembly, and an image processing assembly;
the industrial camera component is arranged above the transmission line through the fixing component, after the setting position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component performs image acquisition on the lithium battery box, acquires first images of all lithium battery modules in the lithium battery box, the image processing component acquires the first images, processes the first images, determines the first position of the first images corresponding to the calibration position of the lithium battery box, performs identification and judgment on the first images of the lithium battery box by taking the first position as a reference, and determines whether the arrangement mode of the lithium battery modules in the lithium battery box meets preset requirements, if the arrangement mode meets the preset requirements, the judgment result is a qualified product, and if the arrangement mode does not meet the preset requirements, the judgment result is a disqualified product;
when the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme of this embodiment adoption is that the machine vision detection module includes: an industrial camera assembly, a stationary assembly, and an image processing assembly; the industrial camera component is arranged above the transmission line through the fixing component, after the setting position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component performs image acquisition on the lithium battery box, acquires first images of all lithium battery modules in the lithium battery box, the image processing component acquires the first images, processes the first images, determines the first position of the first images corresponding to the calibration position of the lithium battery box, performs identification and judgment on the first images of the lithium battery box by taking the first position as a reference, and determines whether the arrangement mode of the lithium battery modules in the lithium battery box meets preset requirements, if the arrangement mode meets the preset requirements, the judgment result is a qualified product, and if the arrangement mode does not meet the preset requirements, the judgment result is a disqualified product; when the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
When the machine vision detection module is used for identifying the lithium battery boxes, the industrial camera assembly is used for collecting the first image, identifying and judging whether the first image meets the preset requirement or not, and when the machine vision detection module is used for identifying and judging, each lithium battery box is rapidly distinguished by using the calibration position, so that the identification efficiency is improved.
In another embodiment, the preset requirements include: the positive electrodes and the negative electrodes of the lithium battery modules are in accordance with the set arrangement, the interval between two lithium batteries in the lithium battery modules is in accordance with the set distance, the length and the width of the lithium battery modules are in accordance with the set size, the number and the sorting mode of the lithium batteries in the lithium battery modules are in accordance with the set requirement, and the electrode size of the lithium batteries in the lithium battery modules is in accordance with the set size.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted in this embodiment is that the preset requirements include: the positive electrodes and the negative electrodes of the lithium battery modules are in accordance with the set arrangement, the interval between two lithium batteries in the lithium battery modules is in accordance with the set distance, the length and the width of the lithium battery modules are in accordance with the set size, the number and the sorting mode of the lithium batteries in the lithium battery modules are in accordance with the set requirement, and the electrode size of the lithium batteries in the lithium battery modules is in accordance with the set size. The method is characterized in that the negative electrode of the whole battery module is required to be identified, the interval, the electrode size and the like of the lithium battery are also required to be identified, the quality of the lithium battery module in the lithium battery box can be judged by identifying the image, and then the sorting operation of the lithium battery box is finished.
In another embodiment, referring to fig. 2, the image processing assembly includes: the image noise reduction processing module is used for carrying out noise reduction processing on the acquired first image;
the image noise reduction processing module includes:
the judging unit is used for judging all the pixel points under the largest filtering template when determining the size of the filtering template of the first image and judging whether the pixel points are effective pixel points or not; setting a noise gray level range in a first image and an initial center pixel during filtering, if the noise gray level range is not processed for effective pixel points, setting an initial maximum value of a filtering template if the noise gray level range is not processed for effective pixel points;
the distance recording unit is used for recording the effective pixel points and calculating the distance between the effective pixel points and the central pixel point; setting coordinates of effective pixel points, traversing all the pixel points except for the middle point in the filtering template, if the effective pixel points are the effective pixel points, recording the coordinate information of the effective pixel points, and calculating the distance between the effective pixel points and the pixel points of the central point;
the optimal filtering template unit is used for determining the size of the optimal filtering template through the distances between all the effective pixel points and the central pixel point; counting the values of the distances between all the effective pixel points and the pixel points of the central point, taking out the value of the distance which enables the effective pixel points at the edge of the filtering template to be the most, and carrying out odd calculation according to the distance to determine the size of the filtering template;
The size of the filtering template is equal to the calculated distance value multiplied by 2 and then added with 1 to form an odd number. The calculated distance is a value of a distance that maximizes the effective pixels of the filter template edge.
