WO2023179663A1 - 一种基于3d建模和视觉检测的生产交互方法及系统 - Google Patents

一种基于3d建模和视觉检测的生产交互方法及系统 Download PDF

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Publication number
WO2023179663A1
WO2023179663A1 PCT/CN2023/083068 CN2023083068W WO2023179663A1 WO 2023179663 A1 WO2023179663 A1 WO 2023179663A1 CN 2023083068 W CN2023083068 W CN 2023083068W WO 2023179663 A1 WO2023179663 A1 WO 2023179663A1
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Prior art keywords
production
basket
area
rules
factors
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PCT/CN2023/083068
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English (en)
French (fr)
Inventor
周禹
孙彬
徐志群
付明全
马伟萍
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高景太阳能股份有限公司
广东金湾高景太阳能科技有限公司
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Publication of WO2023179663A1 publication Critical patent/WO2023179663A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/0006—Industrial image inspection using a design-rule based approach
    • 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
    • B07C5/02—Measures preceding sorting, e.g. arranging articles in a stream orientating
    • 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
    • B07C5/34—Sorting according to other particular properties
    • 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
    • B07C5/36—Sorting apparatus characterised by the means used for distribution
    • B07C5/361—Processing or control devices therefor, e.g. escort memory
    • B07C5/362—Separating or distributor mechanisms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G06T7/292—Multi-camera tracking
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01L—SEMICONDUCTOR DEVICES NOT COVERED BY CLASS H10
    • H01L21/00—Processes or apparatus adapted for the manufacture or treatment of semiconductor or solid state devices or of parts thereof
    • H01L21/67—Apparatus specially adapted for handling semiconductor or electric solid state devices during manufacture or treatment thereof; Apparatus specially adapted for handling wafers during manufacture or treatment of semiconductor or electric solid state devices or components ; Apparatus not specifically provided for elsewhere
    • H01L21/67005—Apparatus not specifically provided for elsewhere
    • H01L21/67242—Apparatus for monitoring, sorting or marking
    • H01L21/67276—Production flow monitoring, e.g. for increasing throughput
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10004—Still image; Photographic image
    • G06T2207/10012—Stereo images
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30108—Industrial image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30232—Surveillance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30241—Trajectory

