CN113917559A - Online monitoring system based on digital twins - Google Patents
Online monitoring system based on digital twins Download PDFInfo
- Publication number
- CN113917559A CN113917559A CN202111051335.2A CN202111051335A CN113917559A CN 113917559 A CN113917559 A CN 113917559A CN 202111051335 A CN202111051335 A CN 202111051335A CN 113917559 A CN113917559 A CN 113917559A
- Authority
- CN
- China
- Prior art keywords
- station
- filling
- quality inspection
- monitoring system
- storehouse
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 24
- 239000000463 material Substances 0.000 claims abstract description 31
- 238000007689 inspection Methods 0.000 claims abstract description 30
- 230000005540 biological transmission Effects 0.000 claims abstract description 11
- 238000012546 transfer Methods 0.000 claims description 5
- 238000013500 data storage Methods 0.000 claims description 2
- 230000001939 inductive effect Effects 0.000 claims 1
- 238000004519 manufacturing process Methods 0.000 abstract description 43
- 238000000034 method Methods 0.000 abstract description 16
- 230000008569 process Effects 0.000 abstract description 13
- 210000004907 gland Anatomy 0.000 abstract description 6
- 238000009826 distribution Methods 0.000 abstract description 3
- 238000003860 storage Methods 0.000 description 23
- 238000007726 management method Methods 0.000 description 19
- 238000004458 analytical method Methods 0.000 description 12
- 238000004088 simulation Methods 0.000 description 11
- 238000005516 engineering process Methods 0.000 description 10
- 238000012423 maintenance Methods 0.000 description 10
- 238000004364 calculation method Methods 0.000 description 9
- 238000011161 development Methods 0.000 description 9
- 230000006870 function Effects 0.000 description 8
- 238000001514 detection method Methods 0.000 description 7
- 238000012545 processing Methods 0.000 description 6
- 238000009792 diffusion process Methods 0.000 description 5
- 238000013461 design Methods 0.000 description 4
- 229910052751 metal Inorganic materials 0.000 description 4
- 239000002184 metal Substances 0.000 description 4
- 239000013307 optical fiber Substances 0.000 description 4
- 230000008859 change Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000012800 visualization Methods 0.000 description 3
- 229910052782 aluminium Inorganic materials 0.000 description 2
- XAGFODPZIPBFFR-UHFFFAOYSA-N aluminium Chemical compound [Al] XAGFODPZIPBFFR-UHFFFAOYSA-N 0.000 description 2
- 230000004888 barrier function Effects 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000007599 discharging Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 230000036541 health Effects 0.000 description 2
- 230000006698 induction Effects 0.000 description 2
- 230000002452 interceptive effect Effects 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000013439 planning Methods 0.000 description 2
- 239000002994 raw material Substances 0.000 description 2
- 238000007789 sealing Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007175 bidirectional communication Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000013523 data management Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000005429 filling process Methods 0.000 description 1
- 238000007654 immersion Methods 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000013433 optimization analysis Methods 0.000 description 1
- 238000012856 packing Methods 0.000 description 1
- 238000003908 quality control method Methods 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000008054 signal transmission Effects 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000005303 weighing Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS; TAGS
- G01V11/00—Prospecting or detecting by methods combining techniques covered by two or more of main groups G01V1/00 - G01V9/00
-
- 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
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
- G05B19/05—Programmable logic controllers, e.g. simulating logic interconnections of signals according to ladder diagrams or function charts
- G05B19/054—Input/output
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B25/00—Models for purposes not provided for in G09B23/00, e.g. full-sized devices for demonstration purposes
- G09B25/02—Models for purposes not provided for in G09B23/00, e.g. full-sized devices for demonstration purposes of industrial processes; of machinery
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B9/00—Simulators for teaching or training purposes
Abstract
The invention relates to an online monitoring system based on digital twins, and belongs to the technical field of information and automatic control. This monitoring system is including conveying station, storehouse station, filling station, gland station and quality inspection station, storehouse station carries out storehouse position scanning or record stock position to the filling material, the filling station is to treating the filling container and move to under the filling head, accomplishes the material filling, the gland station adds the lid operation to the container that the filling is good, the quality inspection station carries out the quality inspection to accomplishing the filling, the article after adding the lid, the conveying station is used for the transmission of article between storehouse station, filling station gland station and quality inspection station. The invention can model the layout of the whole factory production line on a digital twin platform, check the running state of equipment in the factory at a third person's view angle, monitor and manage personnel can collect data, process data and feed back data in time, dynamically make a corresponding production work plan and guide customers to know the distribution of the whole workshop and the conditions of a product production line.