The computing unit is used for carrying out sequencing computation on the effective pixel points of the template corresponding to the optimal filtering template in size, setting a sequenced effective pixel point set, and taking median filtering computation on the effective pixel point set to obtain a filtering result of the first image.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted by the embodiment is that the image processing component comprises: the image noise reduction processing module is used for carrying out noise reduction processing on the acquired first image; the image noise reduction processing module includes: the judging unit is used for judging all the pixel points under the largest filtering template when determining the size of the filtering template of the first image and judging whether the pixel points are effective pixel points or not; setting a noise gray level range in a first image and an initial center pixel during filtering, if the noise gray level range is not processed for effective pixel points, setting an initial maximum value of a filtering template if the noise gray level range is not processed for effective pixel points; the distance recording unit is used for recording the effective pixel points and calculating the distance between the effective pixel points and the central pixel point; setting coordinates of effective pixel points, traversing all the pixel points except for the middle point in the filtering template, if the effective pixel points are the effective pixel points, recording the coordinate information of the effective pixel points, and calculating the distance between the effective pixel points and the pixel points of the central point; the optimal filtering template unit is used for determining the size of the optimal filtering template through the distances between all the effective pixel points and the central pixel point; counting the values of the distances between all the effective pixel points and the pixel points of the central point, taking out the value of the distance which enables the effective pixel points at the edge of the filtering template to be the most, and carrying out odd calculation according to the distance to determine the size of the filtering template; the computing unit is used for carrying out sequencing computation on the effective pixel points of the template corresponding to the optimal filtering template in size, setting a sequenced effective pixel point set, and taking median filtering computation on the effective pixel point set to obtain a filtering result of the first image.
The scheme provided by the embodiment effectively avoids the repeated calculation of some pixel points in the image in the traditional self-adaptive median filtering algorithm, and reduces the complexity of the whole operation; on the other hand, the scheme of the embodiment only sorts the effective pixel points in the graph, so that the denoising effect of the image and the operation efficiency of the algorithm are greatly improved.
In another embodiment, the image processing assembly further comprises:
a center point determining unit for determining a center point of the acquired first image; calculating the center point coordinates of the first image based on all the edge points with gray values of 1 on the first image, and taking the center point coordinates as initial center coordinates of the center points of the first image;
the first image has n points in a two-position coordinate space, and the abscissa of the points is respectively: x is x 1 ,x 2 ,…x n ；
Thus, the center point abscissa x of these points 0 The method comprises the following steps:
simultaneously, n ordinate coordinates are respectively set as follows: y is 1 ,y 2 ,…y n The midpoint ordinate y of these points 0 The method comprises the following steps:
thus, the coordinates of the center point are (x 0 ,y 0 )。
An initial diagonal determining unit, configured to find four points farthest from the initial center coordinate in an area where four vertex angles of the first image are located based on a distance formula, and determine positions where initial diagonals are located by using the four points as initial four vertex angles of the first image;
The distance formula is as follows:
D＝sqrt[(x 0 -x) 2 +(y 0 -y) 2 ]
wherein D represents the distance between two points in the distance formula, sqrt represents the square root, and x 0 Represents the abscissa, y of the center point 0 Representing the ordinate of the center point, x representing the abscissa of the four corners and y representing the ordinate of the four corners.