Definitions

  • the present invention relates to the technical field of intelligent production control, and in particular to a production interaction method and system based on 3D modeling and visual detection.
  • a limit sensor is used to sense the incoming material of the flower basket
  • a position sensor is used to detect the position between each flower basket during film running.
  • the sensor is prone to failure and position deviation during use, maintenance efficiency is low and production is easily delayed.
  • special personnel are required to monitor the production, which is highly dependent on labor. Therefore, the production of ultra-thin silicon wafers is further promoted. During the process, a production efficiency bottleneck was encountered.
  • the present invention aims to solve at least one of the technical problems existing in the prior art. For this reason, the purpose of the present invention The aim is to provide a production interaction method and system based on 3D modeling and visual inspection to solve the problem in the existing technology of relying on a large number of sensors and labor to ensure the production status transfer of flower baskets in silicon wafer production, and to overcome the problem of The efficiency bottleneck in ultra-thin silicon wafer production.
  • the first aspect of the embodiments of this application provides a production interaction method based on 3D modeling and visual inspection for the production status transfer of flower baskets in silicon wafer production, which includes the following steps:
  • the production flow rules include the set characteristics of each production factor in the normal production process;
  • the set production process includes automatic mode and manual mode.
  • step S33 When in manual mode, if the compared production factor characteristics do not match the characteristics set in the production flow rules, step S33 is executed: stop the operation of all production factors, display warning messages, and output optional execution command options. Get and execute manually issued execution command options.
  • the target area includes a unloading area, a sorting area, a basket return area and a grabbing area
  • the production flow rules are divided according to the target area
  • the production flow rules of each target area constrain the production factors therein. actions and states.
  • step S20 when setting the production flow rules, it is determined that in each target area, the corresponding production factor is positioned before and after performing an action, and its trajectory profile is determined based on the images of the production factors positioned before and after. feature.
  • step S20 when setting production flow rules, it specifically includes:
  • each target area is divided according to priority.
  • the unloading area and sorting area are the first priority area, the grabbing area is the second priority area, and the basket return area It is the third priority area;
  • Set the return basket rule when the sorting rules are met, when at least one turning machine in the sorting area is in a horizontal return-to-basket state, record the return basket characteristics of the production factors in the first priority area. When the detected When the characteristics of production factors meet the above return-to-basket characteristics, the return-to-basket rule is satisfied;
  • Basket-shifting rules When the basket-returning rules are met, when there is a basket-returning vacancy in the basket-returning area, the robot arm is controlled to place the empty flower basket in the basket-returning vacancy, and the production factors in the third priority area are recorded. Basket-shifting characteristics, when the detected production factor characteristics meet the above basket-shifting characteristics, the basket-shifting rule is satisfied.
  • when setting incoming material rules it also includes:
  • the feature of recording that all silicon wafers in the fully loaded flower basket in the unloading end of the unloading area are in a flat state is the flat feature.
  • the sorting area includes two turning machines, and the two turning machines are arranged on the left and right sides;
  • the turning machine When the turning machine is in the loading state, the turning machine is located on the left or right side, in a horizontal state, with no flower basket on it;
  • the turning machine When the turning machine is in the film running state, the turning machine is located in the middle position and is in a vertical state;
  • the turning machine When the turning machine is in the basket-returning state, the turning machine is located at the left or right side, in a horizontal state, with a flower basket on it.
  • the second aspect of the embodiment of this application provides a production interaction system based on 3D modeling and visual inspection, including:
  • the 3D camera module is used to collect images of production factors in each target area within the production range, and establish a 3D monitoring model based on the imaging contour characteristics and positional relationships of the production factors; and the production factors in each target area operate according to the set production process When detecting the dynamic characteristics and/or static characteristics of production factors;
  • the rule setting module is used to set production flow rules.
  • the production flow rules include the setting characteristics of each production factor in the normal production process;
  • the production execution module is used to control the production factors in each target area to operate according to the set production process
  • the remaining production factors will be stopped, and the current production factors used for comparison will be controlled to continue executing the current instructions until they match the characteristics set in the production flow rules, and then the rest will be restored. Production factors operate.
  • the 3D camera module includes four 3D cameras, and the 3D cameras are one of a binocular 3D camera, a ToF 3D camera, a monocular structured light 3D camera, and a binocular structured light 3D camera. Or multiple.
  • the present invention at least includes the following beneficial effects:
  • the production interaction method and system based on 3D modeling and visual inspection provided by the embodiments of this application first performs image collection and 3D monitoring model modeling of production factors in each target area within the production range.
  • Corresponding production flow rules are established based on 3D modeling, and the location information, action information, status information, etc. of each production factor characteristic in the production process are defined in the production flow rules; in actual production, each production factor is visually detected in real time Characteristics and compare them with the corresponding set characteristics in the production flow rules. Only if they are consistent with the set characteristics of production factors defined in the model and the judgment is correct, normal operation can continue. If not, corrective measures will be taken immediately; in progress During production interaction, there is no need to rely on sensors and manpower, the error rate is low, and the bottleneck of production efficiency is solved intelligently.
  • Figure 1 is a schematic flow chart of a production interaction method based on 3D modeling and visual inspection provided by an embodiment of the present invention.
  • FIG. 2 is a schematic top view of a scene in which the production interaction method provided by the embodiment of the present invention is used in silicon wafer production for cleaning, running, and returning to the basket.
  • FIG. 3 is a schematic front view of a scene in which the production interaction method provided by the embodiment of the present invention is used in silicon wafer production for cleaning, running, and returning to the basket.
  • a specific device when a specific device is described as being located between a first device and a second device, there may or may not be an intervening device between the specific device and the first device or the second device.
  • the specific device When a specific device is described as being connected to another device, the specific device may be directly connected to the other device without an intervening device, or may not be directly connected to the other device but with an intervening device.
  • this embodiment provides a production interaction method based on 3D modeling and visual inspection, which is used for the production status transfer of flower baskets in silicon wafer production. Furthermore, It is the production state transfer of flower baskets between the cleaning machine 11, the turning machine 22 and the basket return line 31 during the production process of cleaning, running and returning to the basket, including the following steps:
  • the production flow rules include the set characteristics of each production factor in the normal production process; in the 3D monitoring model, each production factor in each target area has been included in different workflows. The characteristics of If the rules are not met, subsequent rules cannot be entered;
  • the set features can be dynamic features, such as movement trajectories, rotation angles, etc., or static features, such as the number of silicon wafers, placement positions, etc., as long as they can be used to reflect various production factors in the normal production process.
  • the operating rules are all within the scope of the set features of this embodiment. In actual production, the characteristics of each production factor are detected through real-time vision and compared with the corresponding set characteristics in the production flow rules. Only if the set characteristics of the production factors defined in the model are consistent with the correct judgment can the normal operation continue. , if not, corrective measures will be taken immediately; during production interaction, there is no need to rely on sensors and manpower, the error rate is low, and the production efficiency bottleneck problem is solved intelligently.
  • the production process is set to include automatic mode and manual mode, that is, in normal production, according to actual needs, it can run in automatic mode or manual mode.
  • the two modes are in steps S10 and S20. , are consistent in S30, the difference is after executing step S30:
  • steps S31 and S32 When in the automatic mode, perform steps S31 and S32. If the characteristics of the compared production factors do not match the characteristics set in the production flow rules, the remaining production factors will be stopped and the current production factors used for comparison will continue to execute the current instructions until they match the characteristics set in the production flow rules, and then resume the operation of other production factors;
  • step S33 is executed: stop the operation of all production factors, display warning information, output optional execution command options, and obtain and execute manually issued execution command options. It should be noted that if a feature inconsistency occurs in manual mode, the operation will be stopped first, a warning message will be displayed to inform the operator of the abnormal situation, and then several optional execution command options will be given on the display interface, including manual reset.
  • execution command options are all safe options.
  • the operator can also jump out of this execution command option and execute other programs through the operation display interface. Allowed actions.