Description
Technical Field
The invention relates to an online monitoring system based on digital twins, and belongs to the technical field of information and automatic control.
Background
In the existing intelligent factory operation and maintenance system, when a fault point occurs in an intelligent factory, the fault point is mostly searched by adopting a manual detection method, and then maintenance is carried out by maintenance personnel, so that operation and maintenance information cannot be directly embodied, the fault point cannot be rapidly positioned when the fault occurs, the operation process is complicated, the operation and maintenance time is greatly increased, the operation and maintenance efficiency is low,
compared with the mode of manually acquiring and processing data in management and production, the research of remote online state monitoring and diagnosis has poor real-time performance and low efficiency, the development of information technology greatly improves the production level of workshops, can timely collect, process and feed back data, and can dynamically make a production work plan so as to enable remote online monitoring. The digital twin intelligent factory is a new stage of modern factory informatization development, and is characterized in that on the basis of a digital factory, the technology of the Internet of things and the equipment monitoring technology are utilized to enhance information management and service, clearly master production and marketing processes, improve the controllability of a production process, reduce manual intervention on a production line, immediately and correctly acquire production line data, and reasonably arrange production plans and progress. And a green intelligent means, an intelligent system and other emerging technologies are integrated, so that a high-efficiency, energy-saving, green and environment-friendly humanized factory with comfortable environment is constructed.
Disclosure of Invention
The invention provides an online monitoring system based on digital twins, aiming at solving the problems of low automation degree and complexity of the existing manufacturing platform. The system can model the layout of the whole factory production line on a digital twin platform, check the running state of equipment in the factory at a third person weighing view angle, monitor and manage personnel can collect data, process data and feedback data in time, dynamically make a corresponding production work plan and guide a client to know the conditions of the whole workshop distribution and the product production line.
The invention adopts the following technical scheme for solving the technical problems:
the utility model provides an on-line monitoring system based on digit twin, includes conveying station, storehouse station, filling station, gland station and quality inspection station, storehouse station carries out position scanning or record stock position to the filling material, the filling station will treat that the filling container moves under the filling head, accomplishes the material filling, the gland station adds the lid operation to the container that the filling is good, the quality inspection station carries out the quality inspection to the article of accomplishing the filling, adding the lid, the conveying station is used for the transmission of article between storehouse station, filling station gland station and quality inspection station.
A stacker crane is arranged in the warehouse station and provided with two motors, wherein the stacker crane comprises an X-direction stepping motor and a Y-direction direct current motor.
And the conveying station, the warehouse station, the filling station, the capping station and the quality inspection station are internally provided with a data acquisition module, a data transmission module and a data storage module.
And a diffusion type photoelectric sensor is arranged in the conveying station.
And an inductance proximity sensor and a capacitance proximity sensor are arranged in the quality inspection station.
The invention has the following beneficial effects:
(1) the pure software simulation intelligent filling line based on the simulation technology is provided, a virtual simulation technology is applied, a simulation object written by software Flash, Unity3D or HTML5 is used, and S7-200SMART simulation PLC developed by C + + is used, so that green and safe industrial process object training is realized. The teaching is convenient, the capital expense is saved, and the maintenance cost is greatly reduced.
(2) And providing a semi-physical simulation interface, and realizing the control of a simulation object by utilizing a real PLC.
(3) Monitoring management personnel can collect data, process data and feedback data in time and dynamically make a corresponding production work plan.
(4) The method realizes interconnection and intercommunication among high-speed local modules, equipment and systems and quick high-speed manufacturing automation simulation (supporting high-speed servo motor object and control simulation).
(5) And independent development (independent animation, modeling and control) and interconnection and intercommunication of systems such as a visualization (VR, animation), a modeling, a real controller, a simulation controller, a built system, an ERP and the like are realized.
(6) Various bus accesses, semi-physical simulation accesses and interconnection and intercommunication between a real controller and a digital platform are supported, and seamless connection of virtual and real world is constructed.
(7) And the interconnection and intercommunication between various virtual and real system systems and the industrial cloud platform are realized through a uniform interface, so that a slave object, detection, control and monitoring are established.
