CN105478363A - Defective product detection and classification method and system based on three-dimensional figures - Google Patents
Defective product detection and classification method and system based on three-dimensional figures Download PDFInfo
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- CN105478363A CN105478363A CN201510808135.5A CN201510808135A CN105478363A CN 105478363 A CN105478363 A CN 105478363A CN 201510808135 A CN201510808135 A CN 201510808135A CN 105478363 A CN105478363 A CN 105478363A
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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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Abstract
The invention discloses a defective product detection and classification method and system based on three-dimensional figures. The method includes the steps that firstly, input signals are received by the system, standard information is exported, and a CCD camera is started; then, pictures shot through the CCD camera are received and the practical three-dimensional product figures are formed; each product and the picture of the product are numbered; then, the practical three-dimensional product figures are compared with internally-set standard three-dimensional product figures, whether the figures are identical or not is judged, and the non-identical product picture serial numbers are marked; and finally, signals sent by a material sensor are received and endowed with sequence numbers respectively, the sequence numbers of the signals are compared with product serial numbers corresponding to the non-identical product picture serial numbers, and according to a comparison result, a discharging device is controlled for classification. By the adoption of the method and system, the shape and size of the products are automatically detected for classification, the automation degree is high, the influences caused by human factors on the detection and classification processes are avoided, detection and classification accuracy is guaranteed, the labor cost is reduced for an enterprise, and detection efficiency is improved.
Description
Technical field
The present invention relates to a kind of detection sorting technique and system, especially a kind of defective products based on 3-D graphic detects sorting technique and system.
Background technology
Product checking is requisite step in all kinds of manufacturing and processing enterprises production process, and it refers to and checks whether various raw material, semi-finished product, finished product meet the course of work of specific technical standard, specification by instrument, instrument or other analytical method.
In the testing process of various product, the shape and size inspection of product is all a very important Testing index, shape of product and size detection can be carried out accurately and automation equipment and the system of carrying out product classification owing to lacking, thus make existing technique when carrying out shape of product and dimension control, usually need manually to adopt that the survey tool of specifying manually detects the profile of the product on streamline, whether size meets the requirements, after having inspected, then by manually by satisfactory product and undesirable product separated.
The requirement of manual detection to staff is higher, if tester's method of testing is inaccurate or survey tool improper use or Check and Inspection not enough or the unintelligible standard value that should reach, all may cause various metrical error, thus make qualified products be identified as substandard product or make substandard product be identified as certified products, also just cause the accuracy of testing result, validity reduces greatly.
On the other hand, once testing staff is careless and inadvertent, undetected situation very likely occurs, the generation of undetected situation will affect adequacy and the validity of detection further.
Further, due to also need by artificial again by certified products and defective work separated, once staff is careless and inadvertent, place mistake, or be undetectedly directly positioned over different rest areas afterwards, the impact of artifact will have been superposed further, add detection and the accuracy of classification results, the further reduction of validity possibility.
Moreover, manual testing, product assortment not only labour intensity are large, manual testing, classification product often also need to spend the regular hour simultaneously, therefore inspection and classification effectiveness also lower, and to improve inspection, sort out efficiency just must increase experienced inspection, classification personnel, this also will increase enterprise human cost.
Finally, because the shape of various product, dimensional parameters often exist larger difference, therefore need to detect with different detection tools, therefore for the various enterprise of product category, the utensil cost of required cost also can increase, and also rarely has equipment, the system of a kind of highly versatile of report, shape of product applied widely, the classification of size Aulomatizeted Detect on the market.
Summary of the invention
Object of the present invention is exactly to solve the above-mentioned problems in the prior art, provides a kind of defective products based on 3-D graphic to detect sorting technique and system.