  • the target area includes a unloading area 1, a sorting area 2, a basket return area 3, and a grabbing area 4.
  • the unloading area 1 includes a cleaning machine 11, and the cleaning machine 11 transfers the cleaned fully loaded flower baskets to The unloading end;
  • the sorting area 2 includes a sorting device 21, which includes two turning machines 22, and the two turning machines 22 turn over and run the pieces in turn;
  • the basket return area 3 includes a basket return line 31, and the empty flower baskets 13 are placed in the return basket.
  • the return basket line 31 transports it to the recycling area;
  • the grabbing area 4 includes a robot arm 41, which is responsible for transporting the flower baskets, including placing the fully loaded flower baskets 12 from the cleaning machine 11 to the turning machine 22, and also includes Put the empty flower basket 13 from the turning machine 22 to the basket return line 31;
  • the production flow rules are divided according to the above target areas.
  • Each target area has a corresponding production flow rule.
  • the production flow rules belonging to one target area can only be applied. In this target area, that is, the production flow rules of each target area constrain the actions and status of the production factors.
  • step S20 when setting the production flow rules and setting the dynamic characteristics, it is determined that in each target area, the corresponding production factors are positioned before and after performing an action, and based on the images of the production factors positioned before and after, Determine its trajectory profile characteristics.
  • the robot arm 41 when the robot arm 41 is placing the fully loaded flower basket 12 from the cleaning machine 11 to the turning machine 22, since there are two flower basket positions A and B at the discharge end of the washing machine 11, and there are also two turning machines 22C and D, therefore When loading materials, the robot arm 41 needs to go from A to C and from B to D in order to place the flower baskets in sequence.
  • the trajectory profile characteristics of the robot arm 41 from A to C and from B to D are determined in the 3D monitoring model. Only if the trajectory of the robot arm 41 matches this set feature can it be proven that its operation is correct.
  • step S20 when setting the production flow rules, it specifically includes:
  • each target area is divided according to priority. Since the blanking area 1 and the sorting area 2 are the core target areas, they directly affect the operation of the flower basket. As long as these two areas The production process needs to be pushed forward, and other areas need to cooperate, so the unloading area 1 and the sorting area 2 are defined as the first priority area; the production status transfer of the flower basket in each target area requires the operation of the machine arm 41, so The grabbing area 4 is defined as the second priority area; finally, as long as the robot arm 41 places the empty flower basket 13 on the basket return line 31, the basket return line 31 needs to be recycled, so the basket return area 3 is defined as the second priority area.
  • Three priority areas. The first priority area has the highest priority. Only when the first priority area reaches certain conditions, the second priority area and the third priority area as auxiliary functions will be put into operation.
  • the production flow rules include several subdivision rules. Each subdivision rule is responsible for the production of the corresponding target area or priority area. In more detail, it includes incoming material rules, material loading rules, sorting rules, and basket return rules. , basket-taking rules and basket-moving rules, the specific setting process is as follows:
  • the robot arm 41 in the grabbing area 4 is controlled to grab the fully loaded flower basket in the unloading area 1 and place it on the turning machine 22 in the sorting area 2 that is in a state of waiting for loading.
  • Record the trajectory profile of the machine arm 41 during loading in the second priority area record the loading trajectory profile of the robot arm 41 as the loading feature, and the loading feature is a dynamic feature.
  • the feeding rules are satisfied; in this rule, the focus is on whether the robot arm 41 works according to the set conveying route and trajectory, and only when the route is consistent can the conveying be carried out;
  • Set the return basket rule when the sorting rules are met, when at least one turning machine 22 in the sorting area 2 is in a horizontal return-to-basket state, record the return basket characteristics of the production factors in the first priority area. At this time, the flower basket is on There is no silicon wafer, and the placement platform of the turning machine 22 is in a horizontal initial position. When the detected production factor characteristics meet the above return characteristics, the return rule is satisfied;
  • the production flow rules when setting the production flow rules, it also includes setting exception rules: when abnormal factors other than production factors are detected to enter the production range, all production factors are stopped. In order to ensure the safety of the production range, other abnormal factors are prevented from entering the production range.
  • the incoming material rules when setting the incoming material rules, it also includes: recording the characteristics of all silicon wafers in the flat state in the fully loaded flower basket 12 in the unloading end of the unloading area 1 as the flat feature.
  • the detected production factors When the characteristics meet the above flat characteristics, the incoming material rules are met. Since the silicon wafers in the flower basket are easily deformed during the cleaning process, visual inspection is required to detect whether all the silicon wafers in the fully loaded flower basket 12 at the unloading end are in a flat state. Only when they are in a flat state can the loading and sorting process be carried out. If there is deformation such as depression or convexity, stop loading first and adjust the flatness before starting loading. It should be noted that the smoothing adjustment can be done manually or by blowing the silicon wafer using blowing air, which is not further limited here.
  • the sorting area 2 includes two turning machines 22.
  • the sorting area 2 has a total of three work stations, which are divided into left and right sides and the middle.
  • the two turning machines 22 are arranged on the left and right sides; the initial state Bottom, the middle station is vacant, and there is a turning machine 22 on each side on the left and right sides;
  • the turning machine 22 When the turning machine 22 is in the loading state, the turning machine 22 is located at the left or right side, and the placement platform of the turning machine 22 is in a horizontal state with no flower basket on it; at this time, the conditions for placing a flower basket on it are met;
  • the turning machine 22 When the turning machine 22 is in the film running state, the turning machine 22 is located in the middle position, and the placement platform of the turning machine 22 is in a vertical state;
  • the turning machine 22 When the turning machine 22 is in the basket-returning state, the turning machine 22 is located at the left or right side position, and the placement platform of the turning machine 22 is in a horizontal state with a flower basket on it.
  • the left side turning machine 22 first moves to the middle station and flips upward 90° to form a vertical state for film running; When, place the fully loaded flower basket on the right turning machine 22; wait for the left turning machine 22 to finish running the film, put the left The side turning machine 22 is turned down 90° to form a horizontal state, and then moved to the left station, waiting for the basket to be returned; at this time, the right turning machine 22 is moved to the middle station, and the fully loaded flower basket is moved on the right turning machine 22. slice, and repeat.
  • the simulation establishes the production factor characteristics of the two turning machines 22 when they switch between the states of loading, running, and returning to the basket. Only when the turning machines 22 are consistent with the production flow rules in the actual production process Only if the corresponding setting characteristics are consistent, execution is allowed to continue.
  • embodiments of the present application provide a production interaction system based on 3D modeling and visual inspection, including:
  • the 3D camera module 5 is used to collect images of production factors in each target area within the production range, and establish a 3D monitoring model based on the imaging contour characteristics and positional relationships of the production factors; and the production factors in each target area follow the set production process During operation, detect dynamic characteristics and/or static characteristics of production factors;
  • the rule setting module is used to set production flow rules.
  • the production flow rules include the setting characteristics of each production factor in the normal production process;
  • the production execution module is used to control the production factors in each target area to operate according to the set production process; it includes a cleaning machine 11, a sorting device 21, a turning machine 22, a machine arm 41 and a basket return line 31, etc.;
  • the remaining production factors will be stopped, and the current production factors used for comparison will be controlled to continue executing the current instructions until they match the characteristics set in the production flow rules, and then the rest will be restored. Production factors operate.
  • the 3D camera module 5 includes four 3D cameras.
  • the 3D cameras are one or more of a binocular 3D camera, a ToF 3D camera, a monocular structured light 3D camera, and a binocular structured light 3D camera.
  • 3D cameras are set up above each target area to shoot from different angles to form a three-dimensional image without blind spots.
  • the dynamic and static characteristics of the action unit and passive objects are monitored in real time, and the production factors within the production range are monitored in real time. Spatial positioning recognition, setting the starting and ending positions of picking and placing, automatically calculating the movement trajectory, avoiding the surrounding environment, and generating the optimal movement trajectory.
  • the above embodiments provide a production interaction method and system based on 3D modeling and visual inspection.
  • image collection and 3D monitoring model modeling of production factors in each target area within the production range are performed.
  • the corresponding production flow rules are established based on 3D modeling.
  • the production flow rules define the position information, action information, status information, etc. of each production factor characteristic in the production process; in actual production, Visually detect the characteristics of each production factor in real time and compare them with the corresponding set characteristics in the production flow rules. Only if they are consistent with the set characteristics of the production factors defined in the model and the judgment is correct, normal operation can continue. If not, the system will immediately Take corrective measures; when conducting production interactions, there is no need to rely on sensors and manpower, the error rate is low, and the bottleneck of production efficiency is solved intelligently.