(8) To wisdom filling line, can realize student's independent programming and many people's cooperation.
Drawings
Fig. 1 is a device part component preview diagram, in which: 1-conveying station, 2-warehouse station, 3-filling station, 4-capping station and 5-quality inspection station.
FIG. 2 is a diagram of a Web-based digital twin plant architecture model.
Fig. 3 is a cloud platform interface distribution diagram.
FIG. 4 is a flow chart of plant management.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention.
Before the embodiments of the present patent are described, a digital twin development platform is described to help understand the related schemes in the embodiments of the present invention. The digital twin development platform is used for completing the mapping of real automation equipment in a virtual space by utilizing data such as a digital model, sensor updating, operation signals and the like, and creating virtual equipment synchronous with the real equipment for the full life cycle management of equipment visualization.
In the manufacturing process of the digital twin filling workshop, firstly, a stacker crane in a warehouse station scans warehouse positions or waits for a user (or an image recognition system) to give warehouse position information, and judges the number and the types of materials, wherein one type is the primary color of aluminum, and the other type is partial or full black. The inventory location is recorded. The function of the filling station is to complete the transfer of the bottles from the material table to the position right below the filling head; the filling head is then moved by the stepper motor to the mouth of the bottle to complete the filling, and the filled bottle is then returned to the material station, where the function of the capping station is then to complete the assembly of the cap in the magazine of that station to the bottle placed in the assembly hopper. Wherein the two tubular silos are respectively provided with a plastic cover and a metal cover. The cover pushing device is used for storing workpiece raw materials and pushing the workpiece on the lowest layer in the storage bin to the discharging table when needed. The device mainly comprises two tubular bins, two material pushing cylinders, two material ejecting cylinders, a magnetic induction proximity switch and a diffusion type photoelectric sensor. The lower part is a turntable which sends the bottles to the lower part of the caps and then to a quality monitoring station by a conveyor belt, wherein the quality monitoring station is a final station and completes the quality detection of the filled and capped products sent from the previous station. And (5) performing quality inspection according to the attributes of the production single materials, and feeding the production single materials into a classification trough. When the conveying station sends a workpiece to the conveying belt and is detected by the photoelectric sensor at the feeding port, the frequency converter is started, and the workpiece is sent to the quality detection area for quality detection. The transmission and quality inspection mechanism mainly comprises a transmission belt, a discharge chute, a material pushing (quality inspection) cylinder, a diffusion type photoelectric sensor, an optical fiber sensor, an inductance proximity sensor (for detecting metal), and a capacitance proximity sensor (for detecting plastic). Conveying the machined and assembled workpieces, detecting the workpieces by an optical fiber sensor, performing quality inspection, driving a grabbing manipulator device of the grabbing manipulator device to be accurately positioned to a material platform of a designated station by a conveying station process function, grabbing bottles on the material platform, conveying the grabbed bottles to a designated place, putting the bottles down, putting the bottles into a paper box on a conveying crawler, and finally packing and sealing the paper box by an automatic box sealing machine to finally realize highly-automatic assembly line operation.
The intelligent filling line simulation system adopts a FLASH 2.5D design or a Unit3D design. Has a structure and an operation method substantially identical to those of a real system. The system consists of a stereoscopic warehouse, 5 workstations for filling, processing, assembling and quality inspection, as shown in figure 1.
Description of the technological Process of an Intelligent filling line
Warehouse station
The main structural components of the warehouse unit are as follows: warehouse positions, a stacker crane, an electromagnetic valve group, a terminal row assembly, a PLC, a bottom plate and the like. If there is no image recognition system, the transmission is manually recognized using a touch screen.
There are 4 rows and 4 columns of magazine locations, with the second row on the right being used to feed material to the transfer station. The library site has a sensor. The materials on the storage position comprise two types.
The stacker crane is provided with two motors, wherein the two motors comprise an X-direction stepping motor and a Y-direction direct-current motor, and a Z-direction horizontal pushing cylinder.
And the stacker crane returns to the original position after being started. And then waiting for the user to give the storage position information to obtain all the materials. Then, according to the order requirement, the material is obtained from the nearest position. When the stacking machine is started, the stacking machine scans the storage position or waits for a user (or an image recognition system) to give the storage position information, and the number and the type of the materials are judged, wherein one is the primary color of aluminum, and the other is partial or full black. The inventory location is recorded.
