CN114895634A - Product production line automatic control system based on machine vision - Google Patents
Product production line automatic control system based on machine vision Download PDFInfo
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- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41885—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by modeling, simulation of the manufacturing system
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32339—Object oriented modeling, design, analysis, implementation, simulation language
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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Abstract
The invention discloses a product production line automatic control system based on machine vision, which relates to the technical field of LED control, and is characterized in that the operation action of an employee of each station node on a production line is identified, whether the operation action of the employee is standard or not and whether the operation sequence is correct or not are judged, when the operation action and the operation sequence of the employee are normal, the operation action of the employee is analyzed according to the duration of the actual action of the employee and the duration of the standard operation action, so that whether the station where the employee is located is a bottleneck station is judged, and if the station is the bottleneck station, the linear speed is adjusted according to the operation duration of the operation action of the employee; deviation between the operation track and the standard operation track through monitoring equipment to judge whether the operation of equipment is normal, deviation surpasses the setting value when the operation in-process of equipment, then generates early warning information, thereby guarantees the standardization of equipment operation, avoids equipment operation anomaly to cause product batched quality problem.
Description
Technical Field
The invention relates to the technical field of LED control, in particular to an automatic control system of a product production line based on machine vision.
Background
Machine vision is an important branch of artificial intelligence developing rapidly, and in brief, machine vision utilizes the robot to replace the human eye to measure and judge, along with industrial intellectuality, automated development, more and more industrial field use machine vision detection technology to carry out product inspection, and machine vision detection technology not only has efficient detection speed, can also provide the testing result of high accuracy.
The existing production line is in the production process, the line speed of the production line is often adjusted according to experience by managers, the adaptation can not be achieved with the actual operation capability of staff on the production line in the adjusting mode, the situation that operation cannot be followed up occurs on some stations of the production line is made, whether deviation can not be effectively monitored in the track of equipment on the production line in the operation process or not is achieved, how machine vision is utilized is achieved, the equipment is monitored, monitoring and analyzing are conducted on the operation of the staff of the stations on the production line, the line speed of the production line is automatically adjusted, the problem that people need to solve is solved, and the automatic control system of the production line based on the machine vision is provided.
Disclosure of Invention
The invention aims to provide a product production line automatic control system based on machine vision.
The purpose of the invention can be realized by the following technical scheme: a product production line automatic control system based on machine vision comprises a monitoring center, wherein the monitoring center is in communication and/or electric connection with a data acquisition module, a data processing module, a data analysis module and a production line adjusting module;
the data acquisition module consists of a plurality of visual acquisition terminals and is used for acquiring operation data of the production line in the operation process and acquiring operation videos of staff and equipment on the production line through the visual acquisition terminals;
the data processing module is used for processing the employee work video and the equipment work video acquired by the data acquisition module;
the data analysis module is used for analyzing the running state of each station node and equipment node on the production line according to the data processed by the data processing module;
the production line adjusting module is used for adjusting the operation process of the production line and the equipment according to the analysis results of the station nodes and the equipment nodes.
Further, the process of acquiring the production line operation data by the data acquisition module comprises:
constructing a production line model, and marking the positions of production line nodes in the production line model; the production line nodes comprise station nodes and equipment nodes; and respectively acquiring the operation video of the staff of the station node and the operation video of the equipment in the operation process through the visual acquisition terminals arranged on the station node and the equipment node.
Further, the processing process of the data processing module on the job video of the employee comprises the following steps:
rasterizing the obtained employee job video to obtain a video frame of the employee job; inputting the obtained video frame of the employee operation into a neural network training model;
identifying employees and the working actions of the employees in the video frame through a neural network training model;
the method comprises the steps of decomposing the work of an employee into a plurality of work units and obtaining the work time of each work unit; setting standard operation actions according to the operation content of the station nodes, dividing the standard operation actions into a plurality of standard operation units, and acquiring the operation time of each standard operation unit;
and matching the obtained work unit in the work action of the employee work with the standard work unit in the standard work action.