Object of the present invention is achieved through the following technical solutions:
Defective products based on 3-D graphic detects a sorting technique, comprises the steps:
S1, setting up procedure: the enabling signal and the product type signal that receive user's input, derives the standard information that this product type is corresponding, and sends the working signal of startup two CCD camera;
S2, graphic hotsopt and numbering step: receive two spacings and determine the shape picture of each product of the CCD camera shooting of angle and carry out graphical analysis, form the actual 3-D graphic of product; Meanwhile, be numbered and record according to the actual 3-D graphic of product of order to this product and correspondence thereof of each product by CCD camera, make both numbering one_to_one corresponding;
S3, comparison step: actual for the product of generation 3-D graphic and built-in product standard 3-D graphic are compared, draw the actual error value between two figures, actual error value and standard error value are compared, judge whether consistent, and mark the actual 3-D graphic numbering of inconsistent product;
S4, product classification step: the product that reception Material Sensor sends is by the signal of this Material Sensor, and give this signal a serial number according to each product by the order of this Material Sensor, production code member corresponding to each serial number and the actual 3-D graphic of inconsistent product being numbered is compared, according to comparison result, transmit control signal to blanking device, product subregion is placed.
Preferably, described a kind of defective products based on 3-D graphic detects sorting technique, wherein: at S2, to take pictures and in numbering step, use Epipolar geometry algorithm comparison film to carry out pixel matching analysis, form the actual graphics form point cloud of product, graphics form point cloud forms the actual 3-D graphic of product.
Preferably, described a kind of defective products based on 3-D graphic detects sorting technique, wherein: at S3, in comparison step: first by overlapping with the coordinate origin of product standard 3-D graphic for the coordinate origin of actual for product 3-D graphic, the position of three pole axis and direction in correction space coordinate system, then contrast the XYZ coordinate value of each three-dimensional point in space coordinates.
Preferably, described a kind of defective products based on 3-D graphic detects sorting technique, wherein: at S4, in product classification step, when serial number and the actual 3-D graphic of inconsistent product number described corresponding production code member consistent time, send to described blanking device and the product corresponding to this serial number be placed into substandard product district control signal; When serial number and the actual 3-D graphic of inconsistent product number described corresponding production code member inconsistent time, send idle signal to described blanking device.
Preferably, described a kind of defective products based on 3-D graphic detects sorting technique, wherein: also comprise S5, inventory analysis step, add up and store the number of times that in the quantity of different judged result in S3 step and S4 step, different control signal sends, and two groups of data of record are contrasted, judge whether two groups of data mate.
Defective products based on 3-D graphic detects a categorizing system, and it comprises
Start module, for receiving enabling signal and the product type signal of user's input, deriving the standard information that this product type is corresponding, and sending the working signal of startup two CCD camera;
Graphic hotsopt and numbering module, determine the shape picture of each product of the CCD camera shooting of angle for receiving two spacings and carry out graphical analysis, forming the actual 3-D graphic of product; Meanwhile, be numbered and record according to the actual 3-D graphic of product of order to this product and correspondence thereof of each product by CCD camera, make both numbering one_to_one corresponding;
Comparing module, for actual for the product of generation 3-D graphic and built-in product standard 3-D graphic are compared, draw the actual error value between two figures, actual error value and standard error value are compared, judge whether consistent, and mark inconsistent product photo numbering; And
Product classification module, for receiving a product that Material Sensor the sends signal by this Material Sensor, and give this signal a serial number according to each product by the order of this Material Sensor, production code member corresponding to each serial number and the actual 3-D graphic of inconsistent product being numbered is compared, according to comparison result, transmit control signal to blanking device, product subregion is placed.
Preferably, described a kind of defective products based on 3-D graphic detects categorizing system, wherein: also comprise inventory analysis module, for adding up and the number of times that sends of the different control signals of the quantity and product classification module that store the different judged results of comparing module, and two groups of data of record are contrasted, judge whether two groups of data mate.
The advantage of technical solution of the present invention is mainly reflected in:
1. deft design of the present invention, a set of method and system realizing shape of product, size Aulomatizeted Detect and classification are provided, automaticity is high, solve the problem that prior art manual detection classification effectiveness is low, detection classification accuracy is looked into, avoid human factor to the impact detecting assorting process, ensure that the precision detecting classification, reduce business manpower cost, improve detection efficiency.
2. detection system of the present invention and method highly versatile, not by shape, the isoparametric restriction of size of product, the quantity of Reasonable adjustment CCD camera and angle is only needed to realize, do not need extra measurement device, thus substantially increase the scope of application of native system and method.
3. method of the present invention is by the Data Comparison of front and back process, ensure that the unification of detection and classify data, thus can realize the front and back confirmation of whole process, guarantees the accuracy detecting and sort out, does not occur undetected situation; Meanwhile, the statistics of various data store also can for the later stage carry out product percent of pass, percent defective, day detection limit etc. further data analysis effective support is provided.
