CN111754490A - Graphite boat sheet-reversing detection method, device and system based on vision - Google Patents
Graphite boat sheet-reversing detection method, device and system based on vision Download PDFInfo
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Abstract
The invention discloses a graphite boat sheet-rewinding detection method, a device and a system based on vision, which belong to the technical field of tubular PECVD equipment and are used for solving the technical problems of complex structure and low detection precision of the conventional sheet-rewinding detection, and the method comprises the following steps: acquiring graphite boat images acquired at different positions of a graphite boat; 2) processing the images of the graphite boats to obtain a larger distance value between the edge of the silicon wafer in the image of the graphite boat and the edge of the nearer graphite boat groove; 3) and judging whether the silicon wafer in the corresponding graphite boat groove has a reverse wafer or not based on the larger distance value. The invention has the advantages of high detection precision, high detection reliability and the like.
Description
Technical Field
The invention mainly relates to the technical field of tubular PECVD equipment, in particular to a graphite boat sheet inversion detection method, a graphite boat sheet inversion detection device and a graphite boat sheet inversion detection system based on vision.
Background
The PECVD equipment is coating deposition equipment in semiconductor processing, can be applied to a silicon wafer coating process of a photovoltaic cell, and improves the power generation efficiency of the photovoltaic cell. The existing tubular PECVD equipment adopts a graphite boat to bear a silicon wafer for coating process production, and automatic material loading and unloading of the graphite boat are realized by connecting an automatic loading and unloading system of the equipment with a transmission belt of an automatic wafer inserting machine. The graphite boat carries out the silicon chip inserted sheet through automatic film inserting machine, carries to the automatic material system from top to bottom of PECVD through the transmission band again, snatchs the graphite boat to pushing away on the boat mechanism through crossing the manipulator at last to realize the automatic material from top to bottom of graphite boat. In the transmission process of the graphite boat, because mechanical vibration or improper insertion of a sheet inserting machine cause the situation that a silicon wafer is possibly inverted in the graphite boat, the inverted silicon wafer can cause bad film coating, the product quality is affected, and the product cost is increased, so that the phenomenon of inversion in the graphite boat needs to be detected before the graphite boat enters a furnace for carrying out a process.
The conventional device for detecting the reverse of the graphite boat is complex and can only detect the completely-toppled reverse, for example, in the invention patent application of 'a graphite boat side-out mechanism 201611117340.8 with a reverse detection device', a plurality of photoelectric switches are arranged above the graphite boat, a plurality of light reflecting seats are arranged below the graphite boat, and when the graphite boat moves below the photoelectric switches, if no reverse exists in the graphite boat, light emitted by the photoelectric switches can penetrate through grooves in the graphite boat, irradiate the grooves on the light reflecting seats and reflect the light reflecting seats back to the photoelectric switches, so that the detection of the reverse is realized. However, the structure of the solution is complex, the silicon wafer inversion with a large inclination angle can only be detected under the influence of the installation precision and the detection precision of the photoelectric switch, the silicon wafer inversion with a small inclination angle or unstable placement cannot be detected, and the inversion detection rate cannot meet the requirement.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides a vision-based graphite boat inverted sheet detection method, device and system with high detection precision and high detection reliability.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a graphite boat sheet-pouring detection method based on vision comprises the following steps:
1) acquiring graphite boat images acquired at different positions of a graphite boat;
2) processing the images of the graphite boats to obtain a larger distance value between the edge of the silicon wafer in the image of the graphite boat and the edge of the nearer graphite boat groove;
3) and judging whether the silicon wafer in the corresponding graphite boat groove has a reverse wafer or not based on the larger distance value.
As a further improvement of the above technical solution:
in step 2), the specific process of image processing is as follows:
2.1) image calibration correction: calibrating the position coordinates of the peripheral edge of the graphite boat in the image, respectively carrying out trapezoidal correction on the two pictures according to edge positioning, and intercepting the image within the edge line of the graphite boat;
2.2) image segmentation and interception: respectively segmenting and intercepting each graphite boat image subjected to coordinate calibration and trapezoidal correction, segmenting and identifying each graphite boat groove for placing the silicon wafer according to image coordinates, and obtaining n-m 'groove images (n, m)';
2.3) image gray processing: graying the intercepted 'groove image (n, m)', and converting the color image into a grayscale image;
2.4) edge detection filtering: carrying out edge detection filtering on the single 'groove image (n, m)', and carrying out binarization processing on the filtered image to form the 'groove image (n, m)', after edge detection;
2.5) image synthesis: superposing the 'groove images (n, m)' extracted by cutting each image to synthesize a new 'groove image (n, m)', and then carrying out image splicing on the new 'groove image (n, m)' according to the number of rows and columns to synthesize a final graphite boat binary image;
2.6) detecting the offset distance of the silicon chip: and extracting the silicon wafer edge image in the binary image of the graphite boat, and calculating a larger distance value k (n, m) between the edge of the silicon wafer and the edge of the nearer graphite boat groove.