Further, the process of processing the job video of the device by the data processing module includes;
rasterizing the obtained operation video of the equipment to obtain a video frame of the equipment operation; inputting the obtained video frame of the equipment operation into a neural network training model; identifying the running track of the equipment in the video frame through a neural network training model, decomposing the obtained running track of the equipment into a plurality of running nodes, and obtaining the running time of each running node; constructing a three-dimensional coordinate system; and setting a standard running track of the equipment, decomposing the standard running track into a plurality of standard running nodes, and acquiring the time spent by each standard running node.
Further, the process of analyzing the operating state of the station node by the data analysis module includes:
sequencing each operation unit of the operation actions of the staff on the station node acquired by the vision acquisition terminal in sequence; sorting the standard operation units corresponding to the standard operation actions corresponding to the station nodes according to the sequence; matching the operation units acquired by the vision acquisition terminal with the standard operation units one by one, and outputting a matching result; after matching of all the operation units is completed, if the standard operation units are not labeled, the operation action of the employee is not standardized; after matching of all the operation units is completed, if an operation unit which can not be matched with the standard operation unit exists, marking the corresponding unit as a redundant operation unit; if all the standard operation units are labeled, whether the sequence of the labeled standard operation units is the same as the sequence of the standard operation units is obtained, so that whether the operation sequence of the staff is correct is judged, and when the operation action of the staff is standard and the operation sequence is correct, the operation deviation duration of the staff of each station node is obtained.
Further, the process of matching the job unit with the standard job unit includes:
matching the operation unit with the standard operation unit, and judging whether the standard operation unit same as the operation unit exists or not;
if the standard operation unit with the same operation unit does not exist, the operation unit is represented as a redundant operation unit; if the standard operation unit identical to the operation unit exists, the corresponding standard operation unit is numbered, and the number of the standard operation unit is consistent with that of the operation unit.
Further, the process of analyzing the operation state of the device node by the data analysis module includes: and obtaining the deviation coefficient of the equipment at each running node according to the coordinates of each running node of the running track and the coordinates of each running node of the standard running track.
Further, the process of adjusting the production line by the production line adjusting module comprises:
setting an operation deviation duration threshold, comparing the operation deviation duration with the operation deviation duration threshold, judging whether station nodes are normal or not, and marking the abnormal station nodes;
acquiring whether a marked station node has a redundant operation unit, if so, rejecting the redundant operation unit, acquiring operation deviation duration again, comparing the operation deviation duration with an operation deviation duration threshold, and judging whether the station node is a bottleneck node according to a comparison result;
and readjusting the production line speed according to the operation duration of the operation action of the staff of the bottleneck node.
Compared with the prior art, the invention has the beneficial effects that: identifying the operation action of the staff of each station node on the production line to judge whether the operation action of the staff is normal or not and whether the operation sequence is correct or not, generating early warning information when the operation action and the operation sequence of the staff are abnormal, analyzing the operation action of the staff according to the duration of the actual action of the staff and the duration of the standard operation action when the operation action and the operation sequence of the staff are normal, judging whether the station where the staff is located is a bottleneck station or not, and adjusting the linear speed according to the operation duration of the operation action of the staff if the station is the bottleneck station;
deviation between the operation track and the standard operation track through monitoring equipment to judge whether the operation of equipment is normal, deviation surpasses the setting value when the operation in-process of equipment, then generates early warning information, thereby guarantees the standardization of equipment operation, avoids equipment operation anomaly to cause product batched quality problem.
Drawings
Fig. 1 is a schematic diagram of the present invention.
Detailed Description
As shown in fig. 1, a product production line automatic control system based on machine vision comprises a monitoring center, wherein the monitoring center is in communication and/or electric connection with a data acquisition module, a data processing module, a data analysis module and a production line adjusting module;
the data acquisition module comprises a plurality of vision acquisition terminals for obtain the operating data of production line in the operation process, and specific process includes:
constructing a production line model, and marking the positions of production line nodes in the production line model; it is further noted that, in the specific implementation process, the production line node includes a station node and an equipment node;
marking production line nodes needing to be provided with the vision acquisition terminals according to actual requirements, and arranging the vision acquisition terminals on the corresponding production line nodes;
the method comprises the steps that staff operation information of a station node is obtained through a visual acquisition terminal installed on the station node, a work video of staff of the station node is obtained, and the work video of the staff is sent to a data processing module;
the method comprises the steps of obtaining operation videos in the operation process of equipment through a visual collection terminal installed on equipment nodes, and sending the operation videos in the operation process of the equipment to a data processing module.