4. the testing process of this method is non-contact type, does not need to come in contact with product, also would not cause damage to product surface, ensure that the quality of product.
Accompanying drawing explanation
Fig. 1 is the structural representation of apparatus of the present invention;
Fig. 2 is the process schematic of the inventive method.
Detailed description of the invention
Object of the present invention, advantage and disadvantage, by for illustration and explanation for the non-limitative illustration passing through preferred embodiment below.These embodiments are only the prominent examples of application technical solution of the present invention, allly take equivalent replacement or equivalent transformation and the technical scheme that formed, all drop within the scope of protection of present invention.
Present invention is disclosed a kind of defective products and detect classification control device, as shown in Figure 1, include contact panel, data-interface; Described defective products detects classification control device and also comprises a kind of defective products based on 3-D graphic detection categorizing system; Described defective products detects classification control device and is electrically connected to two CCD camera, Material Sensor and blanking devices, and realizes the size of product, SHAPE DETECTION control described blanking device and put by the product classification after detecting according to the course of work that the described defective products based on 3-D graphic detects categorizing system.
Described a kind of defective products based on 3-D graphic detects categorizing system, as shown in Figure 1, comprising:
Start module 1, for receiving enabling signal and the product type signal of user's input, derive the standard information that this product type is corresponding, these standard information comprise but are not limited to product standard 3-D graphic and the standard error value of this product, and send the working signal of startup two CCD camera.
Graphic hotsopt and numbering module 2, determine the shape picture of each product of the CCD camera shooting of angle for receiving two spacings and carry out graphical analysis, forming the actual 3-D graphic of product; Meanwhile, be numbered and record according to the actual 3-D graphic of product of order to this product and correspondence of each product by CCD camera, make both numbering one_to_one corresponding.
Comparing module 3, for actual for the product of generation 3-D graphic and built-in product standard 3-D graphic are compared, draw the actual error value between two figures, actual error value and standard error value are compared, judge whether consistent, and mark the actual 3-D graphic numbering of inconsistent product.
And product classification module 4, for receiving a product that Material Sensor the sends signal by this Material Sensor, and give this signal a serial number according to each product by the order of this Material Sensor, production code member corresponding to the serial number of each signal and the actual 3-D graphic of inconsistent product being numbered is compared, according to comparison result, transmit control signal to blanking device, product subregion is placed.
Further, the described defective products based on 3-D graphic detects categorizing system and also comprises inventory analysis module 5, described inventory analysis module 5 is for adding up and the number of times that sends of the different control signals of the quantity and product classification module 4 that store the different judged results of comparing module 3, and two groups of data of record are contrasted, judge whether two groups of data mate.
Described inventory analysis module 5 is also for adding up the parameter such as qualification rate, disqualification rate storing all products detected simultaneously; Further, it is also for storing the parameter such as product standard 3-D graphic and standard error value of often kind of above-mentioned product.
When application native system carries out defective products detection and classification, as shown in Figure 2, its concrete course of work is as follows:
S1, setting up procedure: described startup module 1 receives enabling signal and the product type signal of user's input, derive the standard information that this product type is corresponding, then send described comparing module 3 to, and send startup two spacings and determine the working signal of the CCD camera of angle to described CCD camera.
Now, two CCD camera are taken pictures to the product passed through simultaneously, and the photo of shooting is sent to described graphic hotsopt and numbering module 2.
S2, graphic hotsopt and numbering step: described graphic hotsopt and numbering module 2 receive the shape picture of each product of two CCD camera shootings and carry out graphical analysis, concrete, described graphic hotsopt and numbering module 2 carry out pixel matching analysis according to Epipolar geometry algorithm comparison film, form the actual graphics form point cloud of product, graphics form point cloud forms the actual 3-D graphic of product, and actual for the product of generation 3-D graphic is sent to described comparing module 3.
Simultaneously, described graphic hotsopt and numbering module 2 are numbered and record according to the actual 3-D graphic of product of order to this product and correspondence thereof of each product by described CCD camera, make both numbering one_to_one corresponding, and the numbering of correspondence and the relation of correspondence are sent to described comparing module 3 and product classification module 4.