In step 2.1), the coordinate of the peripheral edge of the graphite boat in the image is calibrated by identifying the coordinate mark preset at the edge of the graphite boat in each image.
In step 2.2), the process of segmenting and identifying is as follows: and calibrating and placing a silicon wafer slot space image according to the image coordinate, segmenting the image, extracting a single slot space image by adopting a mask algorithm, and extracting n-m slot images (n, m).
In step 2.5), the pixels of each pixel point are added and averaged to realize the superposition of the "slot image (n, m)".
In step 2.6), the number of pixels spaced by two edge lines is converted into the actual spacing position distance to obtain a larger distance value k (n, m).
The specific process of the step 3) is as follows:
taking an average value k (avg) of the larger distance values of the distances between the edges of the silicon wafers and the edges of the grooves;
calculating the deviation k1(n, m) from the groove edge of each silicon chip, wherein k (n, m) -k (avg); if the deviation k1(n, m) is larger than a preset threshold k2, the silicon wafer in the (n, m) -th groove is judged to be a reverse wafer.
In step 1), graphite boat images collected at both end positions of the graphite boat are acquired.
The invention also discloses a graphite boat sheet inversion detection device based on vision, which comprises:
the acquisition module is used for acquiring graphite boat images acquired at different positions of the graphite boat;
the image processing module is used for carrying out image processing on each graphite boat image to obtain a larger distance value between the edge of the silicon wafer in the graphite boat image and the edge of the nearer graphite boat groove;
and the judging module is used for judging whether the silicon wafers in the corresponding graphite boat grooves have the inverted wafers or not based on the larger distance value.
The invention further discloses a vision-based graphite boat sheet inversion detection system, which comprises an image acquisition assembly and the vision-based graphite boat sheet inversion detection device, wherein the image acquisition assembly comprises a plurality of image acquisition units which are arranged at different positions of a graphite boat to be detected.
Compared with the prior art, the invention has the advantages that:
according to the invention, the front images of the silicon wafer graphite boat are collected at different positions, the collected images are processed by an image processing algorithm (including coordinate positioning, segmentation and interception, image filtering, edge detection, software ranging and the like) to detect the edge distance from the edge of the silicon wafer to the graphite boat groove, and whether the wafer is inverted is judged by the silicon wafer deviation distance; with the improvement of the visual acquisition precision, the detection precision can be correspondingly improved; in addition, images are acquired through a plurality of visions, so that mutual verification can be realized, and the reliability of detection is further improved.
Drawings
FIG. 1 is a flow chart of an embodiment of the method of the present invention.
FIG. 2 is an image of a cut silicon wafer slot of the present invention.
FIG. 3 is a block diagram of an embodiment of the detecting device of the present invention.
The reference numbers in the figures denote: 1. a support frame; 2. a graphite boat; 3. mounting a bracket; 4. a first image acquisition unit; 5. a second image acquisition unit.
Detailed Description
The invention is further described below with reference to the figures and the specific embodiments of the description.
As shown in fig. 1 and fig. 2, the method for detecting the inverted sheet of the graphite boat based on the vision of the embodiment includes the steps of:
1) acquiring images of the graphite boat 2 collected at different positions of the graphite boat 2;
2) processing the images of the graphite boats 2 to obtain a larger distance value between the edge of the silicon wafer in the image of the graphite boat 2 and the edge of the nearer graphite boat groove;
3) and judging whether the silicon wafer in the corresponding graphite boat groove has a reverse wafer or not based on the larger distance value.
According to the invention, the front images of the silicon wafer graphite boat 2 are acquired at different positions, the acquired images are processed by an image processing algorithm to detect the edge distance from the edge of the silicon wafer to the edge of the graphite boat groove, and the silicon wafer deviation distance is used for judging whether the wafer is inverted; with the improvement of the visual acquisition precision, the detection precision can be correspondingly improved; in addition, images are acquired through a plurality of visions, so that mutual verification can be realized, and the reliability of detection is further improved.