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Abstract

本发明公开一种基于3D建模和视觉检测的生产交互方法及系统，先对生产范围内各个目标区域中的生产因素进行图像采集及3D监控模型建模，根据正常设定的生产流程，基于3D建模建立起对应的生产流规则，在生产流规则中定义了每一个生产因素特征在生产过程中的位置信息、动作信息、状态信息等；在实际生产中，实时视觉检测各个生产因素特征，并将其与生产流规则中对应的设定特征作对比，只有与模型中所定义的生产因素设定特征相符，判断正确才能继续正常运行，若不符，则马上采取更正措施；在进行生产交互时，无需借助感应器和人力，错误率低，智能化解决生产效率瓶颈问题。

Description

一种基于3D建模和视觉检测的生产交互方法及系统 技术领域
本发明涉及智能生产控制技术领域，尤其涉及一种基于3D建模和视觉检测的生产交互方法及系统。
背景技术
在进行硅片生产过程中，需要在清洗机的下料端，将清洗好的插载好硅片的花篮放置在分选机中，由分选机逐一对每个花篮进行跑片，而跑片完毕的空花篮则放置在回篮线中，再传输至回收区，这期间花篮的搬运需要使用机器臂。可以看出，为了实现硅片的跑片，需要多台生产设备之间的交互，而为了满足自动生产，每台生产设备之间的生产因素状态是否进行妥当，是否满足进入下一步骤的条件，都是需要确保的，尤其在进行薄硅片生产时，例如对110微米以下硅片的清洁后跑片步骤中，则必须保证各个生产因素之间的配合要严丝合缝，不能有超出误差以外的偏差，否则如果花篮发生误撞、误停机或误压篮，薄硅片容易受到损伤，产生坏片。
现有技术中，通常是通过各种感应器来对各个生产因素的动作进行监控，例如使用限位传感器进行花篮来料的感应，再用位置感应器来检测跑片时各个花篮之间的位置配合，总之需要在生产线上装配一系列感应器，来保证生产的逻辑流畅性。但是由于感应器容易发生故障，在使用过程中容易发生位置偏移，维修效率低，容易耽误生产，而且还需专人盯着生产，对人工依赖性强，所以在进一步推广超薄型硅片生产过程中，遇到了生产效率瓶颈。
发明内容
本发明旨在至少解决现有技术中存在的技术问题之一。为此，本发明的目 的在于提供一种基于3D建模和视觉检测的生产交互方法及系统，以解决现有技术中需要依赖大量感应器和人工来保证硅片生产中花篮的生产状态转移的问题，克服了在对超薄硅片生产时的效率瓶颈。
为达到上述目的，本发明采用如下技术方案：
本申请实施例第一方面，提供一种基于3D建模和视觉检测的生产交互方法，用于硅片生产中花篮的生产状态转移，包括以下步骤：
S10、采集生产范围内各目标区域中的生产因素图像，根据生产因素的成像轮廓特征及位置关系，建立3D监控模型；
S20、基于3D监控模型，设定生产流规则，所述生产流规则中包括各生产因素在正常生产流程中的设定特征；
S30、控制各目标区域中的生产因素按设定生产流程运作，检测生产因素的动态特征和/或静态特征，并逐一将生产因素特征与生产流规则中对应的设定特征作对比：
S31、若所对比的生产因素特征与生产流规则中设定特征相符，则继续按设定生产流程运作；
S32、若所对比的生产因素特征与生产流规则中设定特征不符，则停止其余生产因素，控制用于对比的当前生产因素继续执行当前指令，直至与生产流规则中设定特征相符，再恢复其余生产因素运作。
在一些可能的实施例中，所述设定生产流程包括自动模式和手动模式，在执行步骤S30后：
当处于自动模式下时，若所对比的生产因素特征与生产流规则中设定特征不符，按步骤S32执行；
当处于手动模式下时，若所对比的生产因素特征与生产流规则中设定特征不符，则执行步骤S33：停止所有生产因素的运作，显示警示信息，并输出可供选择的执行命令选项，获取并执行手动下达的执行命令选项。
在一些可能的实施例中，所述目标区域包括下料区、分选区、回篮区和抓取区，所述生产流规则按目标区域划分，各目标区域的生产流规则约束其中生产因素的动作和状态。
在一些可能的实施例中，在步骤S20中，设定生产流规则时，确定在各目标区域中，对应生产因素在执行一个动作的前后定位，根据前后定位的生产因素图像，确定其轨迹轮廓特征。
在一些可能的实施例中，在步骤S20中，设定生产流规则时，具体包括：
根据设定生产流程的作业顺序，将各个目标区域按优先级划分，所述下料区和分选区为第一优先级区，所述抓取区为第二优先级区，所述回篮区为第三优先级区；
设定来料规则：当至少一个满载的花篮被输送至所述下料区的下料端，且所述分选区中至少一个翻转机处于水平的待上料状态时，记录第一优先级区中生产因素的来料特征，当所检测的生产因素特征满足以上来料特征时，即满足来料规则；
设定上料规则：在满足来料规则情况下，控制抓取区的机器臂抓取下料区中的满载花篮并放置在分选区中处于待上料状态的翻转机，记录第二优先级区中机器臂在上料时的轨迹轮廓，将所述机器臂的上料轨迹轮廓记录为上料特征，当所检测的生产因素特征满足以上上料特征时，即满足上料规则；
设定分选规则：在满足上料规则情况下，控制分选区中各翻转机轮流进行 跑片，记录第一优先级区中各翻转机在跑片时的轨迹轮廓，将所述翻转机的跑片轨迹轮廓记录为分选特征，当所检测的生产因素特征满足以上分选特征时，即满足分选规则；
设定回篮规则：在满足分选规则情况下，当所述分选区中至少一个翻转机处于水平的待回篮状态时，记录第一优先级区中生产因素的回篮特征，当所检测的生产因素特征满足以上回篮特征时，即满足回篮规则；
设定取篮规则：在满足回篮规则情况下，控制抓取区的机器臂抓取处于水平的待回篮状态中的翻转机上的空花篮，记录第二优先级区中机器臂在取篮时的轨迹轮廓，将所述机器臂的取篮轨迹轮廓记录为取篮特征，当所检测的生产因素特征满足以上取篮特征时，即满足取篮规则；
设定移篮规则：在满足取篮规则情况下，当所述回篮区上有回篮空位时，控制机器臂将空花篮放置于所述回篮空位，记录第三优先级区中生产因素的移篮特征，当所检测的生产因素特征满足以上移篮特征时，即满足移篮规则。
在一些可能的实施例中，在设定生产流规则时，还包括设定异常规则：
当检测到生产因素以外的异常因素进入生产范围时，停止所有生产因素。
在一些可能的实施例中，在设定来料规则时，还包括：
记录所述下料区的下料端中满载的花篮内所有硅片处于平整状态下的特征为平整特征，当所检测的生产因素特征满足以上平整特征时，即满足来料规则。
在一些可能的实施例中，在所述分选区中包括两台翻转机，两台所述翻转机为左右两侧布置；
当所述翻转机处于待上料状态时，所述翻转机位于左或右侧边位置，处于水平状态，其上无花篮；
当所述翻转机处于跑片状态时，所述翻转机位于中部位置，处于垂直状态；
当所述翻转机处于待回篮状态时，所述翻转机位于左或右侧边位置，处于水平状态，其上有花篮。
本申请实施例第二方面，提供一种基于3D建模和视觉检测的生产交互系统，包括：
3D相机模块，用于采集生产范围内各目标区域中的生产因素图像，根据生产因素的成像轮廓特征及位置关系，建立3D监控模型；且在各目标区域中的生产因素按设定生产流程运作时，检测生产因素的动态特征和/或静态特征；
规则设定模块，用于设定生产流规则，所述生产流规则中包括各生产因素在正常生产流程中的设定特征；
生产执行模块，用于控制各目标区域中的生产因素按设定生产流程运作；
交互处理模块，用于将所检测的生产因素特征与生产流规则中对应的设定特征作对比：
若所对比的生产因素特征与生产流规则中设定特征相符，则继续按设定生产流程运作；
若所对比的生产因素特征与生产流规则中设定特征不符，则停止其余生产因素，控制用于对比的当前生产因素继续执行当前指令，直至与生产流规则中设定特征相符，再恢复其余生产因素运作。
在一些可能的实施例中，所述3D相机模块包括4台3D相机，所述3D相机为双目3D相机、ToF 3D相机、单目结构光3D相机、双目结构光3D相机中的一种或者多种。
相比现有技术，本发明至少包括以下有益效果：
