CN107101598B - Automatic detection method and device for concentricity quality of piezoelectric ceramic silver sheet - Google Patents
Automatic detection method and device for concentricity quality of piezoelectric ceramic silver sheet Download PDFInfo
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- BQCADISMDOOEFD-UHFFFAOYSA-N Silver Chemical compound [Ag] BQCADISMDOOEFD-UHFFFAOYSA-N 0.000 title claims abstract description 153
- 239000000919 ceramic Substances 0.000 title claims abstract description 138
- 229910052709 silver Inorganic materials 0.000 title claims abstract description 127
- 239000004332 silver Substances 0.000 title claims abstract description 127
- 238000001514 detection method Methods 0.000 title claims abstract description 98
- 238000000034 method Methods 0.000 claims abstract description 26
- 238000007747 plating Methods 0.000 claims description 23
- 238000003708 edge detection Methods 0.000 claims description 20
- 239000002699 waste material Substances 0.000 claims description 19
- 238000009499 grossing Methods 0.000 claims description 6
- 230000000877 morphologic effect Effects 0.000 claims description 6
- 238000012163 sequencing technique Methods 0.000 claims description 4
- 230000009466 transformation Effects 0.000 claims description 4
- 238000004519 manufacturing process Methods 0.000 abstract description 3
- 238000005245 sintering Methods 0.000 description 6
- 230000007547 defect Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000003993 interaction Effects 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
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- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000001035 drying Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000007639 printing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000007650 screen-printing Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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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
- G01B11/26—Measuring arrangements characterised by the use of optical techniques for measuring angles or tapers; for testing the alignment of axes
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Abstract
The invention discloses a method and a device for automatically detecting concentricity quality of a piezoelectric ceramic silver sheet, wherein the method comprises the following steps: and acquiring a gray level image through a camera, searching an outer circle and an inner circle contour point set of each piezoelectric ceramic silver sheet in the image, fitting a circular curve on the obtained point sets respectively, calculating the circle centers and the radiuses of the inner circle and the outer circle obtained by fitting, and calculating the concentricity of the inner circle and the outer circle. And comparing the concentricity measured by each piezoelectric ceramic silver piece with a preset concentricity threshold value, and judging whether the piezoelectric ceramic silver pieces belong to good products or unqualified products piece by piece. After the quality threshold is set according to the product model, the concentricity of the piezoelectric ceramic silver plates with different sizes is automatically measured without adjusting any parameter, the identification accuracy is high, the automatic detection degree can be greatly improved, and the production efficiency is improved.
Description
Technical Field
The invention relates to the field of computer vision and quality detection research, in particular to a method and a device for automatically detecting concentricity quality of a piezoelectric ceramic silver sheet.
Background
The piezoelectric ceramic silver sheet is formed by sintering piezoelectric ceramic, printing silver paste on the ceramic sheet in a silk screen printing mode, and drying and sintering. The quality of the piezoelectric ceramic silver sheet is mainly judged by the following three aspects: (1) concentricity of the ceramic chip and the silver layer: the center of the printed round silver layer in the round piezoelectric ceramic plate is concentric with the outer circle of the piezoelectric ceramic plate, and the concentricity is poor when the center deviation of the two is larger than a certain value, namely the concentricity is larger than a certain value; (2) poor sintering: the surface of the silver flake can generate bubbles, bulges and color changes due to high-temperature sintering, and is poor in sintering; (3) ceramic chip damage, silver layer scratch, etc.
The detection of poor concentricity is different from the detection of poor sintering and breakage of ceramic chips, and the detection of poor concentricity can be carried out by qualitatively judging whether various defects exist or not, but the concentricity requires quantitative size judgment to distinguish qualified products from unqualified products, so that on most production lines which also adopt naked eye manual detection at present, the concentricity is actually only judged to be very rough, and therefore, the control of the quality of products is very inaccurate.
In the prior art, concentricity is detected, the Hough transformation is mostly adopted to search the inner circle and the outer circle, and the center and the radius of the searched circle are calculated to calculate the concentricity. The method has certain requirement on the minimum distance between the inner circle and the outer circle, the distance between the inner circle and the outer circle is too short, and the phenomenon that the inner circle and the outer circle are overlapped easily occurs to the algorithm during detection. Because the inner circle formed by the silver paste printed on the piezoelectric ceramic plate is generally very close to the outer circle of the ceramic plate, the condition that the inner circle is not detected or the outer circle is not detected easily occurs, and the concentricity of the inner circle and the outer circle cannot be calculated correctly; in addition, when the size of the circle changes, the method needs to adjust a plurality of parameters, and if the parameters are improperly set, the condition that the circle cannot be found easily occurs, so that concentricity cannot be calculated. As a series of products with wide application, the piezoelectric ceramic silver plates have various sizes, and the method can make it difficult for workers to correctly adjust parameters in the system, so that the system cannot work normally.