Second, filling station
The function of the filling station is to complete the transfer of the bottles to be transferred from the material station to just below the filling heads; the filling head is then moved by the stepper motor to the bottle mouth to complete the filling process, and the filled bottles are then returned to the material station.
Third, cover station
The function of the capping station is to complete the assembly of the caps in the magazine of the station to the bottles placed in the assembly hopper. Wherein the two tubular silos are respectively provided with a plastic cover and a metal cover. The cover pushing device is used for storing workpiece raw materials and pushing the workpiece on the lowest layer in the storage bin to the discharging table when needed. The device mainly comprises two tubular bins, two material pushing cylinders, two material ejecting cylinders, a magnetic induction proximity switch and a diffusion type photoelectric sensor. The lower part is a turntable which carries the bottles under the cap.
Four, quality inspection station
The quality inspection station is the last station and is used for performing quality inspection on the filled and capped products sent from the last station. And (5) performing quality inspection according to the attributes of the production single materials, and feeding the production single materials into a classification trough. When the conveying station sends a workpiece to the conveying belt and is detected by the photoelectric sensor at the feeding port, the frequency converter is started, and the workpiece is sent to the quality detection area for quality detection. The transmission and quality inspection mechanism mainly comprises a transmission belt, a discharge chute, a material pushing (quality inspection) cylinder, a diffusion type photoelectric sensor, an optical fiber sensor, an inductance proximity sensor (for detecting metal), and a capacitance proximity sensor (for detecting plastic). And conveying the machined and assembled workpiece, detecting the workpiece by an optical fiber sensor and performing quality inspection.
Fifth, the transfer station
The process functions of the conveying station are as follows: the gripping manipulator device is driven to be accurately positioned to a material platform of a designated station, the bottles are gripped on the material platform, and the gripped bottles are conveyed to a designated place and then put down.
Based on a digital twin development platform, the embodiment of the invention provides a factory management system which is used for managing an equal-scale 3D model of a factory. The specific scheme is as follows:
as shown in FIG. 2, the digital structure system of the workshop researched in the invention aims to form a remote monitoring system of the workshop manufacturing process, and the important point is to realize the analysis management and diversified remote application of the workshop data, so that the invention provides a Web-based digital twin workshop structure model, which comprises the following five layers, namely a physical entity layer, a virtual model layer, a data barrier layer, an analysis and calculation layer, a system application layer and the like.
The entity set which exists in the production workshop mainly comprises entity elements such as a production factory building, production equipment, processing materials, a sensing detector, operators, environment and the like, wherein the elements are coordinated with each other to receive a production task, execute a production instruction, collect production data and finish a production process. Is the basis of the digital structure modeling of the production workshop.
The virtual model layer is a mirror image super-realistic model of a physical entity layer, is a digital mirror image containing all information and knowledge, and comprises 4 layers of concepts such as a geometric model, a physical model, a behavior model and a rule model. The method comprises the steps of obtaining a physical entity layer, a geometric model, a physical model and a rule model, wherein the physical entity layer comprises a plurality of physical entity layers, the geometric model describes geometric relevant parameters such as size, shape, position and assembly relation of the physical entity elements, the physical model analyzes physical attributes such as stress, strain and fatigue of the physical entity elements, the behavior model describes response of the physical entity layer to external input or interference, and the rule model evaluates, optimizes and predicts operation rules of the physical entity layer. The virtual model layer has multiple characteristics such as uniqueness, virtualization, multi-physics, multi-scale and multi-hierarchy, integration, dynamics, super-writability, computability, probability, multidisciplinary and the like, and is responsible for describing the functions of monitoring and analyzing, simulating and optimizing, predicting and regulating the production process in a virtual space.
The data barrier layer is used as a support for the operation of the whole upper layer system and mainly comprises three parts of data acquisition, data transmission and data management. The data sources of the system mainly comprise physical entity layer data, virtual model layer data, analysis and calculation layer data, service application layer data, data generated in the interaction process of the physical entity layer data, the virtual model layer data, the analysis and calculation layer data, the service application layer data, data transmitted by MES, ERP, DOM and other systems, cover all elements, all services and all processes, are supplemented, updated and cleaned along with the arrival of real-time data, and are the driving and engine for the operation of the rest four layers. By means of the advanced sensing technology and the signal transmission and storage technology, data can be acquired more quickly, accurately and sufficiently, a workshop field information island is eliminated, centralized management and control of workshop automation equipment are achieved comprehensively, the production process is transparent and controllable, relevant personnel can know the running state of the equipment and the workshop production condition in real time conveniently, and the monitoring and management intelligence of the workshop production process is guaranteed.