A new center point determination unit configured to take an intersection point of the initial diagonal lines as a new center point coordinate of the first image;
the new center point coordinate of the first image, which is the intersection of the two diagonals, is (x d ,y d ) The calculation formula for calculating the distance d between the new center point and the original center point is as follows:
d＝sqrt[(x 0 -x d ） 2 +(y 0 -y d ) 2 ]
if the distance between the two is less than or equal to 1 pixel point, namely d is less than or equal to 1, the four vertex coordinates obtained by calculation at the moment are taken as the positions of the four vertex angles of the first image, so that the position of a diagonal line of the first image can be determined, and the size of the diagonal line is further calculated; if d >1, stopping the circulation until the distance between the new center point and the center point obtained last time is less than or equal to 1 pixel point, namely d is less than or equal to 1, and outputting two diagonal sizes.
And the lithium battery module size determining unit is used for calculating the current diagonal size when the distance between the determined diagonal intersection point and the central point obtained by the previous calculation is less than or equal to 1 pixel point, and determining the length and the width of the lithium battery module based on the current diagonal size.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted by the embodiment is that the image processing component further comprises: a center point determining unit for determining a center point of the acquired first image; calculating the center point coordinates of the first image based on all the edge points with gray values of 1 on the first image, and taking the center point coordinates as initial center coordinates of the center points of the first image; an initial diagonal determining unit, configured to find four points farthest from the initial center coordinates in an area where four vertex angles of the first image are located, and determine positions where initial diagonals are located by using the four points as initial four vertex angles of the first image; a new center point determination unit configured to take an intersection point of the initial diagonal lines as a new center point coordinate of the first image; and the lithium battery module size determining unit is used for calculating the current diagonal size when the distance between the determined diagonal intersection point and the central point obtained by the previous calculation is less than or equal to 1 pixel point, and determining the length and the width of the lithium battery module based on the current diagonal size.
In the prior art, the Pythagorean theorem is adopted to calculate the diagonal dimension when the edge length dimension is calculated, and the calculation method omits the problems of round corners, burrs and the like possibly occurring in the vertex angles.
In this embodiment, the length and width of the lithium battery module are calculated, specifically, the length and width are calculated by calculating a diagonal line, the diagonal line is calculated and determined by updating the center point, and the process of updating the center point is repeated until the center point is unchanged, so that the position of the diagonal line is determined, and the length and width of the lithium battery module are further determined.
In another embodiment, the image processing assembly further comprises:
an electrode image obtaining unit for obtaining an electrode image of each lithium battery in the lithium battery module based on the first image; threshold segmentation is carried out on the first image, a gray value is set to divide the gray value of the electrode image into two parts, when the inter-class variance of the training drum part is the maximum value, the set gray value is used as the segmentation threshold of the electrode image, and the electrode image is obtained based on threshold segmentation;
an electrode image contour obtaining unit, configured to perform feature extraction on an edge of the electrode image to obtain a contour of the electrode image; detecting from the lower left corner of the electrode image along the anticlockwise direction, if the pixel point at the lower left corner is detected to be a black point, then tracking along the boundary is started; if the pixel point at the lower left corner is not a black point, rotating the detection direction by 45 degrees along the anticlockwise direction until the first black point in the image is detected, and performing tracking along the boundary; rotating the electrode image along the clockwise direction by 90 degrees on the basis of the current exploration direction, repeating the steps until the original detection point is detected, completing the boundary tracking of the whole electrode image, and determining the outline of the electrode image;
The abnormal point identification unit is used for identifying whether an abnormal point exists in the outline based on the outline of the electrode image.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted by the embodiment is that the image processing component further comprises: an electrode image obtaining unit for obtaining an electrode image of each lithium battery in the lithium battery module based on the first image; threshold segmentation is carried out on the first image, a gray value is set to divide the gray value of the electrode image into two parts, when the inter-class variance of the training drum part is the maximum value, the set gray value is used as the segmentation threshold of the electrode image, and the electrode image is obtained based on threshold segmentation; an electrode image contour obtaining unit, configured to perform feature extraction on an edge of the electrode image to obtain a contour of the electrode image; detecting from the lower left corner of the electrode image along the anticlockwise direction, if the pixel point at the lower left corner is detected to be a black point, then tracking along the boundary is started; if the pixel point at the lower left corner is not a black point, rotating the detection direction by 45 degrees along the anticlockwise direction until the first black point in the image is detected, and performing tracking along the boundary; rotating the electrode image along the clockwise direction by 90 degrees on the basis of the current exploration direction, repeating the steps until the original detection point is detected, completing the boundary tracking of the whole electrode image, and determining the outline of the electrode image; the abnormal point identification unit is used for identifying whether an abnormal point exists in the outline based on the outline of the electrode image.