Disclosure of Invention
The invention mainly aims to overcome the defects and shortcomings of the prior art and provide the automatic detection method for the concentricity quality of the piezoelectric ceramic silver plates, which can automatically measure the concentricity of the piezoelectric ceramic silver plates with different sizes, and has the advantages of high identification accuracy and good reliability.
The invention further aims to provide a device for realizing the automatic detection method for the concentricity quality of the piezoelectric ceramic silver sheet, which is high in automation degree and high in working efficiency.
The aim of the invention is achieved by the following technical scheme: a method for automatically detecting concentricity quality of a piezoelectric ceramic silver sheet comprises the following steps:
(1) Initializing: judging whether the color of the current detection supporting plate is close to the color of the silver plating area of the piezoelectric ceramic silver plate, if so, placing the silver plating area of the piezoelectric ceramic silver plate to be detected on the detection supporting plate horizontally, arranging the detection supporting plate in the shooting view of a camera, and shooting by the camera to obtain an original image;
(2) Calculating excircle parameters: extracting an outline point set of a piezoelectric ceramic silver sheet to be detected in an original image, performing circle fitting to obtain a fitting excircle, and calculating the circle center and the radius of the fitting excircle;
(3) Solving an inner circle parameter: extracting an inner contour point set of a piezoelectric ceramic silver plate to be detected in an original image, performing circle fitting to obtain a fitting inner circle, and calculating the circle center and the radius of the fitting inner circle;
(4) And calculating concentricity of the inner and outer circles, and if the concentricity is larger than a preset threshold value, judging that the piezoelectric ceramic silver sheet to be detected currently is good, otherwise, judging that the piezoelectric ceramic silver sheet to be detected currently is waste.
Preferably, in the step (1), whether the color of the currently detected supporting plate is close to the color of the piezoelectric ceramic silver plating area is judged, and the judgment is carried out only once when the detected supporting plate is replaced, and the specific method is as follows: placing a piezoelectric ceramic silver sheet in the center of the detection supporting plate, acquiring an image by using a camera, positioning the circle center and the diameter of the outer circle of the piezoelectric ceramic silver sheet through Hough transformation, and counting the gray average value of all pixel points positioned in the outer circle as the gray average value of the piezoelectric ceramic silver sheet; and (3) expanding M pixels outwards from the outer circle to obtain an annular background area, counting the gray average value in the background area, comparing the gray average value with the gray average value of the piezoelectric ceramic silver plate, and recognizing that the color of the detection support plate is close to the color of the piezoelectric ceramic silver plating area when the gray difference between the gray average value and the gray average value is within the range of 30-50.
Preferably, in the step (2), the step of extracting the outer contour point set of the piezoelectric ceramic silver sheet to be detected in the original image is as follows:
(2-1) performing gaussian smoothing on an original image;
(2-2) performing edge detection on the smoothed image;
(2-3) detecting an outline point set of the piezoelectric ceramic silver sheet by using a topological principle and an edge tracking method, wherein the method specifically comprises the following steps: scanning the binary image detected by the edge in the step (2-2) row by row, wherein the boundary of the searched first pixel value, which is changed from 0 to 1, is the outer contour;
and (2-4) performing quadratic curve-based circle fitting according to the outer contour point set to obtain a fitting excircle, and recording the circle center and the radius of the fitting excircle.
Further, a canny edge detection algorithm is adopted in the step (2-2).
Further, considering that the edge detection in the step (2-2) may include some noise, in order to find the outer contour more accurately, the method is modified as follows: and (2-3) extracting all edges in the image obtained after edge detection, calculating the area of the area surrounded by each edge, and taking the edge corresponding to the maximum area as the outline of the piezoelectric ceramic silver sheet.
Preferably, in the step (3), the step of extracting the inner contour point set of the piezoelectric ceramic silver sheet to be detected in the original image is as follows:
(3-1) performing gaussian smoothing on the original image;
(3-2) performing morphological closing operation on the smoothed image by using a rectangular kernel by utilizing the characteristic that the color of the detection support plate is close to that of the silver plating area of the piezoelectric ceramic silver plate, so that only the silver plating area of the piezoelectric ceramic silver plate is reserved in the image;
(3-3) performing edge detection on the image obtained in the step (3-2);
(3-4) extracting edges of silver plating areas of the piezoelectric ceramic silver plates, namely inner contour point sets;
and (3-5) performing quadratic curve-based circle fitting according to the inner contour point set to obtain a fitting inner circle, and recording the circle center and the radius of the fitting inner circle.