The analysis and calculation layer is an important function support layer, and brings 'intelligence' to the production line. The software mainly expresses computer programs of a physical model, a behavior model and a rule model in a virtual model layer, and also comprises algorithms such as signal processing, machine learning, processing quality analysis, fault diagnosis prediction, equipment health management, resource optimization configuration, workshop scheduling, energy consumption management, visualization, data fusion and mining, closed-loop control and the like, and computing methods such as high-performance, large-scale and distributed computing. The analysis and calculation layer extracts characteristic data capable of reflecting the essence of the problem from the disordered original data, and the obtained result is really useful information, and the analysis and calculation layer directly provides support for various services of the system application layer and is finally used for the construction of an intelligent workshop.
The system application layer of the invention provides corresponding functional modules for the production, logistics, maintenance and other requirements of an actual production workshop, integrates various information systems such as monitoring, control, analysis, management and the like, and provides services and support for the intelligent management and control tasks of the workshop such as intelligent planning and scheduling, process path planning, production process management and control, equipment health management, product quality control, energy efficiency optimization analysis, service fusion coordination and the like under the support of the driving of a data protection layer and an analysis and calculation layer. The system application layer provides intelligent manufacturing, real-time monitoring, optimal management and reliable operation and maintenance services, a user can obtain a clear and visual display form easy to understand, meanwhile, the user can interact with the system, and even immersion feelings of VR, AR and MR can be further obtained. The system application layer should meet the following requirements for ease of use and maintenance:
1. the system has rich interfaces, and a system application layer must be connected and communicated with a data protection layer, an analysis and calculation layer and the like;
2. has friendly interface, the display of the interface is in line with professional characteristics, and the interface is simple and intuitive and is easy to operate
3. The coupling among all modules is low, and when one module is changed, the normal work of other modules is not influenced.
The VR animation design three-dimensional animation in the invention is also called 3D animation, and is a model for developing and applying a computer virtual program. Firstly, a corresponding virtual portrait is established according to an image through a virtual program, secondly, the motion trail of the model is set according to the regulation and control size of the object image, the motion and parameter change conditions of virtual photography are determined, and finally, external auxiliary factors required by the motion change of the object image of the main body, such as application of light and color, are added. And after the intelligent program is started, the corresponding elements are projected at the same time, and finally, the corresponding graphs are obtained. Compared with the common two-dimensional graph change, the three-dimensional animation can well integrate the front view, the top view and the side view into a whole, complete the whole application of the dynamic image quality and strengthen the reality and the clearness of the whole image quality. With further analysis and exploration of the three-dimensional animation technology, color adjustment and character modeling establishment in the three-dimensional animation creation process become three-dimensional and full, and the application field is continuously expanded.
As shown in fig. 3, in the cloud platform interface development of the present invention, the cloud platform is composed of four parts, including a storage layer, a base management layer, an application interface layer, and an access layer.
The storage tier is the most basic part of cloud storage. The storage device may be an FC fibre channel storage device, an IP storage device such as NAS and iSCSI, or a DAS storage device such as SCSI or SAS. Storage devices in cloud storage tend to be large in number and distributed over many different regions. Connected together through a wide area network, the internet or an FC fibre channel network.
The basic management layer is the most core part of the cloud storage and is the most difficult part to realize in the cloud storage. The basic management layer realizes cooperative work among a plurality of storage devices in cloud storage through technologies such as clustering, a distributed file system and grid computing, so that the plurality of storage devices can provide the same service to the outside and provide stronger and better data access performance.
The application interface layer is the most flexible and changeable part of the cloud storage. Different cloud storage operation units can develop different application service interfaces according to actual service types and provide different application services. Such as video surveillance application platforms, IPTV and video-on-demand application platforms, network hard disk application platforms, remote data backup application platforms, and the like.
The access layer is a man-machine interactive interface, provides an interactive channel between equipment and people, is bidirectional communication, and can be used for clients to request new access on terminal equipment.