The outline can be determined in a boundary-following mode, so that the image area of the electrode is further accurate, and the electrode size or whether the surface of the electrode is abnormal or not can be conveniently judged.
In another embodiment, the present embodiment provides a method for detecting a lithium battery case based on machine vision, referring to fig. 3, the method includes:
s100, calibrating the set position of each lithium battery box on the transmission line, determining the calibrated position, and distinguishing each lithium battery box from the adjacent lithium battery boxes;
s200, calibrating the set position of each lithium battery box on a transmission line through a machine vision detection module, determining the calibrated position, and distinguishing each lithium battery box from the adjacent lithium battery boxes;
s300, outputting a detection result of the machine vision detection module.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme adopted by the embodiment is that the set position of each lithium battery box on a transmission line is calibrated, the calibration position is determined, and each lithium battery box is distinguished from the adjacent lithium battery box; calibrating the set position of each lithium battery box on the transmission line through the machine vision detection module, determining the calibrated position, and distinguishing each lithium battery box from the adjacent lithium battery boxes; and outputting a detection result of the machine vision detection module.
In another embodiment, the S200 includes:
s201, the machine vision detection module comprises: an industrial camera assembly, a stationary assembly, and an image processing assembly;
s202, the industrial camera component is arranged above a transmission line through the fixing component, after the setting position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component acquires images of the lithium battery box, first images of all lithium battery modules in the lithium battery box are acquired, and the image processing component acquires the first images;
s203, processing the first image, determining a first position in the first image corresponding to a calibration position of the lithium battery box, identifying and judging the first image of the lithium battery box by taking the first position as a reference, and determining whether the arrangement mode of the lithium battery modules in the lithium battery box meets the preset requirement, if so, judging the lithium battery modules as qualified products, and if not, judging the lithium battery modules as unqualified products;
when the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
The working principle and the beneficial effects of the technical scheme are as follows: the scheme that this embodiment adopted is to set up the machine vision detection module includes: an industrial camera assembly, a stationary assembly, and an image processing assembly; the industrial camera component is arranged above the transmission line through the fixing component, the set position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component acquires images of the lithium battery box, first images of all lithium battery modules in the lithium battery box are acquired, and the image processing component acquires the first images; processing the first image, determining a first position in the first image corresponding to a calibration position of the lithium battery box, identifying and judging the first image of the lithium battery box by taking the first position as a reference, and determining whether the arrangement mode of the lithium battery modules in the lithium battery box meets the preset requirement, if so, determining that the lithium battery modules are qualified products, and if not, determining that the lithium battery modules are unqualified products; when the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. Detection device of lithium battery box based on machine vision, characterized by comprising: the device comprises a machine vision detection module, a positioning calibration module and a detection result output module;
the positioning calibration module is used for calibrating the set position of each lithium battery box on the transmission line, determining the calibration position and distinguishing each lithium battery box from the adjacent lithium battery boxes;
the machine vision detection module is used for performing machine vision detection on the lithium battery boxes on the transmission line, acquiring the arrangement modes of all the lithium battery modules in the lithium battery boxes based on the calibration setting positions of the positioning calibration module when performing machine vision detection, judging whether the arrangement modes meet preset requirements, and determining a detection result according to a judgment result;
the detection result output module is used for outputting the detection result of the machine vision detection module.