The data processing module is used for processing the employee work video and the equipment work video acquired by the data acquisition module;
the processing process of the data processing module on the job video of the employee comprises the following steps:
rasterizing the obtained employee job video to obtain a video frame of the employee job; inputting the obtained video frame of the employee operation into a neural network training model;
identifying employees and the working actions of the employees in the video frame through a neural network training model;
the method comprises the steps of decomposing the work of an employee into a plurality of work units, and sequentially marking the work units as i, i is 1, 2, … …, n and n is an integer;
acquiring the working time of each working unit and marking the working time of each working unit as ZD i ；
Setting standard operation actions according to the operation content of the station nodes, dividing the standard operation actions into a plurality of standard operation units, and acquiring the operation time of each standard operation unit;
matching the operation unit in the operation action of the obtained employee operation with the standard operation unit in the standard operation action, and sending the matching result to the data analysis module;
the process of processing the operation video of the equipment by the data processing module comprises the following steps;
rasterizing the obtained operation video of the equipment to obtain a video frame of the equipment operation; inputting the obtained video frame of the equipment operation into a neural network training model;
identifying the running track of the equipment in the video frame through a neural network training model;
dividing the obtained running track of the equipment into a plurality of running nodes, and labeling each running node according to a running sequence, wherein j is 1, 2, … …, m is an integer;
acquiring the running time of each running node, and marking the running time of each running node as SJ j ；
Constructing a three-dimensional coordinate system according to the position of the equipment;
setting a standard running track of the equipment, decomposing the standard running track into a plurality of standard running nodes, and acquiring the time spent by each standard running node;
marking the coordinate position of each standard operation node in a three-dimensional coordinate system;
and sending the data obtained after the data processing module processes the data to a data analysis module.
The data analysis module is used for analyzing the running state of each station node and equipment node on the production line according to the data processed by the data processing module;
the process of analyzing the operation state of the station nodes on the production line by the data analysis module comprises the following steps:
sequencing each operation unit of the operation actions of the staff on the station node acquired by the vision acquisition terminal in sequence;
sorting the standard operation units of the standard operation action corresponding to the station node according to the sequence;
the operation units acquired by the vision acquisition terminal are matched with the standard operation units one by one, and the matching result is output, wherein the specific matching process comprises the following steps:
matching the operation unit with the index i being 1 with the standard operation unit, and judging whether the standard operation unit identical to the operation unit with the index i being 1 exists or not;
if the standard operation unit identical to the operation unit with the reference number i being 1 does not exist, the operation unit is an excess operation unit;
if there is a standard operation unit identical to the operation unit with the index i being 1, the corresponding standard operation unit is numbered as "1";
matching the operation units with other labels with the standard operation units respectively to complete the matching process of all the operation units and output the matching result;
after matching of all the operation units is completed, if the standard operation units are not labeled and indicate that the operation actions of the staff are not standard, generating early warning information and sending the early warning information to a monitoring center;
after matching of all the operation units is completed, if an operation unit which can not be matched with the standard operation unit exists, marking the corresponding unit as a redundant operation unit;
if all the standard operation units are marked, whether the marked sequence of the standard operation units is the same as the sequence of the standard operation units is obtained, if so, the operation sequence of the employee operation action is consistent with the standard operation action sequence, and the employee operation sequence is correct;
if the sequence of the marks of the standard operation units is different from the sequence of the standard operation units, which indicates that the operation action sequence of the staff is wrong, generating early warning information and sending the early warning information to a monitoring center;
it should be further noted that, in the specific implementation process, when the employee work action is normative and the work sequence is correct, the work deviation duration of the employee at each workstation node is obtained, and the work deviation duration is marked as ZP, where
Wherein ti is the operation time of the standard operation unit corresponding to the operation unit with the label i, and t is the total duration of the standard operation action; it should be further noted that, in the implementation process, when there is no standard operation unit corresponding to the operation unit labeled i, ti is equal to 0; and sending the operation deviation duration of each station node to a production line adjusting module.