S3, comparison step: actual for the product of generation 3-D graphic and built-in product standard 3-D graphic compare by described comparing module 3, concrete, first by overlapping with the coordinate origin of product standard 3-D graphic for the coordinate origin of actual for product 3-D graphic, the position of three pole axis and direction in correction space coordinate system, then the XYZ coordinate value of each three-dimensional point in space coordinates is contrasted, draw the actual error value between two figures, actual error value and standard error value are compared, and judges that whether two values are consistent.
Concrete, when actual error value is not in the scope of standard error value, the numbering corresponding to the actual 3-D graphic of product that described comparing module 3 marks current comparison, and the production code member of this numbering correspondence is sent to described product classification module 4; When actual error value is in the scope of standard error value, then the numbering corresponding to actual for the product of current comparison 3-D graphic is not sent to described product classification module 4.
Namely the detection to each shape of product, size is automatically completed, stored in described inventory analysis module during the fructufy of the detection of each product after comparison.
Product through detecting advances to product classification district with streamline, enter as to as described in Material Sensor induction range after, described Material Sensor sends product to described product classification module and passes through signal.
S4, product classification step: described product classification module 4 receives described comparison and receives the signal of a product sending of Material Sensor by this Material Sensor, and give this signal a serial number according to each product by the order of this Material Sensor, thus make the corresponding product of a serial number; Subsequently, described product classification module the actual 3-D graphic of inconsistent product of each serial number and reception is numbered corresponding to production code member compare, according to comparison result, transmit control signal to blanking device, product subregion placed.
Concrete, when serial number and the actual 3-D graphic of inconsistent product number described corresponding production code member consistent time, product corresponding for this serial number is placed into substandard product district control signal to described blanking device transmission by described product classification module 4; When serial number and the actual 3-D graphic of inconsistent product number described corresponding production code member inconsistent time, send idle signal to described blanking device, now, product steps to qualified products district with streamline.
Like this, the automatic clustering of certified products and defective work is just completed.
Further, described inventory analysis module 5 real-time statistics, store the result of each step, the parameter such as number of signals including but not limited to the control blanking device work that the inconsistent product actual 3-D graphic numbering quantity of the quantity of certified products and the defective work detected, mark and described product classification module send.
On the other hand, the number of signals of the control blanking device work that the inconsistent product actual 3-D graphic numbering quantity of mark and described product classification module can send by described inventory analysis module 5 contrasts, judge the situation whether having product assortment mistake in rectification process, thus realize corroborating each other of front and back process.
The present invention still has numerous embodiments, all employing equivalents or equivalent transformation and all technical schemes formed, and all drops within protection scope of the present invention.
Claims (7)
1. the defective products based on 3-D graphic detects a sorting technique, it is characterized in that: comprise the steps:
S1, setting up procedure: the enabling signal and the product type signal that receive user's input, derives the standard information that this product type is corresponding, and sends the working signal of startup two CCD camera;
S2, graphic hotsopt and numbering step: receive two spacings and determine the shape picture of each product of the CCD camera shooting of angle and carry out graphical analysis, form the actual 3-D graphic of product; Meanwhile, be numbered and record according to the actual 3-D graphic of product of order to this product and correspondence thereof of each product by CCD camera, make both numbering one_to_one corresponding;
S3, comparison step: actual for the product of generation 3-D graphic and built-in product standard 3-D graphic are compared, draw the actual error value between two figures, actual error value and standard error value are compared, judge whether consistent, and mark the actual 3-D graphic numbering of inconsistent product;
S4, product classification step: the product that reception Material Sensor sends is by the signal of this Material Sensor, and give this signal a serial number according to each product by the order of this Material Sensor, production code member corresponding to each serial number and the actual 3-D graphic of inconsistent product being numbered is compared, according to comparison result, transmit control signal to blanking device, product subregion is placed.
2. a kind of defective products based on 3-D graphic according to claim 1 detects sorting technique, it is characterized in that: at S2, to take pictures and in numbering step, Epipolar geometry algorithm comparison film is used to carry out pixel matching analysis, form the actual graphics form point cloud of product, graphics form point cloud forms the actual 3-D graphic of product.