In this embodiment, in step 2), the specific process of image processing is as follows:
2.1) image calibration correction: calibrating the position coordinates of the peripheral edge of the graphite boat 2 in the image, respectively carrying out trapezoidal correction on the two pictures according to edge positioning, and intercepting the image within the edge line of the graphite boat 2; specifically, the position coordinates of the peripheral edge of the graphite boat 2 in the image are calibrated by identifying the coordinate marks preset at the edge of the graphite boat 2 in each image;
2.2) image segmentation and interception: respectively segmenting and intercepting each image of the graphite boat 2 subjected to coordinate calibration and trapezoidal correction, segmenting and identifying each graphite boat groove for placing the silicon wafer according to image coordinates, and obtaining n-m groove images (n, m);
2.3) image gray processing: graying the intercepted 'groove image (n, m)', and converting the color image into a grayscale image;
2.4) edge detection filtering: carrying out edge detection filtering on the single 'groove image (n, m)', and carrying out binarization processing on the filtered image to form the 'groove image (n, m)', after edge detection;
2.5) image synthesis: superposing the 'groove images (n, m)' extracted by cutting each image to synthesize a new 'groove image (n, m)', and then carrying out image splicing on the new 'groove image (n, m)' according to the number of rows and columns to synthesize a final binary image of the graphite boat 2;
2.6) detecting the offset distance of the silicon chip: and (3) extracting the silicon wafer edge image in the binary image of the graphite boat 2, and calculating a larger distance value k (n, m) of the distance between the silicon wafer edge and the edge of the nearer graphite boat groove.
In this embodiment, in step 2.2), the process of segmenting and identifying is as follows: and calibrating and placing a silicon wafer slot space image according to the image coordinate, segmenting the image, extracting a single slot space image by adopting a mask algorithm, and extracting n-m slot images (n, m).
In this embodiment, in step 2.5), the pixels of each pixel are added and averaged to realize the superposition of the "slot image (n, m)"; in step 2.6), the number of pixels spaced by two edge lines is converted into the actual spacing position distance to obtain a larger distance value k (n, m).
In this embodiment, the specific process of step 3) is as follows:
taking an average value k (avg) of the larger distance values of the distances between the edges of the silicon wafers and the edges of the grooves;
calculating the deviation k1(n, m) from the groove edge of each silicon chip, wherein k (n, m) -k (avg); if the deviation k1(n, m) is larger than a preset threshold k2, the silicon wafer in the (n, m) -th groove is judged to be a reverse wafer.
In this embodiment, in step 1), images of the graphite boat 2 collected at both end positions of the graphite boat 2 are acquired.
The invention also discloses a graphite boat sheet inversion detection device based on vision, which comprises:
the acquisition module is used for acquiring images of the graphite boat 2 acquired at different positions of the graphite boat 2;
the image processing module is used for carrying out image processing on the images of the graphite boats 2 to obtain a larger distance value between the edge of the silicon wafer in the image of the graphite boat 2 and the edge of the nearer graphite boat groove;
and the judging module is used for judging whether the silicon wafers in the corresponding graphite boat grooves have the inverted wafers or not based on the larger distance value.
As shown in fig. 3, the present invention further discloses a vision-based graphite boat sheet inversion detection system, which comprises an image acquisition assembly and the vision-based graphite boat sheet inversion detection apparatus, wherein the image acquisition assembly comprises a plurality of image acquisition units, and the image acquisition units are installed at different positions of the graphite boat 2 to be detected. Wherein graphite boat 2 is placed on support frame 1, and support frame 1 adopts high temperature resistant carborundum pole to constitute, and support frame 1 is installed and is put the boat device in getting, detects through moving graphite boat 2 to the position that awaits measuring on the support frame. In a specific embodiment, the number of the image acquisition units is two, and the two image acquisition units are respectively the first image acquisition unit 4 and the second image acquisition unit 5, which are both mounted at two ends of the graphite boat 2 to be detected through the mounting bracket 3, and are used for respectively acquiring images of silicon wafers loaded on the graphite boat 2 from two ends of the graphite boat 2, and the two images acquired from different positions have complementarity, so that the inverted wafers of the graphite boat 2 can be more reliably checked.
Specifically, the first image acquisition unit 4 and the second image acquisition unit 5 have the same structure and both include an ultra high definition camera and a fill light. In addition, the periphery of the graphite boat 2 is provided with obvious edge coordinate marks for subsequent image processing coordinate positioning. Of course, in other embodiments, three, four or more image capturing units may be used to capture images of the graphite boat 2 from different positions of the graphite boat 2, so as to improve the reliability of detection.