2. The machine vision-based lithium battery cartridge detection device of claim 1, wherein the positioning calibration module comprises: positioning an electronic tag;
the positioning electronic tag positions a set position of the lithium battery box through positioning equipment, and the electronic tag is stuck to the set position;
before the machine vision detection module performs image acquisition of the lithium battery box, an electronic tag is stuck to the set position, and when the image is processed after the image is acquired, two adjacent lithium battery boxes are distinguished based on the electronic tag;
the detection result output module transmits the detection result to a reader-writer corresponding to the electronic tag on the corresponding lithium battery box, and the reader-writer writes the corresponding detection result into the corresponding electronic tag based on the unique identification of the electronic tag.
3. The machine vision-based lithium battery cartridge detection device of claim 1, wherein the positioning calibration module further comprises: laser positioning identification;
the laser positioning mark outputs a laser beam through laser positioning equipment, and the set position of the lithium battery box is calibrated through the laser beam;
when the machine vision detection module performs image acquisition of the lithium battery boxes, the laser positioning equipment generates laser beams to position the set positions, and when the images are acquired, light spots generated by the laser beams irradiating the lithium battery boxes are used as positioning calibration to distinguish two adjacent lithium battery boxes.
4. The machine vision-based lithium battery cartridge inspection device of claim 1, wherein the machine vision inspection module comprises: an industrial camera assembly, a stationary assembly, and an image processing assembly;
the industrial camera component is arranged above the transmission line through the fixing component, after the setting position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component performs image acquisition on the lithium battery box, acquires first images of all lithium battery modules in the lithium battery box, the image processing component acquires the first images, processes the first images, determines the first position of the first images corresponding to the calibration position of the lithium battery box, performs identification and judgment on the first images of the lithium battery box by taking the first position as a reference, and determines whether the arrangement mode of the lithium battery modules in the lithium battery box meets preset requirements, if the arrangement mode meets the preset requirements, the judgment result is a qualified product, and if the arrangement mode does not meet the preset requirements, the judgment result is a disqualified product;
when the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
5. The machine vision-based lithium battery cartridge inspection device of claim 1, wherein the preset requirements include: the positive electrodes and the negative electrodes of the lithium battery modules are in accordance with the set arrangement, the interval between two lithium batteries in the lithium battery modules is in accordance with the set distance, the length and the width of the lithium battery modules are in accordance with the set size, the number and the sorting mode of the lithium batteries in the lithium battery modules are in accordance with the set requirement, and the electrode size of the lithium batteries in the lithium battery modules is in accordance with the set size.
6. The machine vision based lithium battery cartridge inspection device of claim 4, wherein the image processing component comprises: the image noise reduction processing module is used for carrying out noise reduction processing on the acquired first image;
the image noise reduction processing module includes:
the judging unit is used for judging all the pixel points under the largest filtering template when determining the size of the filtering template of the first image and judging whether the pixel points are effective pixel points or not; setting a noise gray level range in a first image and an initial center pixel during filtering, if the noise gray level range is not processed for effective pixel points, setting an initial maximum value of a filtering template if the noise gray level range is not processed for effective pixel points;
The distance recording unit is used for recording the effective pixel points and calculating the distance between the effective pixel points and the central pixel point; setting coordinates of effective pixel points, traversing all the pixel points except for the middle point in the filtering template, if the effective pixel points are the effective pixel points, recording the coordinate information of the effective pixel points, and calculating the distance between the effective pixel points and the pixel points of the central point;
the optimal filtering template unit is used for determining the size of the optimal filtering template through the distances between all the effective pixel points and the central pixel point; counting the values of the distances between all the effective pixel points and the pixel points of the central point, taking out the value of the distance which enables the effective pixel points at the edge of the filtering template to be the most, and carrying out odd calculation according to the distance to determine the size of the filtering template;
the computing unit is used for carrying out sequencing computation on the effective pixel points of the template corresponding to the optimal filtering template in size, setting a sequenced effective pixel point set, and taking median filtering computation on the effective pixel point set to obtain a filtering result of the first image.