Further, a canny edge detection algorithm is adopted in the step (3-3).
Further, considering that the edge detection in the step (3-3) may include some noise, in order to find the outer contour more accurately, the method is modified as follows: and (3-4) extracting all edges in the image obtained after edge detection, calculating the area of the area surrounded by each edge, and taking the edge corresponding to the maximum area as the edge of the silver plating area of the piezoelectric ceramic silver sheet.
Preferably, in the step (4), the formula for calculating the concentricity c of the inner and outer circles is:
c＝1-((x1-x2) 2 +(y1-y2) 2 )/(R-r) 2
wherein (x 1, y 1) is the center of the outer circle, R is the radius of the outer circle, (x 2, y 2) is the center of the inner circle, R is the radius of the inner circle, and the value range of concentricity c is [0,1].
In order to improve detection efficiency, N piezoelectric ceramic silver plates to be detected are placed on a detection supporting plate at a time according to a set arrangement mode, the position of each piezoelectric ceramic silver plate to be detected in an image is determined according to the arrangement rule of central coordinates of each piezoelectric ceramic silver plate, and the steps of extracting inner and outer contours are as follows:
step (2-2) after all edges in the image are extracted, calculating the area of an area surrounded by each edge, sequencing the areas from large to small, and selecting a point set corresponding to N edges with the largest area as an outer contour point set of N piezoelectric ceramic silver plates to be detected;
and (3-3) after all edges in the image are extracted, calculating the area of an area surrounded by each edge, sequencing according to the area from large to small, and selecting a point set corresponding to the N edges with the largest area as an inner contour point set of N piezoelectric ceramic silver plates to be detected.
The device for realizing the automatic detection method of the concentricity quality of the piezoelectric ceramic silver sheet comprises a controller, a workbench, a camera device, a detection supporting plate and a manipulator, wherein the controller is respectively connected with the camera device and the manipulator, the workbench is provided with a detection area, the detection supporting plate is arranged at the detection area, and the camera device is fixed above the detection supporting plate; during detection, the silver plating surface of the piezoelectric ceramic silver sheet to be detected faces upwards, and the piezoelectric ceramic silver sheet to be detected is placed on a detection supporting plate in a certain arrangement mode, and the color of the detection supporting plate is close to that of a silver plating area of the piezoelectric ceramic silver sheet; the tail end of the manipulator is provided with a sucker, and a plurality of suction nozzles are arranged on the sucker in the same arrangement mode according to the arrangement of the piezoelectric ceramic silver plates to be detected on the detection supporting plate; a good product area is arranged on one side of the detection area, the detection supporting plate can rotate under the control of the controller, and a waste frame is arranged on the lower side of the rotation direction of the detection supporting plate; the controller detects each piezoelectric ceramic silver piece according to the automatic detection method for the concentricity quality of the piezoelectric ceramic silver pieces, judges the positions of good products according to detection results, then sends signals to the mechanical arm, the mechanical arm starts the corresponding suction nozzle to suck the good products and convey the good products to the good product area, and then the controller controls the detection support plate to rotate so that the rest waste products fall into the waste frame.
Compared with the prior art, the invention has the following advantages and beneficial effects:
(1) The invention can finish concentricity measurement by only one CCD camera without other sensors.
(2) The method can automatically separate the outline of the inner circle from the outline of the outer circle of the piezoelectric ceramic silver piece, and can well solve the problem that the inner circle and the outer circle are mixed together and cannot be distinguished correctly in the traditional algorithm when the piezoelectric ceramic silver piece is smaller.
(3) The circle center and the radius are determined by performing circle fitting on the separated inner and outer circular outlines, the concentricity of the piezoelectric ceramic silver plates with different sizes can be automatically measured without adjusting parameters, the application range is wide, and the operation is simple.
(4) The invention has high recognition accuracy, can greatly improve the degree of automatic detection and improves the production efficiency.
(5) According to the invention, the mechanical arm with the sucker is adopted, so that the grabbing of good products after detection can be realized, and meanwhile, the detection supporting plate can rotate under the control of the controller, so that the automatic screening of the good products and the waste products is realized, and the automatic screening device has the advantage of high efficiency.