3. a kind of defective products based on 3-D graphic according to claim 1 and 2 detects sorting technique, it is characterized in that: at S3, in comparison step: first by overlapping with the coordinate origin of product standard 3-D graphic for the coordinate origin of actual for product 3-D graphic, the position of three pole axis and direction in correction space coordinate system, then contrast the XYZ coordinate value of each three-dimensional point in space coordinates.
4. a kind of defective products based on 3-D graphic according to claim 3 detects sorting technique, it is characterized in that: at S4, in product classification step, when serial number and the actual 3-D graphic of inconsistent product number described corresponding production code member consistent time, send to described blanking device and product corresponding for this serial number be placed into substandard product district control signal; When serial number and the actual 3-D graphic of inconsistent product number described corresponding production code member inconsistent time, send idle signal to described blanking device.
5. a kind of defective products based on 3-D graphic according to claim 4 detects sorting technique, it is characterized in that: also comprise S5, inventory analysis step, add up and store the number of times that in the quantity of different judged result in S3 step and S4 step, different control signal sends, and two groups of data of record are contrasted, judge whether two groups of data mate.
6. the defective products based on 3-D graphic detects a categorizing system, it is characterized in that: comprise
Start module (1), for receiving enabling signal and the product type signal of user's input, deriving the standard information that this product type is corresponding, and sending the working signal of startup two CCD camera;
Graphic hotsopt and numbering module (2), determine the shape picture of each product of the CCD camera shooting of angle for receiving two spacings and carry out graphical analysis, forming the actual 3-D graphic of product; Meanwhile, be numbered and record according to the actual 3-D graphic of product of order to this product and correspondence of each product by CCD camera, make both numbering one_to_one corresponding;
Comparing module (3), for actual for the product of generation 3-D graphic and built-in product standard 3-D graphic are compared, draw the actual error value between two figures, actual error value and standard error value are compared, judge whether consistent, and mark the actual 3-D graphic numbering of inconsistent product; And
Product classification module (4), for receiving a product that Material Sensor the sends signal by this Material Sensor, and give this signal a serial number according to each product by the order of this Material Sensor, production code member corresponding to each serial number and the actual 3-D graphic of inconsistent product being numbered is compared, according to comparison result, transmit control signal to blanking device, product subregion is placed.
7. a kind of defective products based on 3-D graphic according to claim 6 detects categorizing system, it is characterized in that: also comprise inventory analysis module (5), for adding up and the number of times that sends of the different control signals of the quantity and product classification module (4) that store the different judged results of comparing module (3), and two groups of data of record are contrasted, judge whether two groups of data mate.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106269548A (en) * | 2016-09-27 | 2017-01-04 | 深圳市创科智能技术有限公司 | A kind of object automatic sorting method and device thereof |
| CN106362963A (en) * | 2016-11-18 | 2017-02-01 | 山东爱而生智能科技有限公司 | Accurate-sorting ceramic tile sorting device and data transmission technology thereof |
| CN106645779A (en) * | 2016-09-27 | 2017-05-10 | 安徽唯嵩光电科技有限公司 | Area array color sorter material speed measurement method and defective material elimination method |
| CN109840572A (en) * | 2019-01-23 | 2019-06-04 | 江西银河表计有限公司 | A kind of SMT producing line management method and manufacture end |
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1909674A (en) * | 2005-08-05 | 2007-02-07 | 庞维克 | Method and device for stereoscopic imaging |