本申请实施例提供的基于3D建模和视觉检测的生产交互方法及系统，先对生产范围内各个目标区域中的生产因素进行图像采集及3D监控模型建模，根据正常设定的生产流程，基于3D建模建立起对应的生产流规则，在生产流规则中定义了每一个生产因素特征在生产过程中的位置信息、动作信息、状态信息等；在实际生产中，实时视觉检测各个生产因素特征，并将其与生产流规则中对应的设定特征作对比，只有与模型中所定义的生产因素设定特征相符，判断正确才能继续正常运行，若不符，则马上采取更正措施；在进行生产交互时，无需借助感应器和人力，错误率低，智能化解决生产效率瓶颈问题。
下面结合附图和具体实施方式对本发明作进一步详细说明。
附图说明
利用附图对本发明作进一步说明，但附图中的实施例不构成对本发明的任何限制，对于本领域的普通技术人员，在不付出创造性劳动的前提下，还可以根据以下附图获得其它的附图。
图1为本发明实施例提供的一种基于3D建模和视觉检测的生产交互方法的流程示意图。
图2为本发明实施例提供的生产交互方法应用在硅片生产中清洗、跑片、回篮的场景的俯视简图。
图3为本发明实施例提供的生产交互方法应用在硅片生产中清洗、跑片、回篮的场景的正视简图。
图中，1、下料区；2、分选区；3、回篮区；4、抓取区；11、清洗机；12、满载的花篮；13、空的花篮；21、分选装置；22、翻转机；31、回篮线；41、机器臂；5、3D相机模块。
具体实施方式
下面将结合附图对本发明的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
在本发明的描述中，需要说明的是，术语“中心”、“上”、“下”、“左”、“右”、“竖直”、“水平”、“内”、“外”等指示的方位或位置关系为基于附图所示的方位或位置关系，仅是为了便于描述本发明和简化描述，而不是指示或暗示所指的装置或元件必须具有特定的方位、以特定的方位构造和操作，因此不能理解为对本发明的限制。此外，术语“第一”、“第二”、“第三”仅用于描述目的，而不能理解为指示或暗示相对重要性。
在本发明的描述中，当描述到特定器件位于第一器件和第二器件之间时，在该特定器件与第一器件或第二器件之间可以存在居间器件，也可以不存在居间器件。当描述到特定器件连接其它器件时，该特定器件可以与所述其它器件直接连接而不具有居间器件，也可以不与所述其它器件直接连接而具有居间器件。
对于相关领域普通技术人员已知的技术、方法和设备可能不作详细讨论，但在适当情况下，所述技术、方法和设备应当被视为说明书的一部分。
在生产厚度小于120微米的硅片，尤其是110微米硅片时，在从清洗机下料端将满载的花篮放置在分选机中、再将跑片完的空花篮放回至回篮线时，要不需要人工进行转移，效率低下，不适应大规模生产；要不采用一系列感应器，来感应满花篮和空花篮的位置和状态，而偏偏在这一步骤中，花篮中的110微米硅片在经过清洗之后可能发生形变，出现不同程度的凹陷或者上凸，利用传统感应器无法精准检测到每一片硅片的情况，因此导致在后续的翻转、跑片时容 易出现碰撞、压篮等问题，影响了生产质量和生产效率。
为了解决上述问题，第一方面，参照图1至图3，本实施例提供一种基于3D建模和视觉检测的生产交互方法，用于硅片生产中花篮的生产状态转移，更进一步地，是在清洗、跑片、回篮的生产过程中，花篮在清洗机11、翻转机22和回篮线31之间的生产状态转移，包括以下步骤：
S10、采集生产范围内各目标区域中的生产因素图像，根据生产因素的成像轮廓特征及位置关系，建立3D监控模型；每个目标区域的功能不一样，因此每个目标区域都有其特有的生产因素，当然地，花篮需要穿梭于多个目标区域，因此花篮作为共同生产因素流转；通过采集图像，包括动态特征和/或静态特征，建立起能含括生产范围内所有生产因素的3D监控模型；
S20、基于3D监控模型，设定生产流规则，生产流规则中包括各生产因素在正常生产流程中的设定特征；在3D监控模型中已经包括在不同工作流程中，各个目标区域各个生产因素的特征，通过这些特征的组合和排序，可模拟出正常生产流程中的特征流，需要注意的是，在生产流规则中，存在逻辑判断，即需要满足特定规则，才能进入目标规则，前置规则未满足，则无法进入后续规则；
S30、在设定好生产流规则后，进入实际生产中，控制各目标区域中的生产因素按设定生产流程运作，在正常运作过程中，实时检测生产因素的动态特征和/或静态特征，并逐一将生产因素特征与生产流规则中对应的设定特征作对比：
S31、若所对比的生产因素特征与生产流规则中设定特征相符，则继续按设定生产流程运作；
S32、若所对比的生产因素特征与生产流规则中设定特征不符，则停止其余 生产因素，控制用于对比的当前生产因素继续执行当前指令，直至与生产流规则中设定特征相符，再恢复其余生产因素运作。
需要说明的是，设定特征可以是动态特征，例如移动轨迹、转动角度等，也可以是静态特征，例如硅片数量、摆放位置等，只要能用来反映在正常生产流程中各个生产因素的运作规则，均在本实施例的设定特征范围内。在实际生产中，通过实时视觉检测各个生产因素特征，并将其与生产流规则中对应的设定特征作对比，只有与模型中所定义的生产因素设定特征相符，判断正确才能继续正常运行，若不符，则马上采取更正措施；在进行生产交互时，无需借助感应器和人力，错误率低，智能化解决生产效率瓶颈问题。
作为一种实施方式，设定生产流程包括自动模式和手动模式，即在正常生产中，根据实际需要，可以在自动模式下运行，也可以在手动模式下运行，两种模式在步骤S10、S20、S30中是一致的，区别点就在执行步骤S30后：
当处于自动模式下时，按步骤S31和S32执行，其中，若所对比的生产因素特征与生产流规则中设定特征不符，则停止其余生产因素，控制用于对比的当前生产因素继续执行当前指令，直至与生产流规则中设定特征相符，再恢复其余生产因素运作；
当处于手动模式下时，若所对比的生产因素特征与生产流规则中设定特征相符，则继续按设定生产流程运作，这一步骤与S31相同；若所对比的生产因素特征与生产流规则中设定特征不符，则执行步骤S33：停止所有生产因素的运作，显示警示信息，并输出可供选择的执行命令选项，获取并执行手动下达的执行命令选项。需注意的是，若在手动模式下出现了特征不符，先停止运作，显示出警示信息，告知操作者异常情况，然后在显示界面给出若干个可供选择的执行命令选项，包括有手动复位、再执行当前步骤、返回上一步骤等，即尽量在 人工不接触内部生产因素的情况下，让控制系统自行修复和还原，其中，执行命令选项均是安全选项，当然地，操作者也可通过操作显示界面，跳出此执行命令选项，执行另外的程序允许的动作。
在本实施例中，目标区域包括下料区1、分选区2、回篮区3和抓取区4，其中，下料区1包括清洗机11，清洗机11将清洗完的满载花篮传输至下料端；分选区2包括分选装置21，其中包括两台翻转机22，两台翻转机22依次进行翻转跑片；回篮区3包括回篮线31，将空的花篮13放置在回篮线31上，回篮线31将其传输至回收区；抓取区4包括机器臂41，机器臂41负责搬运花篮，包括将满载的花篮12从清洗机11放至翻转机22，也包括将空的花篮13从翻转机22放至回篮线31；生产流规则根据以上目标区域进行划分，每个目标区域都有对应的生产流规则，属于一个目标区域中的生产流规则只能作用于本目标区域，即各目标区域的生产流规则约束其中生产因素的动作和状态。
更进一步地，在步骤S20中，设定生产流规则时，在设定动态的特征时，确定在各目标区域中，对应生产因素在执行一个动作的前后定位，根据前后定位的生产因素图像，确定其轨迹轮廓特征。例如机器臂41在将满载的花篮12从清洗机11放至翻转机22过程中，由于清洗机11的下料端有两个花篮位A、B，还存在两台翻转机22C、D，因此在上料时，机器臂41需要从A到C，还需从B到D，以实现依次放置花篮，在3D监控模型中确定从A到C、从B到D机器臂41的轨迹轮廓特征，机器臂41的轨迹只有与此设定特征相符，才能证明其运行正确。
在本实施例中，在步骤S20中，设定生产流规则时，具体包括：