The method and apparatus of the present invention are further described below in conjunction with a full embodiment:
1. image acquisition: after the graphite boat 2 reaches the detection position, the first image acquisition unit 4 and the second image acquisition unit 5 start a light supplement lamp, and respectively acquire images of the graphite boat 2 through the ultra-high-definition camera, wherein the acquired images are a first image and a second image respectively;
2. calibrating and correcting the image: respectively identifying edge coordinate marks of the graphite boat 2 of the two images, calibrating position coordinates of the peripheral edge of the graphite boat 2, respectively performing trapezoidal correction on the two images according to edge positioning, and intercepting the image within an edge line of the graphite boat 2;
3. image segmentation and interception: the method comprises the following steps of respectively segmenting and intercepting two images of the graphite boat 2 subjected to coordinate calibration and trapezoidal correction, segmenting and identifying each groove for placing the silicon wafer according to image coordinates, and specifically comprises the following steps: marking a space image of a silicon wafer placing groove according to an image coordinate, dividing the image, extracting a single groove space image by adopting a mask algorithm, and extracting n x m pieces of groove images (n, m), wherein the size of the silicon wafer groove in FIG. 3 is 190mm x 11mm, the n x m pieces of silicon wafer groove images of the space image of the silicon wafer placing groove are extracted together and marked as the groove images (n, m);
4. image gray processing: graying the intercepted 'groove image (n, m)', and converting the color image into a grayscale image;
5. and (3) edge detection filtering: carrying out edge detection filtering on the single 'groove image (n, m)', wherein the filtering method can be a differential filter, a wavelet filter, a convolution filter and the like, and carrying out binarization processing on the filtered image to form the 'groove image (n, m)', after edge detection;
6. image synthesis: superposing the 'groove images (n, m)' of the images cut and extracted from the first image and the second image, namely adding pixels of each pixel point, then averaging, synthesizing a new 'groove image (n, m)', then carrying out image splicing on the new 'groove image (n, m)', and synthesizing a final binary image of the graphite boat 2;
7. detecting the offset distance of the silicon wafer: extracting the silicon wafer edge image in the binary image of the graphite boat 2, and calculating a larger distance value k (n, m) of the distance between the edge of the silicon wafer and the edge of the nearer graphite boat 2 groove (converting the number of pixel points separated by two edge lines into the actual distance of the spacing position);
8. and (4) rewinding extraction and judgment: averaging the edge distances of the spacing grooves of the edge images of the silicon wafers processed in the previous step, wherein the average value is k (avg), calculating the deviation k1(n, m) of the edge distance of each silicon wafer, namely k (n, m) -k (avg), and if the deviation k1(n, m) is larger than a threshold k2 (threshold setting is carried out according to actual conditions), judging that the silicon wafer in the (n, m) th groove is a reverse wafer.
The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above-mentioned embodiments, and all technical solutions belonging to the idea of the present invention belong to the protection scope of the present invention. It should be noted that modifications and embellishments within the scope of the invention may be made by those skilled in the art without departing from the principle of the invention.
Claims (10)
1. A graphite boat inversion detection method based on vision is characterized by comprising the following steps:
1) acquiring images of the graphite boat (2) collected at different positions of the graphite boat (2);
2) carrying out image processing on the images of the graphite boats (2) to obtain a larger distance value between the edge of the silicon wafer in the image of the graphite boat (2) and the edge of the nearer graphite boat groove;
3) and judging whether the silicon wafer in the corresponding graphite boat groove has a reverse wafer or not based on the larger distance value.
2. The vision-based detection method for the inverted sheets of the graphite boat as claimed in claim 1, wherein in step 2), the specific process of image processing is as follows:
2.1) image calibration correction: calibrating the position coordinates of the peripheral edge of the graphite boat in the image, respectively carrying out trapezoidal correction on the two pictures according to edge positioning, and intercepting the image within the edge line of the graphite boat (2);
2.2) image segmentation and interception: respectively segmenting and intercepting images of each graphite boat (2) subjected to coordinate calibration and trapezoidal correction, segmenting and identifying each graphite boat groove for placing a silicon wafer according to image coordinates, and obtaining n x m groove images (n, m);
2.3) image gray processing: graying the intercepted 'groove image (n, m)', and converting the color image into a grayscale image;
2.4) edge detection filtering: carrying out edge detection filtering on the single 'groove image (n, m)', and carrying out binarization processing on the filtered image to form the 'groove image (n, m)', after edge detection;
2.5) image synthesis: superposing the 'groove images (n, m)' extracted by cutting each image to synthesize a new 'groove image (n, m)', and then carrying out image splicing on the new 'groove image (n, m)' according to the number of rows and columns to synthesize a final binary image of the graphite boat (2);
2.6) detecting the offset distance of the silicon chip: and (3) extracting the silicon wafer edge image in the binary image of the graphite boat (2), and calculating a larger distance value k (n, m) of the distance between the silicon wafer edge and the edge of the nearer graphite boat groove.