| JP2008009999A (en) * | 2007-07-27 | 2008-01-17 | Sony Corp | Plane extraction method, and device, program, and storage medium therefor, and imaging device |
| CN201413359Y (en) * | 2009-06-11 | 2010-02-24 | 天津力神电池股份有限公司 | Internal resistance meter testing counter |
| DE102009001894A1 (en) * | 2009-03-26 | 2010-09-30 | Ifm Electronic Gmbh | Robot system for sorting objects in e.g. wooden box, has three-dimensional-camera movably or stationary arranged at last articulated arm, and determining operating range based on travel-time of light |
| CN102914543A (en) * | 2011-08-03 | 2013-02-06 | 浙江中茂科技有限公司 | Article detection device of three-dimensional stereo image |
| CN103139477A (en) * | 2013-01-25 | 2013-06-05 | 哈尔滨工业大学 | Three-dimensional (3D) camera and method of stereo image obtaining |
| CN103753585A (en) * | 2014-01-10 | 2014-04-30 | 南通大学 | Method for intelligently adjusting manipulator and grasping force on basis of visual image analysis |
| CN204584223U (en) * | 2015-01-12 | 2015-08-26 | 温州乐控节能科技有限公司 | A kind of foundry goods automatic production line |
| CN104913737A (en) * | 2015-06-30 | 2015-09-16 | 长安大学 | Component quality checking device based on line laser three-dimensional measurement and detection method of device |
-
2015
- 2015-11-20 CN CN201510808135.5A patent/CN105478363A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1909674A (en) * | 2005-08-05 | 2007-02-07 | 庞维克 | Method and device for stereoscopic imaging |
| JP2008009999A (en) * | 2007-07-27 | 2008-01-17 | Sony Corp | Plane extraction method, and device, program, and storage medium therefor, and imaging device |
| DE102009001894A1 (en) * | 2009-03-26 | 2010-09-30 | Ifm Electronic Gmbh | Robot system for sorting objects in e.g. wooden box, has three-dimensional-camera movably or stationary arranged at last articulated arm, and determining operating range based on travel-time of light |
| CN201413359Y (en) * | 2009-06-11 | 2010-02-24 | 天津力神电池股份有限公司 | Internal resistance meter testing counter |
| CN102914543A (en) * | 2011-08-03 | 2013-02-06 | 浙江中茂科技有限公司 | Article detection device of three-dimensional stereo image |
| CN103139477A (en) * | 2013-01-25 | 2013-06-05 | 哈尔滨工业大学 | Three-dimensional (3D) camera and method of stereo image obtaining |
| CN103753585A (en) * | 2014-01-10 | 2014-04-30 | 南通大学 | Method for intelligently adjusting manipulator and grasping force on basis of visual image analysis |
| CN204584223U (en) * | 2015-01-12 | 2015-08-26 | 温州乐控节能科技有限公司 | A kind of foundry goods automatic production line |
| CN104913737A (en) * | 2015-06-30 | 2015-09-16 | 长安大学 | Component quality checking device based on line laser three-dimensional measurement and detection method of device |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106269548A (en) * | 2016-09-27 | 2017-01-04 | 深圳市创科智能技术有限公司 | A kind of object automatic sorting method and device thereof |
| CN106645779A (en) * | 2016-09-27 | 2017-05-10 | 安徽唯嵩光电科技有限公司 | Area array color sorter material speed measurement method and defective material elimination method |
| CN106362963A (en) * | 2016-11-18 | 2017-02-01 | 山东爱而生智能科技有限公司 | Accurate-sorting ceramic tile sorting device and data transmission technology thereof |
| CN106362963B (en) * | 2016-11-18 | 2023-03-24 | 山东爱而生智能科技有限公司 | Ceramic tile sorting device capable of sorting accurately and data transmission process thereof |
| CN110455380A (en) * | 2018-01-31 | 2019-11-15 | 北京戴纳实验科技有限公司 | Part preliminary examination examining system |
| CN109840572A (en) * | 2019-01-23 | 2019-06-04 | 江西银河表计有限公司 | A kind of SMT producing line management method and manufacture end |
| CN109858928A (en) * | 2019-01-23 | 2019-06-07 | 江西银河表计有限公司 | A kind of DIP producing line management method and manufacture end |
| CN109840572B (en) * | 2019-01-23 | 2022-10-14 | 江西银河表计有限公司 | SMT production line management method and manufacturing end |
| CN110404825A (en) * | 2019-08-22 | 2019-11-05 | 深圳眼千里科技有限公司 | Screening technique and device in optics module AI detection device |
| CN113695271A (en) * | 2020-05-22 | 2021-11-26 | 海太半导体（无锡）有限公司 | Method for automatically setting defective product mark |
| CN117495785A (en) * | 2023-10-18 | 2024-02-02 | 深圳市沐沐计算机科技有限公司 | Product detection method and device based on point cloud data |
| CN117495785B (en) * | 2023-10-18 | 2024-08-16 | 深圳市沐沐计算机科技有限公司 | Product detection method and device based on point cloud data |
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