根据设定生产流程的作业顺序，将各个目标区域按优先级划分，由于下料区1和分选区2是最核心的目标区域，直接影响花篮的运转，只要这两个区域 需要向前推进生产流程，其余区域需要配合，因此将下料区1和分选区2定义为第一优先级区；花篮在各个目标区域中的生产状态转移都需要机器臂41的投运，因此将抓取区4定义为第二优先级区；最后，只要机器臂41将空的花篮13放置在回篮线31上，回篮线31即需进行回收，因此将回篮区3定义为第三优先级区。第一优先级区的优先级最高，只有当第一优先级区达到一定条件，才会使作为辅助功能的第二优先级区和第三优先级区投入运行。
在生产流规则中，包括有若干个细分规则，每一个细分规则负责对应目标区域或优先级区的生产，更详细地，包括来料规则、上料规则、分选规则、回篮规则、取篮规则和移篮规则，具体设定过程如下：
设定来料规则：当至少一个满载的花篮12被输送至下料区1的下料端，且分选区2中至少一个翻转机22处于水平的待上料状态时，证明此时可以将满载花篮输送至翻转机22，记录第一优先级区中生产因素的来料特征，来料特征为静态特征，当所检测的生产因素特征满足以上来料特征时，即满足来料规则；在这一规则中，重点在于第一优先级区中的下料端和翻转机22是否满足可以上料的条件，通过视觉检测可反映真实情况；
设定上料规则：在满足来料规则情况下，控制抓取区4的机器臂41抓取下料区1中的满载花篮并放置在分选区2中处于待上料状态的翻转机22，记录第二优先级区中机器臂41在上料时的轨迹轮廓，将机器臂41的上料轨迹轮廓记录为上料特征，上料特征为动态特征，当所检测的生产因素特征满足以上上料特征时，即满足上料规则；在这一规则中，重点在于机器臂41是否按设定的输送路线和轨迹来工作，路线相符才能进行输送；
设定分选规则：在满足上料规则情况下，控制分选区2中各翻转机22轮流进行跑片，记录第一优先级区中各翻转机22在跑片时的轨迹轮廓，将翻转机22 的跑片轨迹轮廓记录为分选特征，分选特征为动态特征，当所检测的生产因素特征满足以上分选特征时，即满足分选规则；在这一规则中，重点在于两台翻转机22的工作配合，两台翻转机22需要满足轮流依次跑片的规则；
设定回篮规则：在满足分选规则情况下，当分选区2中至少一个翻转机22处于水平的待回篮状态时，记录第一优先级区中生产因素的回篮特征，此时花篮上无硅片，且翻转机22的放置平台处于水平初始位置状态，当所检测的生产因素特征满足以上回篮特征时，即满足回篮规则；
设定取篮规则：在满足回篮规则情况下，控制抓取区4的机器臂41抓取处于水平的待回篮状态中的翻转机22上的空花篮，记录第二优先级区中机器臂41在取篮时的轨迹轮廓，将机器臂41的取篮轨迹轮廓记录为取篮特征，取料特征为动态特征，当所检测的生产因素特征满足以上取篮特征时，即满足取篮规则；在这一规则中，重点在于机器臂41是否按设定的搬运路线和轨迹来工作，路线相符才能进行输送；
设定移篮规则：在满足取篮规则情况下，当回篮区3上有回篮空位时，控制机器臂41将空花篮放置于回篮空位，记录第三优先级区中生产因素的移篮特征，当所检测的生产因素特征满足以上移篮特征时，即满足移篮规则。
可见，在持续进行花篮跑片的过程中，至少需要经历来料、上料、分选、回篮、取篮和移篮，而且以上步骤环环相扣，只要满足来料之后，才会控制上料，上完料再分选，每分选完一个花篮，就进行回篮、取篮和移篮，回收这一花篮，因此在设定相应的生产流规则时，需要进行优先级划分，第二优先级区的动作需要第一优先级区满足相应前置条件，只有第二优先级区进入取篮规则中，才会触发第三优先级区进行移篮，优先级区划分使得生产交互更清晰，目的性更强，步骤简单不冗余。
作为一种实施方式，在设定生产流规则时，还包括设定异常规则：当检测到生产因素以外的异常因素进入生产范围时，停止所有生产因素。为了保证生产范围的安全性，杜绝其余异常因素进入生产范围。
作为一种实施方式，在设定来料规则时，还包括：记录下料区1的下料端中满载的花篮12内所有硅片处于平整状态下的特征为平整特征，当所检测的生产因素特征满足以上平整特征时，即满足来料规则。由于在清洗过程中，花篮中的硅片容易被清洗变形，因此需要通过视觉检测，检测在下料端中满载的花篮12内所有硅片是否处于平整状态，只有处于平整状态才能进入上料和分选，如果存在凹陷或上凸等变形，则先停止上料，调整好平整状态后再进入上料。需要注意的是，调整平整的动作，可以是人为调整，也可以是利用吹风来吹动硅片，在此不作进一步限定。
在本实施例中，在分选区2中包括两台翻转机22，分选区2一共有三个工位，分为是左右两侧和中间，两台翻转机22为左右两侧布置；初始状态下，中间工位的空置的，左右两侧一边一台翻转机22；
当翻转机22处于待上料状态时，翻转机22位于左或右侧边位置，翻转机22的放置平台处于水平状态，其上无花篮；此时满足在其上放置花篮的条件；
当翻转机22处于跑片状态时，翻转机22位于中部位置，翻转机22的放置平台处于垂直状态；
当翻转机22处于待回篮状态时，翻转机22位于左或右侧边位置，翻转机22的放置平台处于水平状态，其上有花篮。
需要说明的是，当先在左侧翻转机22上放置满载花篮后，左侧翻转机22先平移至中间工位，向上翻转90°形成垂直状态，以便跑片；在左侧翻转机22跑片时，再在右侧翻转机22上放置满载花篮；等左侧翻转机22跑片结束，将左 侧翻转机22向下翻转90°形成水平状态，再平移至左侧工位，等待回篮；此时将右侧翻转机22平移至中间工位，进行右侧翻转机22上满载花篮的跑片，并如此重复。
在3D监控模型中，模拟建立出两台翻转机22在待上料、跑片、待回篮几个状态之间切换时的生产因素特征，只有当实际生产过程中翻转机22与生产流规则中对应的设定特征相符，才允许继续执行。
第二方面，本申请实施例提供一种基于3D建模和视觉检测的生产交互系统，包括：
3D相机模块5，用于采集生产范围内各目标区域中的生产因素图像，根据生产因素的成像轮廓特征及位置关系，建立3D监控模型；且在各目标区域中的生产因素按设定生产流程运作时，检测生产因素的动态特征和/或静态特征；
规则设定模块，用于设定生产流规则，生产流规则中包括各生产因素在正常生产流程中的设定特征；
生产执行模块，用于控制各目标区域中的生产因素按设定生产流程运作；包括有清洗机11、分选装置21、翻转机22、机器臂41和回篮线31等；
交互处理模块，用于将所检测的生产因素特征与生产流规则中对应的设定特征作对比：
若所对比的生产因素特征与生产流规则中设定特征相符，则继续按设定生产流程运作；
若所对比的生产因素特征与生产流规则中设定特征不符，则停止其余生产因素，控制用于对比的当前生产因素继续执行当前指令，直至与生产流规则中设定特征相符，再恢复其余生产因素运作。
其中，3D相机模块5包括4台3D相机，3D相机为双目3D相机、ToF 3D相机、单目结构光3D相机、双目结构光3D相机中的一种或者多种。
在各目标区域的上方设置4台3D相机，分别从不同角度进行拍摄，形成无死角的三维图像，对动作单元和被动作物体的动态和静态特性进行实时监控，对生产范围内的生产因素进行空间定位识别，设置取放始末位置，自动计算运动轨迹，避让开周边环境，生成最优运动轨迹。
相对于现有技术，上述实施例提供一种基于3D建模和视觉检测的生产交互方法及系统，先对生产范围内各个目标区域中的生产因素进行图像采集及3D监控模型建模，根据正常设定的生产流程，基于3D建模建立起对应的生产流规则，在生产流规则中定义了每一个生产因素特征在生产过程中的位置信息、动作信息、状态信息等；在实际生产中，实时视觉检测各个生产因素特征，并将其与生产流规则中对应的设定特征作对比，只有与模型中所定义的生产因素设定特征相符，判断正确才能继续正常运行，若不符，则马上采取更正措施；在进行生产交互时，无需借助感应器和人力，错误率低，智能化解决生产效率瓶颈问题。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上实施例仅表达了本发明的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进，这些都属于本发明的保护范围。因此，本发明专利的保护范围应以所附权利要求为准。