The process of analyzing the running state of the equipment nodes on the production line by the data analysis module comprises the following steps:
marking the coordinate of each running node of the running track as (X) j ，Y j ，Z j )；
Acquiring the deviation coefficient of the equipment node at each running node, and marking the deviation coefficient of the equipment node at each running node as BP i In which BP i ＝|X i -x| 2 +|Y i -x| 2 +|Y i -x| 2 ；
The deviation coefficient threshold value B0 is set, when BP is i If the running track is greater than B0, the running track of the equipment deviates, and early warning information is generated; when BP i And when the speed is less than or equal to B0, the running track of the equipment is normal.
The production line adjusting module is used for adjusting the operation process of the production line according to the analysis results of the station nodes and the equipment nodes, and the specific process comprises the following steps:
setting a work deviation duration threshold value, and setting a work deviation duration threshold value Z0;
when the operation deviation duration ZP is less than or equal to Z0, the station node is normal;
when the operation deviation duration ZP is more than Z0, marking the station node;
acquiring whether redundant operation units exist in the station node, if so, removing the redundant operation units, acquiring operation deviation duration ZP1 again, comparing the operation deviation duration ZP1 with an operation deviation duration threshold value, and if ZP1 is greater than Z0, marking the station node as a bottleneck node;
readjusting the production line speed according to the operation duration of the operation action of the staff of the bottleneck node;
it should be further noted that, in the specific implementation process, the operation duration of the operation action of the bottleneck node referred to by the production line linear speed does not include the duration spent by the redundant operation unit, that is, the duration spent by all the operation units after the redundant operation unit is removed by the bottleneck node is used as the reference for the production line linear speed adjustment, so that the employee operation of all the workstation nodes can be adapted to the production line linear speed.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (8)
1. A product production line automatic control system based on machine vision comprises a monitoring center, and is characterized in that the monitoring center is in communication and/or electric connection with a data acquisition module, a data processing module, a data analysis module and a production line adjusting module;
the data acquisition module consists of a plurality of visual acquisition terminals and is used for acquiring operation data of the production line in the operation process and acquiring operation videos of staff and equipment on the production line through the visual acquisition terminals;
the data processing module is used for processing the employee work videos and the equipment work videos acquired by the data acquisition module;
the data analysis module is used for analyzing the running state of each station node and equipment node on the production line according to the data processed by the data processing module;
the production line adjusting module is used for adjusting the operation process of the production line and the equipment according to the analysis results of the station nodes and the equipment nodes.
2. The system of claim 1, wherein the process of acquiring the production line operation data by the data acquisition module comprises:
constructing a production line model, and marking the positions of production line nodes in the production line model; the production line nodes comprise station nodes and equipment nodes; and respectively acquiring the operation video of the staff of the station node and the operation video of the equipment in the operation process through the visual acquisition terminals arranged on the station node and the equipment node.
3. The automatic control system for the product production line based on the machine vision as claimed in claim 2, wherein the processing process of the data processing module to the job video of the employee comprises the following steps:
rasterizing the obtained employee job video to obtain a video frame of the employee job; inputting the obtained video frame of the employee operation into a neural network training model;
identifying employees and the working actions of the employees in the video frame through a neural network training model;
the method comprises the steps of decomposing the work of an employee into a plurality of work units and obtaining the work time of each work unit; setting standard operation actions according to the operation content of the station nodes, dividing the standard operation actions into a plurality of standard operation units, and acquiring the operation time of each standard operation unit;
and matching the obtained work unit in the work action of the employee work with the standard work unit in the standard work action.
4. The automatic control system for the product production line based on the machine vision as claimed in claim 3, wherein the process of processing the operation video of the equipment by the data processing module comprises;
rasterizing the obtained operation video of the equipment to obtain a video frame of the equipment operation; inputting the obtained video frame of the equipment operation into a neural network training model; identifying the running track of the equipment in the video frame through a neural network training model, decomposing the obtained running track of the equipment into a plurality of running nodes, and obtaining the running time of each running node; constructing a three-dimensional coordinate system; and setting a standard running track of the equipment, decomposing the standard running track into a plurality of standard running nodes, and acquiring the time spent by each standard running node.
5. The automatic control system for the production line based on the machine vision as claimed in claim 4, wherein the process of analyzing the operation state of the station node by the data analysis module comprises:
sequencing each operation unit of the operation actions of the staff on the station node acquired by the vision acquisition terminal in sequence; sorting the standard operation units of the standard operation action corresponding to the station node according to the sequence; matching the operation units acquired by the vision acquisition terminal with the standard operation units one by one, and outputting a matching result; after matching of all the operation units is completed, if the standard operation units are not labeled, the operation action of the employee is not standardized; after matching of all the operation units is completed, if an operation unit which can not be matched with the standard operation unit exists, marking the corresponding unit as a redundant operation unit; if all the standard operation units are labeled, whether the sequence of the labeled standard operation units is the same as the sequence of the standard operation units is obtained, so that whether the operation sequence of the staff is correct is judged, and when the operation action of the staff is standard and the operation sequence is correct, the operation deviation duration of the staff of each station node is obtained.
6. The machine-vision-based automatic control system for product production line according to claim 5, wherein the matching process of the working unit and the standard working unit comprises:
matching the operation unit with the standard operation unit, and judging whether the standard operation unit same as the operation unit exists or not;
if the standard operation unit with the same operation unit does not exist, the operation unit is represented as a redundant operation unit; if the standard operation unit identical to the operation unit exists, the corresponding standard operation unit is numbered, and the number of the standard operation unit is consistent with that of the operation unit.
7. The automatic control system for product production line based on machine vision as claimed in claim 6, wherein said process of analyzing the operation state of equipment node by said data analysis module comprises: and obtaining the deviation coefficient of the equipment at each running node according to the coordinates of each running node of the running track and the coordinates of each running node of the standard running track.
8. The system of claim 7, wherein the process line adjustment module adjusts the production line by:
setting an operation deviation duration threshold, comparing the operation deviation duration with the operation deviation duration threshold, judging whether station nodes are normal or not, and marking the abnormal station nodes;
acquiring whether a marked station node has a redundant operation unit, if so, rejecting the redundant operation unit, acquiring operation deviation duration again, comparing the operation deviation duration with an operation deviation duration threshold, and judging whether the station node is a bottleneck node according to a comparison result;
and readjusting the production line speed according to the operation duration of the operation action of the staff of the bottleneck node.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115457040A (en) * | 2022-11-14 | 2022-12-09 | 青岛海天成光伏新能源有限公司 | Intelligent control method, device, equipment and medium for photovoltaic junction box production line |
| CN117075528A (en) * | 2023-10-17 | 2023-11-17 | 深圳市磐锋精密技术有限公司 | Mobile phone accessory rotating assembly line monitoring system based on data processing |
-
2022
- 2022-04-20 CN CN202210417878.XA patent/CN114895634A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115457040A (en) * | 2022-11-14 | 2022-12-09 | 青岛海天成光伏新能源有限公司 | Intelligent control method, device, equipment and medium for photovoltaic junction box production line |
| CN115457040B (en) * | 2022-11-14 | 2023-04-07 | 青岛海天成光伏新能源有限公司 | Intelligent control method, device, equipment and medium for photovoltaic junction box production line |
| CN117075528A (en) * | 2023-10-17 | 2023-11-17 | 深圳市磐锋精密技术有限公司 | Mobile phone accessory rotating assembly line monitoring system based on data processing |
| CN117075528B (en) * | 2023-10-17 | 2023-12-26 | 深圳市磐锋精密技术有限公司 | Mobile phone accessory rotating assembly line monitoring system based on data processing |
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