Drawings
Fig. 1 is a schematic diagram of the system components of the device for automatically detecting the concentricity quality of a piezoelectric ceramic silver sheet according to the present embodiment.
Fig. 2 is a flowchart of the automatic concentricity measurement operation according to the present embodiment.
Fig. 3 is a flowchart of an algorithm of concentricity detection according to the present embodiment.
Fig. 4 is a flowchart of the concentricity detection algorithm according to the present embodiment.
Fig. 5 is a flowchart of the concentricity detection algorithm according to the present embodiment.
Fig. 6 is an original image, a gaussian filter result image and a morphological filter result image of the piezoelectric ceramic silver plate in the method of the present embodiment.
Detailed Description
The present invention will be described in further detail with reference to examples and drawings, but embodiments of the present invention are not limited thereto.
Example 1
As shown in fig. 1, the device for automatically detecting concentricity quality of a piezoelectric ceramic silver sheet according to the embodiment comprises a PC 1, a camera 2, a workbench 3, a detection supporting plate 4, a good product area 5, a waste frame 6 and a manipulator 7. The camera 2 is arranged above the detection supporting plate 4, and the specific height can be comprehensively considered and set according to parameters of the camera, the size of the piezoelectric ceramic silver sheet to be detected and other factors, for example, the specific height can be set to be 30-50cm. The PC 1 is respectively connected with the camera 2 and the manipulator 7 in a wired or wireless mode, and is used for receiving images shot by the camera 2, carrying out quality detection on the concentricity of the piezoelectric ceramic silver plates in the current image based on an image processing mode, judging the position of good products according to a quality detection result, then sending a signal to the manipulator 2, opening a corresponding suction nozzle by the manipulator 2 to suck and convey the good products into a good product area 5, and enabling the rest waste products to fall into a waste frame 6.
In this embodiment, a slide rail is disposed on one side of the workbench 3, the good product area 5 and the waste frame 6 are disposed at two ends of the workbench 3 respectively, the manipulator 7 slides along the slide rail between the detection support plate 4 and the good product area 5, and when the camera 2 shoots, the manipulator 2 stops above the good product area 5. One side of the detection support plate 4 is fixed on a rotating shaft which is controlled by a driving motor which is connected with the PC 1. When the waste on the detection supporting plate needs to be removed, a signal is sent to a driving motor through the PC 1, the driving motor drives a rotating shaft to rotate, and then the detection supporting plate 4 is driven to rotate, and the waste frame 6 is arranged on the lower side of the rotation direction of the detection supporting plate 4, so that the waste automatically falls into the waste frame 6.
In order to facilitate the suction of good products, the silver-plated surfaces of the piezoelectric ceramic silver plates to be detected on the detection supporting plate 4 face upwards, are horizontally arranged on the detection supporting plate 4 at equal intervals, and have the interval of 5-8mm, and particularly, the size of the piezoelectric ceramic silver plates to be detected, the detection area and the size of the detection supporting plate can be adaptively adjusted. The arrangement mode of the suction nozzles on the suction disc of the manipulator 7 is the same as the arrangement mode. And the detection supporting plate 4 adopts a silver flat plate, and the color of the detection supporting plate is close to that of a silver plating area of the piezoelectric ceramic silver plate. Thereby facilitating subsequent image detection.
In addition, in order to further improve efficiency, the process of placing the piezoelectric ceramic silver sheet to be detected on the detection supporting plate can be realized by adopting a mechanical arm auxiliary feeding device, and the device can directly adopt the existing mechanical arm device, so that the repeated description is omitted.
Similarly, in order to improve the use convenience of the device, in this embodiment, a man-machine interaction device is further provided at the PC 1, where the man-machine interaction device includes a user input device and a display device, and existing devices such as a keyboard, a touch screen, and a display screen may be directly adopted, so that input and output of information may be implemented, where the input information includes, but is not limited to, a type of a piezoelectric ceramic silver sheet to be detected currently, preset values necessary for detecting various defects, and the like, and the output information includes, but is not limited to, a currently collected image of a detection support plate, a process diagram and a result diagram for detecting and identifying, and information such as yield, defect type, and the like. Specifically, the setting can be performed by the operator according to the actual application, and will not be described herein.
As shown in fig. 2, the automatic detection method for the concentricity quality of the piezoelectric ceramic silver sheet, which is realized by the device, comprises the following steps:
(1) Initializing a system, and checking connection of a camera and a PC and installation of camera driving software; checking whether the manipulator is placed in the good product area;
(2) The silver-plated surface of the piezoelectric ceramic silver sheet faces upwards and is horizontally arranged on the detection supporting plate at equal intervals, wherein the intervals can be 5-8mm;
(3) Setting concentricity detection thresholds of good products and unqualified products according to the product model;
(4) Shooting all piezoelectric ceramic silver sheets on the detection support plate into an image by the camera, marking the image as an original image, and transmitting the original image to a memory of a PC;
(5) Measuring concentricity values of the piezoelectric ceramic silver plates in the image;
(6) Comparing the concentricity values of the piezoelectric ceramic silver pieces measured in the step (5) with the threshold value set in the step (3) one by one, judging whether the piezoelectric ceramic silver pieces belong to good products or unqualified products, and storing the judging result;
(7) The PC controls the mechanical arm to absorb all the good piezoelectric ceramic silver plates and send the good piezoelectric ceramic silver plates to a good area;
(8) And the supporting plate is detected in a tilting way, so that unqualified products slide to the waste frame.
In practical application, in order to facilitate subsequent image processing, when the detection support plate is replaced, whether the color of the current detection support plate is close to the color of the piezoelectric ceramic silver-plated area or not needs to be judged, and the specific method is as follows: placing a piezoelectric ceramic silver sheet in the center of the detection supporting plate, acquiring an image by using a camera, positioning the circle center and the diameter of the outer circle of the piezoelectric ceramic silver sheet through Hough transformation, and counting the gray average value of all pixel points positioned in the outer circle as the gray average value of the piezoelectric ceramic silver sheet; and expanding 50 pixels outwards from the outer circle to obtain an annular background area, counting the gray average value in the background area, comparing the gray average value with the gray average value of the piezoelectric ceramic silver plate, and recognizing that the color of the detection support plate is close to the color of the piezoelectric ceramic silver plate area when the gray difference between the gray average value and the gray average value is within the range of 30-50.
The step (5) further comprises the following steps, see fig. 3:
(5-1) extracting an outline point set of the piezoelectric ceramic silver plate to be detected in an original image, performing circle fitting to obtain a fitting excircle, and calculating the circle center and the radius of the fitting excircle;
(5-2) extracting an inner contour point set of the piezoelectric ceramic silver plate to be detected in the original image, performing circle fitting to obtain a fitting inner circle, and calculating the circle center and the radius of the fitting inner circle;
(5-3) calculating concentricity of the inner and outer circles, if the concentricity is larger than a preset threshold value, judging that the piezoelectric ceramic silver sheet to be detected currently is good, otherwise, judging that the piezoelectric ceramic silver sheet is waste, and calculating a formula of concentricity c of the inner and outer circles is as follows:
c＝1-((x1-x2) 2 +(y1-y2) 2 )/(R-r) 2
wherein (x 1, y 1) is the center of the outer circle, R is the radius of the outer circle, (x 2, y 2) is the center of the inner circle, R is the radius of the inner circle, and the value range of concentricity c is [0,1].
Referring to fig. 4, the specific steps for determining the excircle parameters in step (5-1) are as follows:
(5-1-1) Gaussian smoothing of the original image.
(5-1-2) detecting edges of the smoothed image using a canny edge detection algorithm.
(5-1-3) detecting the outline point set of each piezoelectric ceramic silver piece by using a topological principle and an edge tracking method.
In the embodiment, 25 piezoelectric ceramic silver plates to be detected are placed on a detection supporting plate at one time according to a 5×5 arrangement mode, and when detection is performed, the position of each piezoelectric ceramic silver plate to be detected is determined according to the arrangement rule of the center coordinates of the piezoelectric ceramic silver plates from left to right and from top to bottom.
As a scheme, in the ideal working condition, a binary image after edge detection in the step (5-1-2) is scanned row by row and column by column in each piezoelectric ceramic silver sheet area to be detected, and the boundary of the first pixel value which is searched from 0 to 1 is the outer contour. The method is simple to implement and low in calculation complexity, but has high requirements on experimental environments.
As another scheme, under the condition that noise points are considered, all edges in an image obtained after edge detection can be extracted by utilizing the characteristic that the area of an area surrounded by an outer contour point set of a piezoelectric ceramic silver sheet is larger than that of an area surrounded by the outer contour point set of noise, the area of the area surrounded by each edge is calculated, the areas are ordered according to the size of the areas, and the point set corresponding to 25 edges with the largest area is selected as the outer contour point set of 25 piezoelectric ceramic silver sheets to be detected. The method has low requirements on experimental environment.
(5-1-4) performing quadratic curve-based circle fitting on each outer contour point set obtained in the step (5-1-3) to obtain a fitting excircle of each piezoelectric ceramic silver sheet.
And (5-1-5) calculating the circle center and the radius of each fitting excircle obtained in the step (5-1-4), and determining the circle center and the radius of each piezoelectric ceramic silver piece excircle.
Referring to fig. 5, the specific steps for obtaining the inner circle parameters in step (5-2) are as follows:
(5-2-1) Gaussian smoothing the original image.
(5-2-2) using a rectangular kernel to perform morphological closing operation on the smoothed image by using the characteristic that the color of the detection support plate is close to that of the silver-plated region of the piezoelectric ceramic silver sheet, so that only the silver-plated region of the piezoelectric ceramic silver sheet is reserved in the image. See fig. 6, wherein the first behavior is an original graph, the second behavior is a gaussian filtering result graph, and the third behavior is a morphological closing operation result graph.
(5-2-3) edge detection is performed on the image after morphological closing operation by using a canny edge detection algorithm.
(5-2-4) detecting the contour point set of each silver-plated area of the piezoelectric ceramic sheet by using a topological principle and an edge tracking method.
Similarly, in order to avoid noise influence, all edges in an image obtained after edge detection can be extracted by utilizing the characteristic that the area of an area surrounded by an inner contour point set of a piezoelectric ceramic silver sheet is larger than that of an area surrounded by the inner contour point set of noise, the area of the area surrounded by each edge is calculated, the areas are ordered from large to small, and the point set corresponding to 25 edges with the largest area is selected as the inner contour point set of 25 piezoelectric ceramic silver sheets to be detected. The method has low requirements on experimental environment.
(5-2-5) performing quadratic curve-based circle fitting on each inner contour point set obtained in the step (5-2-4) to obtain fitting circles of silver plating areas of each piezoelectric ceramic sheet;
and (5-2-6) calculating the circle center and the radius of the fitting circle of each silver plating area to be determined as the circle center and the radius of the inner circle of each piezoelectric ceramic silver piece.
The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above examples, and any other changes, modifications, substitutions, combinations, and simplifications that do not depart from the spirit and principle of the present invention should be made in the equivalent manner, and the embodiments are included in the protection scope of the present invention.
Claims (5)
1. The automatic detection method for the concentricity quality of the piezoelectric ceramic silver sheet is characterized by comprising the following steps:
(1) Initializing: judging whether the color of the current detection supporting plate is close to the color of the silver plating area of the piezoelectric ceramic silver plate, if so, placing the silver plating area of the piezoelectric ceramic silver plate to be detected on the detection supporting plate horizontally, arranging the detection supporting plate in the shooting view of a camera, and shooting by the camera to obtain an original image;
(2) Calculating excircle parameters: extracting an outline point set of a piezoelectric ceramic silver sheet to be detected in an original image, performing circle fitting to obtain a fitting excircle, and calculating the circle center and the radius of the fitting excircle;
(3) Solving an inner circle parameter: extracting an inner contour point set of a piezoelectric ceramic silver plate to be detected in an original image, performing circle fitting to obtain a fitting inner circle, and calculating the circle center and the radius of the fitting inner circle;
(4) Calculating concentricity of the inner circle and the outer circle, if the concentricity is larger than a preset threshold value, judging that the piezoelectric ceramic silver sheet to be detected currently is good, otherwise, judging that the piezoelectric ceramic silver sheet to be detected currently is waste; the formula for calculating the concentricity c of the inner and outer circles is as follows:
c＝1-((x1-x2) 2 +(y1-y2) 2 )/(R-r) 2
wherein (x 1, y 1) is the center of the outer circle, R is the radius of the outer circle, (x 2, y 2) is the center of the inner circle, R is the radius of the inner circle, and the value range of concentricity c is [0,1];
in the step (1), judging whether the color of the current detection supporting plate is close to the color of the piezoelectric ceramic silver plating area, and judging once only when the detection supporting plate is replaced, wherein the specific method is as follows: placing a piezoelectric ceramic silver sheet in the center of the detection supporting plate, acquiring an image by using a camera, positioning the circle center and the diameter of the outer circle of the piezoelectric ceramic silver sheet through Hough transformation, and counting the gray average value of all pixel points positioned in the outer circle as the gray average value of the piezoelectric ceramic silver sheet; starting to expand M pixels outwards from the outer circle to obtain an annular background area, counting the gray average value in the background area, comparing the gray average value with the gray average value of the piezoelectric ceramic silver plate, and recognizing that the color of the detection support plate is close to the color of the piezoelectric ceramic silver plating area when the gray difference between the gray average value and the gray average value is within the range of 30-50;
in the step (2), the step of extracting the outline point set of the piezoelectric ceramic silver plate to be detected in the original image is as follows:
(2-1) performing gaussian smoothing on an original image;
(2-2) performing edge detection on the smoothed image;
(2-3) detecting an outline point set of the piezoelectric ceramic silver sheet by using a topological principle and an edge tracking method, wherein the method specifically comprises the following steps: scanning the binary image detected by the edge in the step (2-2) row by row, wherein the boundary of the searched first pixel value, which is changed from 0 to 1, is the outer contour;
(2-4) performing quadratic curve-based circle fitting according to the outer contour point set to obtain a fitting excircle, and recording the circle center and the radius of the fitting excircle;
extracting all edges in the image obtained after edge detection, calculating the area of the area surrounded by each edge, and taking the edge corresponding to the maximum area as the outline of the piezoelectric ceramic silver sheet;
in the step (3), the step of extracting the inner contour point set of the piezoelectric ceramic silver plate to be detected in the original image is as follows:
(3-1) performing gaussian smoothing on the original image;
(3-2) performing morphological closing operation on the smoothed image by using a rectangular kernel by utilizing the characteristic that the color of the detection support plate is close to that of the silver plating area of the piezoelectric ceramic silver plate, so that only the silver plating area of the piezoelectric ceramic silver plate is reserved in the image;
(3-3) performing edge detection on the image obtained in the step (3-2);
(3-4) extracting edges of silver plating areas of the piezoelectric ceramic silver plates, namely inner contour point sets;
and (3-5) performing quadratic curve-based circle fitting according to the inner contour point set to obtain a fitting inner circle, and recording the circle center and the radius of the fitting inner circle.
2. The method for automatically detecting the concentricity of the silver plates according to claim 1, wherein the canny edge detection algorithm is adopted in the step (2-2).
3. The automatic detection method for the concentricity quality of the piezoelectric ceramic silver sheet according to claim 1, wherein the step (3-3) adopts a canny edge detection algorithm;
and (3-4) extracting all edges in the image obtained after edge detection, calculating the area of the area surrounded by each edge, and taking the edge corresponding to the maximum area as the edge of the silver plating area of the piezoelectric ceramic silver sheet.
4. The automatic detection method for the concentricity quality of the piezoelectric ceramic silver plates according to claim 1, wherein the detection support plate is provided with N piezoelectric ceramic silver plates to be detected at a time according to a set arrangement mode, the position of each piezoelectric ceramic silver plate to be detected in an image is determined according to the arrangement rule of the central coordinates of each piezoelectric ceramic silver plate, and the steps of extracting the inner contour and the outer contour are as follows:
step (2-2) after all edges in the image are extracted, calculating the area of an area surrounded by each edge, sequencing the areas from large to small, and selecting a point set corresponding to N edges with the largest area as an outer contour point set of N piezoelectric ceramic silver plates to be detected;
and (3-3) after all edges in the image are extracted, calculating the area of an area surrounded by each edge, sequencing according to the area from large to small, and selecting a point set corresponding to the N edges with the largest area as an inner contour point set of N piezoelectric ceramic silver plates to be detected.
5. A device for realizing the automatic detection method of the concentricity quality of the piezoelectric ceramic silver sheet according to any one of claims 1 to 4, which is characterized by comprising a controller, a workbench, a camera device, a detection supporting plate and a manipulator, wherein the controller is respectively connected with the camera device and the manipulator, a detection area is arranged on the workbench, the detection supporting plate is arranged at the detection area, and the camera device is fixed above the detection supporting plate; during detection, the silver plating surface of the piezoelectric ceramic silver sheet to be detected faces upwards, and the piezoelectric ceramic silver sheet to be detected is placed on a detection supporting plate in a certain arrangement mode, and the color of the detection supporting plate is close to that of a silver plating area of the piezoelectric ceramic silver sheet; the tail end of the manipulator is provided with a sucker, and a plurality of suction nozzles are arranged on the sucker in the same arrangement mode according to the arrangement of the piezoelectric ceramic silver plates to be detected on the detection supporting plate; a good product area is arranged on one side of the detection area, the detection supporting plate can rotate under the control of the controller, and a waste frame is arranged on the lower side of the rotation direction of the detection supporting plate; the controller detects each piezoelectric ceramic silver piece according to the automatic detection method for the concentricity quality of the piezoelectric ceramic silver pieces according to any one of claims 1-4, judges the position of a good product according to the detection result, then sends a signal to the manipulator, the manipulator starts a corresponding suction nozzle to suck the good product and convey the good product to a good product area, and then the controller controls the detection support plate to rotate so that the rest waste products fall into a waste frame.