Claims (10)

  1. 一种基于3D建模和视觉检测的生产交互方法，用于硅片生产中花篮的生产状态转移，其特征在于，包括以下步骤：
    S10、采集生产范围内各目标区域中的生产因素图像，根据生产因素的成像轮廓特征及位置关系，建立3D监控模型；
    S20、基于3D监控模型，设定生产流规则，所述生产流规则中包括各生产因素在正常生产流程中的设定特征；
    S30、控制各目标区域中的生产因素按设定生产流程运作，检测生产因素的动态特征和/或静态特征，并逐一将生产因素特征与生产流规则中对应的设定特征作对比：
    S31、若所对比的生产因素特征与生产流规则中设定特征相符，则继续按设定生产流程运作；
    S32、若所对比的生产因素特征与生产流规则中设定特征不符，则停止其余生产因素，控制用于对比的当前生产因素继续执行当前指令，直至与生产流规则中设定特征相符，再恢复其余生产因素运作。
  2. 根据权利要求1所述的一种基于3D建模和视觉检测的生产交互方法，其特征在于，所述设定生产流程包括自动模式和手动模式，在执行步骤S30后：
    当处于自动模式下时，若所对比的生产因素特征与生产流规则中设定特征不符，按步骤S32执行；
    当处于手动模式下时，若所对比的生产因素特征与生产流规则中设定特征不符，则执行步骤S33：停止所有生产因素的运作，显示警示信息，并输出可供选择的执行命令选项，获取并执行手动下达的执行命令选项。
  3. 根据权利要求2所述的一种基于3D建模和视觉检测的生产交互方法，其特征在于，所述目标区域包括下料区、分选区、回篮区和抓取区，所述生产 流规则按目标区域划分，各目标区域的生产流规则约束其中生产因素的动作和状态。
  4. 根据权利要求3所述的一种基于3D建模和视觉检测的生产交互方法，其特征在于，在步骤S20中，设定生产流规则时，确定在各目标区域中，对应生产因素在执行一个动作的前后定位，根据前后定位的生产因素图像，确定其轨迹轮廓特征。
  5. 根据权利要求4所述的一种基于3D建模和视觉检测的生产交互方法，其特征在于，在步骤S20中，设定生产流规则时，具体包括：
    根据设定生产流程的作业顺序，将各个目标区域按优先级划分，所述下料区和分选区为第一优先级区，所述抓取区为第二优先级区，所述回篮区为第三优先级区；
    设定来料规则：当至少一个满载的花篮被输送至所述下料区的下料端，且所述分选区中至少一个翻转机处于水平的待上料状态时，记录第一优先级区中生产因素的来料特征，当所检测的生产因素特征满足以上来料特征时，即满足来料规则；
    设定上料规则：在满足来料规则情况下，控制抓取区的机器臂抓取下料区中的满载花篮并放置在分选区中处于待上料状态的翻转机，记录第二优先级区中机器臂在上料时的轨迹轮廓，将所述机器臂的上料轨迹轮廓记录为上料特征，当所检测的生产因素特征满足以上上料特征时，即满足上料规则；
    设定分选规则：在满足上料规则情况下，控制分选区中各翻转机轮流进行跑片，记录第一优先级区中各翻转机在跑片时的轨迹轮廓，将所述翻转机的跑片轨迹轮廓记录为分选特征，当所检测的生产因素特征满足以上分选特征时，即满足分选规则；
    设定回篮规则：在满足分选规则情况下，当所述分选区中至少一个翻转机处于水平的待回篮状态时，记录第一优先级区中生产因素的回篮特征，当所检测的生产因素特征满足以上回篮特征时，即满足回篮规则；
    设定取篮规则：在满足回篮规则情况下，控制抓取区的机器臂抓取处于水平的待回篮状态中的翻转机上的空花篮，记录第二优先级区中机器臂在取篮时的轨迹轮廓，将所述机器臂的取篮轨迹轮廓记录为取篮特征，当所检测的生产因素特征满足以上取篮特征时，即满足取篮规则；
    设定移篮规则：在满足取篮规则情况下，当所述回篮区上有回篮空位时，控制机器臂将空花篮放置于所述回篮空位，记录第三优先级区中生产因素的移篮特征，当所检测的生产因素特征满足以上移篮特征时，即满足移篮规则。
  6. 根据权利要求5所述的一种基于3D建模和视觉检测的生产交互方法，其特征在于，在设定生产流规则时，还包括设定异常规则：
    当检测到生产因素以外的异常因素进入生产范围时，停止所有生产因素。
  7. 根据权利要求6所述的一种基于3D建模和视觉检测的生产交互方法，其特征在于，在设定来料规则时，还包括：
    记录所述下料区的下料端中满载的花篮内所有硅片处于平整状态下的特征为平整特征，当所检测的生产因素特征满足以上平整特征时，即满足来料规则。
  8. 根据权利要求7所述的一种基于3D建模和视觉检测的生产交互方法，其特征在于，在所述分选区中包括两台翻转机，两台所述翻转机为左右两侧布置；
    当所述翻转机处于待上料状态时，所述翻转机位于左或右侧边位置，处于水平状态，其上无花篮；
    当所述翻转机处于跑片状态时，所述翻转机位于中部位置，处于垂直状态；
    当所述翻转机处于待回篮状态时，所述翻转机位于左或右侧边位置，处于水平状态，其上有花篮。
  9. 一种基于3D建模和视觉检测的生产交互系统，其特征在于，包括：
    3D相机模块，用于采集生产范围内各目标区域中的生产因素图像，根据生产因素的成像轮廓特征及位置关系，建立3D监控模型；且在各目标区域中的生产因素按设定生产流程运作时，检测生产因素的动态特征和/或静态特征；
    规则设定模块，用于设定生产流规则，所述生产流规则中包括各生产因素在正常生产流程中的设定特征；
    生产执行模块，用于控制各目标区域中的生产因素按设定生产流程运作；
    交互处理模块，用于将所检测的生产因素特征与生产流规则中对应的设定特征作对比：
    若所对比的生产因素特征与生产流规则中设定特征相符，则继续按设定生产流程运作；
    若所对比的生产因素特征与生产流规则中设定特征不符，则停止其余生产因素，控制用于对比的当前生产因素继续执行当前指令，直至与生产流规则中设定特征相符，再恢复其余生产因素运作。
  10. 根据权利要求9所述的一种基于3D建模和视觉检测的生产交互系统，其特征在于，所述3D相机模块包括4台3D相机，所述3D相机为双目3D相机、ToF 3D相机、单目结构光3D相机、双目结构光3D相机中的一种或者多种。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117601482A (zh) * 2023-12-04 2024-02-27 苏州铂瑞电极工业有限公司 基于智能调控的燃料电池双极板压合机

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114708209B (zh) * 2022-03-25 2023-04-04 高景太阳能股份有限公司 一种基于3d建模和视觉检测的生产交互方法及系统
CN116666268B (zh) * 2023-05-18 2023-12-01 江苏亚电科技有限公司 一种槽内晶圆篮故障排除方法及装置

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090007062A1 (en) * 2007-06-27 2009-01-01 Yuval Gilboa Design-time rules mechanism for modeling systems
US9558467B1 (en) * 2016-03-02 2017-01-31 Software Ag Systems and/or methods for grid-based multi-level digitization of enterprise models
CN109326539A (zh) * 2018-09-18 2019-02-12 江苏中宇光伏科技有限公司 太阳电池生产实时监控数字系统
CN111508066A (zh) * 2020-04-16 2020-08-07 北京迁移科技有限公司 一种基于3d视觉的无序堆叠工件抓取系统及交互方法
CN113591790A (zh) * 2021-08-16 2021-11-02 上海铂端科技有限公司 基于计算机视觉实现生产线装配流程行为监测的系统、方法、装置、处理器及其存储介质
CN114708209A (zh) * 2022-03-25 2022-07-05 广东高景太阳能科技有限公司 一种基于3d建模和视觉检测的生产交互方法及系统

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111951237B (zh) * 2020-08-04 2021-06-08 上海微亿智造科技有限公司 外观视觉检测方法
CN112857458B (zh) * 2021-02-05 2023-08-29 常州捷佳创精密机械有限公司 一种检测装置、料台设备以及其图像处理方法
CN113035761B (zh) * 2021-03-05 2021-11-12 苏州市中辰昊科技有限公司 一种用于双轨上料的硅片花篮调度平台

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20090007062A1 (en) * 2007-06-27 2009-01-01 Yuval Gilboa Design-time rules mechanism for modeling systems
US9558467B1 (en) * 2016-03-02 2017-01-31 Software Ag Systems and/or methods for grid-based multi-level digitization of enterprise models
CN109326539A (zh) * 2018-09-18 2019-02-12 江苏中宇光伏科技有限公司 太阳电池生产实时监控数字系统
CN111508066A (zh) * 2020-04-16 2020-08-07 北京迁移科技有限公司 一种基于3d视觉的无序堆叠工件抓取系统及交互方法
CN113591790A (zh) * 2021-08-16 2021-11-02 上海铂端科技有限公司 基于计算机视觉实现生产线装配流程行为监测的系统、方法、装置、处理器及其存储介质
CN114708209A (zh) * 2022-03-25 2022-07-05 广东高景太阳能科技有限公司 一种基于3d建模和视觉检测的生产交互方法及系统

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117601482A (zh) * 2023-12-04 2024-02-27 苏州铂瑞电极工业有限公司 基于智能调控的燃料电池双极板压合机
CN117601482B (zh) * 2023-12-04 2024-05-03 苏州铂瑞电极工业有限公司 基于智能调控的燃料电池双极板压合机

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