7. The machine vision based lithium battery cartridge inspection device of claim 4, wherein,
the image processing assembly further comprises:
A center point determining unit for determining a center point of the acquired first image; calculating the center point coordinates of the first image based on all the edge points with gray values of 1 on the first image, and taking the center point coordinates as initial center coordinates of the center points of the first image;
an initial diagonal determining unit, configured to find four points farthest from the initial center coordinates in an area where four vertex angles of the first image are located, and determine positions where initial diagonals are located by using the four points as initial four vertex angles of the first image;
a new center point determination unit configured to take an intersection point of the initial diagonal lines as a new center point coordinate of the first image;
and the lithium battery module size determining unit is used for calculating the current diagonal size when the distance between the determined diagonal intersection point and the central point obtained by the previous calculation is less than or equal to 1 pixel point, and determining the length and the width of the lithium battery module based on the current diagonal size.
8. The machine vision based lithium battery cartridge inspection device of claim 4, wherein,
the image processing assembly further comprises:
an electrode image obtaining unit for obtaining an electrode image of each lithium battery in the lithium battery module based on the first image; threshold segmentation is carried out on the first image, a gray value is set to divide the gray value of the electrode image into two parts, when the inter-class variance of the training drum part is the maximum value, the set gray value is used as the segmentation threshold of the electrode image, and the electrode image is obtained based on threshold segmentation;
An electrode image contour obtaining unit, configured to perform feature extraction on an edge of the electrode image to obtain a contour of the electrode image; detecting from the lower left corner of the electrode image along the anticlockwise direction, if the pixel point at the lower left corner is detected to be a black point, then tracking along the boundary is started; if the pixel point at the lower left corner is not a black point, rotating the detection direction by 45 degrees along the anticlockwise direction until the first black point in the image is detected, and performing tracking along the boundary; rotating the electrode image along the clockwise direction by 90 degrees on the basis of the current exploration direction, repeating the steps until the original detection point is detected, completing the boundary tracking of the whole electrode image, and determining the outline of the electrode image;
the abnormal point identification unit is used for identifying whether an abnormal point exists in the outline based on the outline of the electrode image.
9. The detection method of the lithium battery box based on machine vision is characterized by comprising the following steps of:
s100, calibrating the set position of each lithium battery box on the transmission line, determining the calibrated position, and distinguishing each lithium battery box from the adjacent lithium battery boxes;
S200, calibrating the set position of each lithium battery box on a transmission line through a machine vision detection module, determining the calibrated position, and distinguishing each lithium battery box from the adjacent lithium battery boxes;
s300, outputting a detection result of the machine vision detection module.
10. The machine vision based lithium battery cartridge inspection method of claim 9, wherein S200 comprises:
s201, the machine vision detection module comprises: an industrial camera assembly, a stationary assembly, and an image processing assembly;
s202, the industrial camera component is arranged above a transmission line through the fixing component, after the setting position of the lithium battery box is determined and marked through the positioning calibration module, the industrial camera component acquires images of the lithium battery box, first images of all lithium battery modules in the lithium battery box are acquired, and the image processing component acquires the first images;
s203, processing the first image, determining a first position in the first image corresponding to a calibration position of the lithium battery box, identifying and judging the first image of the lithium battery box by taking the first position as a reference, and determining whether the arrangement mode of the lithium battery modules in the lithium battery box meets the preset requirement, if so, judging the lithium battery modules as qualified products, and if not, judging the lithium battery modules as unqualified products;
When the first image of the lithium battery box is identified and judged, the first image is compared with the corresponding standard image, and whether the lithium battery box corresponding to the first image meets the preset requirement is identified through comparison.
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