As shown in fig. 4, the intelligent production digital twin platform includes a cloud platform interface development module, other configuration development, a VR animation design module, and a touch screen program development module, and the three or more of the following may be used for the simulation component: linear motion, rotary motion, pneumatic cylinder motion, and also the five stations mentioned above: the three-dimensional warehouse comprises a stereoscopic warehouse, filling, processing, assembling and quality inspection, wherein N stations are used for developing programs, the developed programs are sent to S7-200SMART, and then the developed programs are sent to an intelligent production line digital twin platform through S7-200 SMART.
Claims (5)
1. The utility model provides an on-line monitoring system based on digit twin, its characterized in that, includes conveying station, storehouse station, filling station, capping station and quality inspection station, storehouse station carries out storehouse level scanning or record stock position to the filling material, the filling station is to waiting that the filling container moves to under the filling head, accomplishes the material filling, capping station adds the lid operation to the container that the filling is good, the quality inspection station carries out the quality inspection to the article of accomplishing the filling, after adding the lid, conveying station is used for the transmission of article between storehouse station, filling station capping station and quality inspection station.
2. The digital twin-based online monitoring system according to claim 1, wherein a stacker crane is arranged in the warehouse station, and the stacker crane has two motors, including an X-direction stepping motor and a Y-direction direct current motor.
3. The digital twin-based online monitoring system as claimed in claim 1, wherein a data acquisition module, a data transmission module and a data storage module are arranged in the conveying station, the warehouse station, the filling station, the capping station and the quality inspection station.
4. The digital twin based on-line monitoring system as claimed in claim 1 wherein a diffuse photo sensor is provided within the transfer station.
5. The digital twin-based online monitoring system as claimed in claim 1, wherein an inductive proximity sensor and a capacitive proximity sensor are arranged in the quality inspection station.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111051335.2A CN113917559A (en) | 2021-09-08 | 2021-09-08 | Online monitoring system based on digital twins |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111051335.2A CN113917559A (en) | 2021-09-08 | 2021-09-08 | Online monitoring system based on digital twins |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113917559A true CN113917559A (en) | 2022-01-11 |
Family
ID=79234354
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111051335.2A Pending CN113917559A (en) | 2021-09-08 | 2021-09-08 | Online monitoring system based on digital twins |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113917559A (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE3801651A1 (en) * | 1988-01-21 | 1989-08-03 | Roland Stengel | Process and apparatus for the automatic rejection of leaking containers, detected by a testing device, from a production line |
| CN202166628U (en) * | 2011-07-01 | 2012-03-14 | 淄博职业学院 | Remote multi-channel wireless chemical oxygen demand (COD) detection alarming system based on capacitive sensor |
| CN203578236U (en) * | 2013-12-10 | 2014-05-07 | 刘显忠 | Conveying and sorting mechanism for automatic production line |
| CN103878414A (en) * | 2014-03-30 | 2014-06-25 | 上海工程技术大学 | Flexible manufacturing production line |
| CN106406263A (en) * | 2016-11-25 | 2017-02-15 | 四川普什宁江机床有限公司 | Flexible manufacturing automatic logistics control method |
| CN206095981U (en) * | 2016-08-31 | 2017-04-12 | 信码互通（北京）科技有限公司 | Bottle lid coding quality inspection system |
| CN107746036A (en) * | 2017-11-09 | 2018-03-02 | 陕西海澳特环保科技有限公司 | The full-automatic canning line system of five gallon bottle drummed pure water |
| CN207107081U (en) * | 2017-09-06 | 2018-03-16 | 漳州片仔癀药业股份有限公司 | The automatic detection device of bottled product liquid level and bottle cap aluminium foil |
| CN108036519A (en) * | 2018-01-23 | 2018-05-15 | 北京国铁科林科技股份有限公司 | The boiler of water quality can be detected |
| CN110716501A (en) * | 2019-11-18 | 2020-01-21 | 康美包（苏州）有限公司 | Data transmission method, equipment and device and computer storage medium |