3. The vision-based detection method for the inverted sheets of the graphite boat as claimed in claim 2, characterized in that in step 2.1), the coordinates of the position of the peripheral edge of the graphite boat (2) in the image are calibrated by identifying the coordinate marks preset on the edge of the graphite boat (2) in each image.
4. The vision-based detection method for the inverted sheets of the graphite boat as claimed in claim 2, wherein in step 2.2), the segmentation and identification processes are as follows: and calibrating and placing a silicon wafer slot space image according to the image coordinate, segmenting the image, extracting a single slot space image by adopting a mask algorithm, and extracting n-m slot images (n, m).
5. The vision-based detection method for the inverted sheets of the graphite boat as claimed in any one of claims 2 to 4, wherein in step 2.5), the pixels of each pixel are added and averaged to realize the superposition of the "slot images (n, m)".
6. The vision-based graphite boat inverted sheet detection method as claimed in any one of claims 2 to 4, wherein in step 2.6), the number of pixel points spaced by two edge lines is converted into the actual spacing position distance to obtain a larger distance value k (n, m).
7. The vision-based detection method for the inverted sheets of the graphite boat as claimed in any one of claims 2 to 4, wherein the specific process of the step 3) is as follows:
taking an average value k (avg) of the larger distance values of the distances between the edges of the silicon wafers and the edges of the grooves;
calculating the deviation k1(n, m) from the groove edge of each silicon chip, wherein k (n, m) -k (avg); if the deviation k1(n, m) is larger than a preset threshold k2, the silicon wafer in the (n, m) -th groove is judged to be a reverse wafer.
8. The vision-based detection method for the inverted sheets of the graphite boat according to any one of claims 1 to 4, characterized in that in the step 1), images of the graphite boat (2) collected at the positions of both ends of the graphite boat (2) are acquired.
9. The utility model provides a graphite boat fall piece detection device based on vision which characterized in that includes:
the acquisition module is used for acquiring images of the graphite boat (2) acquired at different positions of the graphite boat (2);
the image processing module is used for carrying out image processing on the images of the graphite boats (2) to obtain a larger distance value between the edge of the silicon wafer in the image of the graphite boat (2) and the edge of the nearer graphite boat groove;
and the judging module is used for judging whether the silicon wafers in the corresponding graphite boat grooves have the inverted wafers or not based on the larger distance value.
10. A vision-based graphite boat take-over detection system, characterized in that the system comprises an image acquisition assembly and a vision-based graphite boat take-over detection device according to claim 9, wherein the image acquisition assembly comprises a plurality of image acquisition units which are arranged at different positions of a graphite boat (2) to be detected.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114111620A (en) * | 2022-01-28 | 2022-03-01 | 杭州利珀科技有限公司 | Optical detection system and method for graphite boat body of crystalline silicon battery |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004242068A (en) * | 2003-02-06 | 2004-08-26 | Konica Minolta Holdings Inc | Method, apparatus, and program for image processing |
| CN102332488A (en) * | 2011-05-25 | 2012-01-25 | 湖南红太阳光电科技有限公司 | Method and apparatus for laser edge isolation of crystalline silicon solar cells |
| CN105241389A (en) * | 2015-10-12 | 2016-01-13 | 贵州大学 | Machine visual sense based detection system for blunt round radius of cutting edge of milling cutter |
| CN106504262A (en) * | 2016-10-21 | 2017-03-15 | 泉州装备制造研究所 | A kind of small tiles intelligent locating method of multiple features fusion |
| CN106756893A (en) * | 2016-11-21 | 2017-05-31 | 湖南红太阳光电科技有限公司 | A kind of graphite boat handling equipment and its loading and unloading method |
| CN106783675A (en) * | 2016-12-07 | 2017-05-31 | 深圳市捷佳伟创新能源装备股份有限公司 | A kind of lateral Chu Zhou mechanisms of graphite boat with reviewing detection means |
| US20180015571A1 (en) * | 2014-12-30 | 2018-01-18 | Jiangsu University Of Science And Technology | Infrared vision sensing detection method and device for narrow-gap weld seam deviation |
| CN107993969A (en) * | 2017-12-13 | 2018-05-04 | 昆山豪恩特机器人自动化科技有限公司 | A kind of offline PECVD plug-in sheet machines |
| CN108878329A (en) * | 2018-07-19 | 2018-11-23 | 深圳市捷佳伟创新能源装备股份有限公司 | For detecting the detection device, silicon wafer processing system and detection method of position of silicon wafer |
| CN208538806U (en) * | 2018-07-19 | 2019-02-22 | 深圳市捷佳伟创新能源装备股份有限公司 | For detecting the detection device of position of silicon wafer |
| CN110277327A (en) * | 2019-07-22 | 2019-09-24 | 深圳市艾特自动化有限公司 | The detection system and detection method of silicon wafer in a kind of online graphite boat |
| CN209537622U (en) * | 2018-12-21 | 2019-10-25 | 湖南红太阳光电科技有限公司 | A kind of vacuum reaction boiler tube of tubular type PECVD |
| CN110889842A (en) * | 2019-11-28 | 2020-03-17 | 常德金鹏印务有限公司 | Method for detecting looseness of small cigarette pack cigarette label |
-
2020
- 2020-06-28 CN CN202010598314.1A patent/CN111754490B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2004242068A (en) * | 2003-02-06 | 2004-08-26 | Konica Minolta Holdings Inc | Method, apparatus, and program for image processing |
| CN102332488A (en) * | 2011-05-25 | 2012-01-25 | 湖南红太阳光电科技有限公司 | Method and apparatus for laser edge isolation of crystalline silicon solar cells |
| US20180015571A1 (en) * | 2014-12-30 | 2018-01-18 | Jiangsu University Of Science And Technology | Infrared vision sensing detection method and device for narrow-gap weld seam deviation |
| CN105241389A (en) * | 2015-10-12 | 2016-01-13 | 贵州大学 | Machine visual sense based detection system for blunt round radius of cutting edge of milling cutter |
| CN106504262A (en) * | 2016-10-21 | 2017-03-15 | 泉州装备制造研究所 | A kind of small tiles intelligent locating method of multiple features fusion |
| CN106756893A (en) * | 2016-11-21 | 2017-05-31 | 湖南红太阳光电科技有限公司 | A kind of graphite boat handling equipment and its loading and unloading method |
| CN106783675A (en) * | 2016-12-07 | 2017-05-31 | 深圳市捷佳伟创新能源装备股份有限公司 | A kind of lateral Chu Zhou mechanisms of graphite boat with reviewing detection means |
| WO2018103678A1 (en) * | 2016-12-07 | 2018-06-14 | 深圳市捷佳伟创新能源装备股份有限公司 | Graphite boat side discharging mechanism provided with inverted wafer detection device |
| CN107993969A (en) * | 2017-12-13 | 2018-05-04 | 昆山豪恩特机器人自动化科技有限公司 | A kind of offline PECVD plug-in sheet machines |
| CN108878329A (en) * | 2018-07-19 | 2018-11-23 | 深圳市捷佳伟创新能源装备股份有限公司 | For detecting the detection device, silicon wafer processing system and detection method of position of silicon wafer |
| CN208538806U (en) * | 2018-07-19 | 2019-02-22 | 深圳市捷佳伟创新能源装备股份有限公司 | For detecting the detection device of position of silicon wafer |
| CN209537622U (en) * | 2018-12-21 | 2019-10-25 | 湖南红太阳光电科技有限公司 | A kind of vacuum reaction boiler tube of tubular type PECVD |
| CN110277327A (en) * | 2019-07-22 | 2019-09-24 | 深圳市艾特自动化有限公司 | The detection system and detection method of silicon wafer in a kind of online graphite boat |
| CN110889842A (en) * | 2019-11-28 | 2020-03-17 | 常德金鹏印务有限公司 | Method for detecting looseness of small cigarette pack cigarette label |
Non-Patent Citations (1)
| Title |
|---|
| 郭忠君;吕文利;魏唯;: "石墨舟自动装卸定位方法的研究与实现", 自动化与仪器仪表, no. 01 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114111620A (en) * | 2022-01-28 | 2022-03-01 | 杭州利珀科技有限公司 | Optical detection system and method for graphite boat body of crystalline silicon battery |
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