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Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0000259A1 (en) * | 1977-06-23 | 1979-01-10 | Europäische Atomgemeinschaft (Euratom) | Process and apparatus for the alignment of a transducer forming part of a radiation generator |
| US5335298A (en) * | 1991-08-19 | 1994-08-02 | The United States Of America As Represented By The Secretary Of The Army | Automated extraction of airport runway patterns from radar imagery |
| JP2002318195A (en) * | 2001-04-19 | 2002-10-31 | Murata Mfg Co Ltd | External appearance inspection method and external appearance inspection device |
| US6489705B1 (en) * | 2001-06-26 | 2002-12-03 | National Science Council Of Republic Of China | Thin-disc piezoelectric actuating ultrasonic motor |
| JP2003303342A (en) * | 2002-04-10 | 2003-10-24 | Tateyama Machine Kk | Method and apparatus for detecting reference position of annular image by omnidirectional imaging |
| CN101699217A (en) * | 2009-11-03 | 2010-04-28 | 武汉大学 | Method used for detecting concentric circle of industrial part |
| CN102353349A (en) * | 2011-09-30 | 2012-02-15 | 广东工业大学 | Machine vision based micro-sound film concentricity online testing system and testing method |
| CN103439337A (en) * | 2013-08-29 | 2013-12-11 | 华南理工大学 | Automatic detection device and method for apparent defects of piezoelectric ceramic buzzers |
| CN105335976A (en) * | 2015-10-23 | 2016-02-17 | 广州视睿电子科技有限公司 | Image processing method and device |
| CN105469046A (en) * | 2015-11-23 | 2016-04-06 | 电子科技大学 | Vehicle model identification method based on PCA and SURF characteristic cascade |
| CN105930791A (en) * | 2016-04-19 | 2016-09-07 | 重庆邮电大学 | Road traffic sign identification method with multiple-camera integration based on DS evidence theory |
-
2017
- 2017-03-10 CN CN201710141152.7A patent/CN107101598B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0000259A1 (en) * | 1977-06-23 | 1979-01-10 | Europäische Atomgemeinschaft (Euratom) | Process and apparatus for the alignment of a transducer forming part of a radiation generator |
| US5335298A (en) * | 1991-08-19 | 1994-08-02 | The United States Of America As Represented By The Secretary Of The Army | Automated extraction of airport runway patterns from radar imagery |
| JP2002318195A (en) * | 2001-04-19 | 2002-10-31 | Murata Mfg Co Ltd | External appearance inspection method and external appearance inspection device |
| US6489705B1 (en) * | 2001-06-26 | 2002-12-03 | National Science Council Of Republic Of China | Thin-disc piezoelectric actuating ultrasonic motor |
| JP2003303342A (en) * | 2002-04-10 | 2003-10-24 | Tateyama Machine Kk | Method and apparatus for detecting reference position of annular image by omnidirectional imaging |
| CN101699217A (en) * | 2009-11-03 | 2010-04-28 | 武汉大学 | Method used for detecting concentric circle of industrial part |
| CN102353349A (en) * | 2011-09-30 | 2012-02-15 | 广东工业大学 | Machine vision based micro-sound film concentricity online testing system and testing method |
| CN103439337A (en) * | 2013-08-29 | 2013-12-11 | 华南理工大学 | Automatic detection device and method for apparent defects of piezoelectric ceramic buzzers |
| CN105335976A (en) * | 2015-10-23 | 2016-02-17 | 广州视睿电子科技有限公司 | Image processing method and device |
| CN105469046A (en) * | 2015-11-23 | 2016-04-06 | 电子科技大学 | Vehicle model identification method based on PCA and SURF characteristic cascade |
| CN105930791A (en) * | 2016-04-19 | 2016-09-07 | 重庆邮电大学 | Road traffic sign identification method with multiple-camera integration based on DS evidence theory |
Non-Patent Citations (3)
| Title |
|---|
| 基于机器视觉的小型元器件同心度测量仪的设计;林奇鸿等;《传感器与仪器仪表》;20091231;第25卷(第11-1期);第117-118、142页 * |
| 杨帆等.《数字图像处理与分析》.北京航空航天大学出版社,2007,第45-46页. * |
| 林奇鸿等.基于机器视觉的小型元器件同心度测量仪的设计.《传感器与仪器仪表》.2009,第25卷(第11-1期),第117-118、142页. * |
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