| CN110765589A (en) * | 2019-09-10 | 2020-02-07 | 上海大学 | Intelligent workshop virtual and real synchronous monitoring system and method based on digital twins |
| CN212459512U (en) * | 2020-07-24 | 2021-02-02 | 夏海龙 | Inductively coupled plasma mass spectrometer for water quality detection |
-
2021
- 2021-09-08 CN CN202111051335.2A patent/CN113917559A/en active Pending
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE3801651A1 (en) * | 1988-01-21 | 1989-08-03 | Roland Stengel | Process and apparatus for the automatic rejection of leaking containers, detected by a testing device, from a production line |
| CN202166628U (en) * | 2011-07-01 | 2012-03-14 | 淄博职业学院 | Remote multi-channel wireless chemical oxygen demand (COD) detection alarming system based on capacitive sensor |
| CN203578236U (en) * | 2013-12-10 | 2014-05-07 | 刘显忠 | Conveying and sorting mechanism for automatic production line |
| CN103878414A (en) * | 2014-03-30 | 2014-06-25 | 上海工程技术大学 | Flexible manufacturing production line |
| CN206095981U (en) * | 2016-08-31 | 2017-04-12 | 信码互通（北京）科技有限公司 | Bottle lid coding quality inspection system |
| CN106406263A (en) * | 2016-11-25 | 2017-02-15 | 四川普什宁江机床有限公司 | Flexible manufacturing automatic logistics control method |
| CN207107081U (en) * | 2017-09-06 | 2018-03-16 | 漳州片仔癀药业股份有限公司 | The automatic detection device of bottled product liquid level and bottle cap aluminium foil |
| CN107746036A (en) * | 2017-11-09 | 2018-03-02 | 陕西海澳特环保科技有限公司 | The full-automatic canning line system of five gallon bottle drummed pure water |
| CN108036519A (en) * | 2018-01-23 | 2018-05-15 | 北京国铁科林科技股份有限公司 | The boiler of water quality can be detected |
| CN110765589A (en) * | 2019-09-10 | 2020-02-07 | 上海大学 | Intelligent workshop virtual and real synchronous monitoring system and method based on digital twins |
| CN110716501A (en) * | 2019-11-18 | 2020-01-21 | 康美包（苏州）有限公司 | Data transmission method, equipment and device and computer storage medium |
| CN212459512U (en) * | 2020-07-24 | 2021-02-02 | 夏海龙 | Inductively coupled plasma mass spectrometer for water quality detection |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109375601B (en) | Pipeline planning method and equipment based on data-driven modeling and simulation optimization | |
| CN109375595B (en) | Visual workshop monitoring method, device and equipment | |
| CN108510866B (en) | Comprehensive practice teaching system of intelligent manufacturing technology | |
| CN111857065A (en) | Intelligent production system and method based on edge calculation and digital twinning | |
| CN106022523B (en) | A kind of automatic production line Optimization Design based on integrated emulation | |
| CN113093680A (en) | FIMS system architecture design method based on digital twin technology | |
| Yang et al. | Cloud-edge-device collaboration mechanisms of deep learning models for smart robots in mass personalization | |
| CN107145132A (en) | Miniature wisdom plant experiment and research platform | |
| CN106530939A (en) | Control system and control method for multi-robot teaching and practical training platform | |
| CN105023500A (en) | Intelligent assembly line experimental device | |
| Liu et al. | Digital twin-enabled machining process modeling | |
| CN116485576A (en) | Intelligent manufacturing management platform for brain data with known source in aviation manufacturing industry | |
| CN115129004A (en) | Intelligent production system and method based on edge calculation and digital twinning | |
| CN107368586A (en) | A kind of multisystem data analysing method and platform | |
| CN114578770A (en) | Digital twin formula intelligence production line system | |
| CN116540584A (en) | Intelligent management and control system of unmanned production line of fusion-cast charging | |
| CN116468287A (en) | Intelligent park control system based on digital twinning | |
| CN116415386A (en) | Digital twin production line visualization system based on real-time data driving | |
| CN114384881A (en) | Workshop logistics monitoring and simulation system and method based on digital twins | |
| CN206892650U (en) | Miniature wisdom plant experiment and research platform | |
| CN113917559A (en) | Online monitoring system based on digital twins | |
| CN111401154B (en) | AR-based logistics accurate auxiliary operation device for transparent distribution | |
| CN116308043A (en) | System for constructing three-dimensional warehouse based on automation | |
| Kaczmarczyk et al. | Revisiting the role of manufacturing execution systems in Industry 4.0 | |
| Zhao et al. | A framework for development of digital twin industrial robot production lines based on a mechatronics approach |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |