CN112547352B - Automatic spraying monitoring teleoperation method and system based on digital twinning - Google Patents
Automatic spraying monitoring teleoperation method and system based on digital twinning Download PDFInfo
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- CN112547352B CN112547352B CN202011228212.7A CN202011228212A CN112547352B CN 112547352 B CN112547352 B CN 112547352B CN 202011228212 A CN202011228212 A CN 202011228212A CN 112547352 B CN112547352 B CN 112547352B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B05—SPRAYING OR ATOMISING IN GENERAL; APPLYING FLUENT MATERIALS TO SURFACES, IN GENERAL
- B05B—SPRAYING APPARATUS; ATOMISING APPARATUS; NOZZLES
- B05B12/00—Arrangements for controlling delivery; Arrangements for controlling the spray area
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computing arrangements using knowledge-based models
- G06N5/02—Knowledge representation; Symbolic representation
- G06N5/022—Knowledge engineering; Knowledge acquisition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T19/00—Manipulating 3D models or images for computer graphics
- G06T19/006—Mixed reality
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y10/00—Economic sectors
- G16Y10/25—Manufacturing
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/20—Analytics; Diagnosis
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/30—Control
Abstract
The application discloses an automatic spraying monitoring teleoperation method and system based on digital twinning, wherein the method comprises the following steps: monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhancement model; if the automatic paint spraying process is monitored to be abnormal, diagnosing the fault according to the knowledge base, determining the type and the occurrence reason of the fault, and obtaining a solution; and switching from the monitoring mode to a fault teleoperation mode, and processing the fault through the teleoperation controller. The real-time digital signals of the field state are obtained through the sensing network, and judgment can be made more efficiently and accurately by utilizing the real-time enhancement model, so that the machine can be controlled better. The operator starts the emergency treatment system by shaking operation to remove equipment faults. The possible fault types can be diagnosed through the knowledge base, and according to the fault processing method in the example, the current fault processing method and the suggestion are provided to realize accurate and rapid processing of the fault.
Description
Technical Field
The application relates to the technical field of automatic spraying, in particular to an automatic spraying monitoring teleoperation method and system based on digital twinning.
Background
A machine part is an essential element constituting a machine, and is a non-detachable single piece constituting both the machine and the machine. In order to protect the parts and avoid surface oxidation or damage of the parts, part production methods generally need to paint the parts in the prior art.
Mostly manual operation sprays paint to gyration type part among the conventional art, arranges the part in a single file and puts, and the spraying of spray gun straight reciprocating motion spraying. And after finishing spraying, waiting for drying the paint on the surface of the part, and boxing the part. Because manual operation exists inefficiency, and the toxic substance in the paint threatens staff's health, consequently adopts the automatic machine that sprays paint to the part spraying among the prior art.
The fault treatment in the automatic paint spraying process is an important link for ensuring the product quality in the actual production process, but the fault diagnosis result is inaccurate along with the occurrence of various complex data, and the normal spraying operation is influenced.
Disclosure of Invention
In order to solve the technical problems, the following technical scheme is provided:
in a first aspect, an embodiment of the present application provides an automatic spraying monitoring teleoperation method based on digital twinning, where the method includes: monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhancement model; if the automatic paint spraying process is monitored to be abnormal, diagnosing the fault according to the knowledge base, determining the type and the occurrence reason of the fault, and obtaining a solution; after the solution is obtained, the monitoring mode is switched to the fault teleoperation mode, and the fault is processed through the teleoperation controller.
By adopting the implementation mode, the signals with different formats can be preprocessed by the multi-source heterogeneous data through different data acquisition interfaces of the sensor network, and the real-time digital signals of the field state are obtained. The digital twin and augmented reality technology is utilized to establish a field real-time augmented model of the spraying operation, so that an operator can make judgment more efficiently and accurately so as to control a machine better. The safety risk caused by human factors can be reduced by adopting a teleoperation technology, and an operator starts an emergency treatment system by using the remote operation to remove equipment faults. The possible fault types can be diagnosed through the knowledge base, and according to the fault processing method in the example, the current fault processing method and the suggestion are provided to realize accurate and rapid processing of the fault.
With reference to the first aspect, in a first possible implementation manner of the first aspect, the monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhanced model includes: determining the composition and layout of an automatic spraying teleoperation assembly control device; and the establishment of the automatic spraying field augmented reality modeling is realized through multi-source data processing, multi-source information registration and virtual-real information fusion in sequence.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner of the first aspect, the establishing of the automatic spraying field augmented reality modeling by sequentially performing the multi-source data processing, the multi-source information registration, and the virtual-real information fusion includes: under the support of a workshop characteristic data model and an information expression template, rapidly extracting, identifying and optimizing characteristic data and key information of multi-source data acquired on site, and further realizing uniform expression of heterogeneous information; registering the multi-source sensing information based on a least square rule and a maximum likelihood registration algorithm; and dynamically calibrating the field real-time information and the 3D virtual model in real time, and performing interaction of multi-source information on the model to obtain an automatic spraying field virtual-real fusion enhanced model.
With reference to the first aspect, in a third possible implementation manner of the first aspect, operation data, fault data, historical data, process data, resource data, safety processing data, and the like used in teleoperation control are reasonably stored in a knowledge base, where the knowledge base includes a fault instance knowledge base and a fault diagnosis rule knowledge base, the fault instance knowledge base stores fault phenomena, fault sources, and fault causes of faults, and the fault diagnosis rule knowledge base stores rules for diagnosing, reasoning, determining, and processing faults.
With reference to the third possible implementation manner of the first aspect, in a fourth possible implementation manner of the first aspect, if it is monitored that an automatic paint spraying process is abnormal, a fault is diagnosed according to a knowledge base, a type and a cause of the fault are determined, and a solution is obtained, where the method includes: firstly, loading a fault phenomenon, determining a search strategy, and searching an instance library by using the search strategy to obtain a similar fault instance set; obtaining an example meeting a similarity threshold value for reuse through example matching calculation; and (3) performing analog analysis on similar examples, diagnosing the type of the fault which possibly occurs, and proposing a current fault handling method proposal according to the fault handling method in the examples to provide a basis for teleoperation control.
With reference to the fourth possible implementation manner of the first aspect, in a fifth possible implementation manner of the first aspect, after the obtaining the solution, the monitoring mode is switched to a fault teleoperation mode, and the processing of the fault by the teleoperation controller includes: switching modes, namely switching from a normal automatic operation mode to a teleoperation safety processing mode; determining the fault type and proposing a safety processing mode suggestion based on a fault mode and processing method knowledge base, and guiding teleoperation personnel to carry out remote safety processing; and the teleoperation personnel operates the teleoperation controller to process the safety problem, the teleoperation controller generates a teleoperation signal, the teleoperation signal is transmitted to a PLC (programmable logic controller) of the paint spraying equipment through conversion, the field equipment is controlled to execute a teleoperation processing action, and after the safety processing is finished, the teleoperation processing process of the safety problem is ended.
In a second aspect, an embodiment of the present application provides a digital twin-based automatic spray monitoring teleoperation system, including: the monitoring module is used for monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhancement model; the fault diagnosis and judgment module is used for diagnosing the fault according to the knowledge base if the abnormity of the automatic paint spraying process is monitored, determining the type and the occurrence reason of the fault and obtaining a solution; and the processing module is used for switching the monitoring mode into a fault teleoperation mode after the solution is obtained, and processing the fault through the teleoperation controller.
With reference to the second aspect, in a first possible implementation manner of the second aspect, the monitoring module includes: the determining unit is used for determining the composition and the layout of the automatic spraying teleoperation assembly control device; and the model establishing unit is used for realizing the establishment of the automatic spraying field augmented reality modeling by sequentially carrying out multi-source data processing, multi-source information registration and virtual-real information fusion.
With reference to the second aspect, in a second possible implementation manner of the second aspect, the fault diagnosis determining module includes: the first acquisition unit is used for loading the fault phenomenon, determining a search strategy and searching the instance library by using the search strategy to obtain a similar fault instance set; the second acquisition unit is used for acquiring the instances meeting the similarity threshold value for reuse through instance matching calculation; and the diagnosis and judgment unit is used for diagnosing the type of the fault which possibly occurs by carrying out analog analysis on the similar examples, and providing a current fault processing method suggestion according to the fault processing method in the examples so as to provide a basis for teleoperation control.
With reference to the second possible implementation manner of the second aspect, in a third possible implementation manner of the second aspect, the processing module includes: the mode switching unit is used for switching the mode from a normal automatic operation mode to a remote operation safety processing mode; the remote control unit is used for determining the fault type and proposing a safety processing mode suggestion based on the fault mode and the processing method knowledge base and guiding teleoperation personnel to carry out remote safety processing; and the processing unit is used for the teleoperation personnel to operate the teleoperation controller to process the safety problem, the teleoperation controller generates a teleoperation signal, the teleoperation signal is transmitted to the PLC of the paint spraying equipment through conversion, the field equipment is controlled to execute a teleoperation processing behavior, and after the safety processing is finished, the teleoperation processing process of the safety problem is ended.
Drawings
Fig. 1 is a schematic flow chart of an automatic spraying monitoring teleoperation method based on digital twinning according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of the hardware components and layout of an automatic coating teleoperation assembly control system according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of spray painting site perception information processing and augmented reality modeling provided in an embodiment of the present application;
FIG. 4 is a schematic diagram of a database storage structure according to an embodiment of the present application;
FIG. 5 is a schematic diagram of a fault instance knowledge base and a fault diagnosis rule knowledge base provided by an embodiment of the present application;
FIG. 6 is a schematic diagram of an ontology structure of an automatic painting failure provided by an embodiment of the present application;
FIG. 7 is a schematic diagram of a knowledge-base-based automatic paint failure diagnosis process provided by an embodiment of the present application;
fig. 8 is a schematic view of an automatic spraying monitoring teleoperation system based on digital twinning according to an embodiment of the present disclosure.
Detailed Description
The present invention will be described with reference to the accompanying drawings and embodiments.
Fig. 1 is a schematic flow chart of an automatic spraying monitoring teleoperation method based on digital twinning provided in an embodiment of the present application, and referring to fig. 1, the method includes:
s101, monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhancement model.
Firstly, considering the composition and layout of the automatic spraying teleoperation assembly control device, as shown in fig. 2, the field data sensed by the automatic spraying field sensor enters the data acquisition PLC through different data interfaces for rapid preprocessing and structured coding. When a safety problem occurs, a user transmits a control signal to the equipment control PLC through the optical fiber and the switch by remote processing, and then the control signal is transmitted to each on-site execution equipment, and safety processing is performed according to a control instruction.
In order to establish a real-time on-site augmented reality model, as shown in fig. 3, the automatic spraying on-site augmented reality modeling is divided into three steps including multi-source data processing, multi-source information registration and virtual-real information fusion.
Multi-source data processing: under the support of a workshop characteristic data model and an information expression template, characteristic data and key information of multi-source data collected on site are quickly extracted, identified and optimized, and then uniform expression of heterogeneous information is realized;
multi-source information registration: registering the multi-source sensing information based on a least square rule and a maximum likelihood registration algorithm;
fusing virtual and actual information: and carrying out dynamic real-time calibration on the field real-time information and the 3D virtual model, and carrying out interaction on multi-source information on the model to finally obtain the automatic spraying field virtual-real fusion enhanced model.
S102, if the situation that the automatic paint spraying process is abnormal is monitored, diagnosing the fault according to the knowledge base, determining the type and the reason of the fault, and obtaining a solution.
In order to reasonably store various data in the knowledge base, as shown in fig. 4, a storage structure of the database is designed, and operation data, fault data, history data, process data, resource data, safety processing data, and the like used in the remote operation control are reasonably stored in the database. In the figure, rectangular boxes represent entities, connecting lines between the boxes represent relations between the entities, and attribute names in the boxes represent attributes of the entities.
In order to realize reasonable fault diagnosis, the knowledge base is divided into a fault example knowledge base and a fault diagnosis rule knowledge base as shown in fig. 5 according to the requirement of equipment fault maintenance support. The fault instance knowledge base stores fault phenomena, fault sources and fault reasons of the faults. The fault diagnosis rule knowledge base stores rules for diagnosing, reasoning, judging and processing faults.
And analyzing the hierarchical relationship according to the core concept and the 5 top classes of the painting fault extraction to obtain the knowledge ontology structure of the automatic painting fault shown in the figure 6. The method comprises 3 pieces of basic information of fault phenomena, fault sources and fault reasons: the failure phenomenon refers to an abnormal phenomenon or state shown by the paint spraying equipment and the environment when the failure occurs; the failure source refers to a failed device; the cause of the failure guides the specific factors that cause the failure to occur.
The specific steps of fault diagnosis are shown in fig. 7: firstly, loading the fault phenomenon, determining a search strategy, and searching an instance library by using the search strategy to obtain a similar fault instance set. And obtaining the instances meeting the similarity threshold value for reuse through instance matching calculation. And (3) performing analog analysis on similar examples, diagnosing the type of the fault which possibly occurs, and proposing a current fault handling method proposal according to the fault handling method in the examples to provide a basis for teleoperation control.
S103, after the solution is obtained, the monitoring mode is switched to a fault teleoperation mode, and the fault is processed through the teleoperation controller.
The working process of the teleoperation control module can be known, the real-time monitoring of the paint spraying process is carried out based on the virtual and real enhancement model in the paint spraying process, and once a safety fault occurs, the teleoperation control processing of the safety problem can be started immediately. When a safety fault occurs:
firstly, switching modes, namely switching from a normal automatic operation mode to a teleoperation safety processing mode;
secondly, determining the fault type and proposing a safety processing mode suggestion based on a fault mode and processing method knowledge base, and guiding teleoperation personnel to carry out remote safety processing;
and finally, the teleoperation personnel operates the teleoperation controller to process the safety problem, the teleoperation controller generates a teleoperation signal, the teleoperation signal is transmitted to a PLC of the paint spraying equipment through conversion, the field equipment is controlled to execute a teleoperation processing action, and after the safety processing is finished, the teleoperation processing process of the safety problem is ended.
According to the embodiment, the automatic spraying monitoring teleoperation method based on the digital twin is provided, signals with different formats can be preprocessed through different data acquisition interfaces of a sensor network, and real-time digital signals of a field state are obtained. The digital twin and augmented reality technology is utilized to establish a field real-time augmented model of the spraying operation, so that an operator can make judgment more efficiently and accurately so as to control a machine better. The safety risk caused by human factors can be reduced by adopting a teleoperation technology, and an operator starts an emergency treatment system by using the remote operation to remove equipment faults. The possible fault types can be diagnosed through the knowledge base, and according to the fault processing method in the example, the current fault processing method and the suggestion are provided to realize accurate and rapid processing of the fault.
Corresponding to the automatic spraying monitoring teleoperation method based on the digital twin provided by the above embodiment, the present application also provides an embodiment of an automatic spraying monitoring teleoperation system based on the digital twin, and referring to fig. 8, the automatic spraying monitoring teleoperation system 20 based on the digital twin includes: a monitoring module 201, a fault diagnosis judging module 202 and a processing module 203.
The monitoring module 201 is used for monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhancement model. If the fault diagnosis and judgment module 202 monitors that the automatic paint spraying process is abnormal, the fault is diagnosed according to the knowledge base, the type and the occurrence reason of the fault are determined, and a solution is obtained. The processing module 203 is configured to switch the monitoring mode to the fault teleoperation mode after obtaining the solution, and process the fault through the teleoperation controller.
Further, the monitoring module 201 includes: a determining unit and a model building unit.
And the determining unit is used for determining the composition and the layout of the automatic spraying teleoperation assembly control device. The model establishing unit is used for realizing the establishment of the automatic spraying field augmented reality modeling through multi-source data processing, multi-source information registration and virtual-real information fusion in sequence.
Specifically, under the support of a workshop characteristic data model and an information expression template, the characteristic data and key information of multi-source data collected on site are quickly extracted, identified and optimized, and then the uniform expression of heterogeneous information is realized; registering the multi-source sensing information based on a least square rule and a maximum likelihood registration algorithm; and dynamically calibrating the field real-time information and the 3D virtual model in real time, and performing interaction of multi-source information on the model to obtain an automatic spraying field virtual-real fusion enhanced model.
The fault diagnosis determining module 200 includes: the device comprises a first acquisition unit, a second acquisition unit and a diagnosis judgment unit.
The method comprises the steps of reasonably storing operation data, fault data, historical data, process data, resource data, safety processing data and the like used in teleoperation control in a knowledge base, wherein the knowledge base comprises a fault instance knowledge base and a fault diagnosis rule knowledge base, the fault instance knowledge base stores fault phenomena, fault sources and fault reasons of faults, and the fault diagnosis rule knowledge base stores rules for diagnosing, reasoning, judging and processing the faults.
The first obtaining unit is used for loading the fault phenomenon, determining a search strategy, and searching the example base by using the search strategy to obtain a similar fault example set. And the second acquisition unit is used for acquiring the instances meeting the similarity threshold value for reuse through instance matching calculation. The diagnosis and judgment unit is used for diagnosing the type of the fault which possibly occurs by carrying out analog analysis on the similar examples, and providing a current fault processing method suggestion according to the fault processing method in the examples so as to provide a basis for teleoperation control.
The processing module 203 comprises: the remote control system comprises a mode switching unit, a remote control unit and a processing unit.
And the mode switching unit is used for switching the mode from a normal automatic operation mode to a teleoperation safe processing mode. And the remote control unit is used for determining the fault type and proposing a safety processing mode suggestion based on the fault mode and the processing method knowledge base, and guiding teleoperation personnel to carry out remote safety processing. The processing unit is used for a teleoperation operator to operate the teleoperation controller to process safety problems, the teleoperation controller generates teleoperation signals, the teleoperation signals are transmitted to a PLC of the paint spraying equipment through conversion, the field equipment is controlled to execute teleoperation processing behaviors, and after the safety processing is finished, the teleoperation processing process of the safety problems is ended.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Of course, the above description is not limited to the above examples, and technical features that are not described in this application may be implemented by or using the prior art, and are not described herein again; the above embodiments and drawings are only for illustrating the technical solutions of the present application and not for limiting the present application, and the present application is only described in detail with reference to the preferred embodiments instead, it should be understood by those skilled in the art that changes, modifications, additions or substitutions within the spirit and scope of the present application may be made by those skilled in the art without departing from the spirit of the present application, and the scope of the claims of the present application should also be covered.
Claims (7)
1. A digital twin-based automatic spraying monitoring teleoperation method is characterized by comprising the following steps:
monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhancement model;
the real-time monitoring of the automatic paint spraying site through the sensing network and the establishment of the site real-time enhancement model comprise the following steps:
determining the composition and layout of an automatic spraying teleoperation assembly control device;
the establishment of the automatic spraying field augmented reality modeling is realized through multi-source data processing, multi-source information registration and virtual-real information fusion in sequence;
the establishment of the automatic spraying field augmented reality modeling is realized through multi-source data processing, multi-source information registration and virtual-real information fusion in sequence, and the establishment comprises the following steps:
under the support of a workshop characteristic data model and an information expression template, rapidly extracting, identifying and optimizing characteristic data and key information of multi-source data acquired on site, and further realizing uniform expression of heterogeneous information;
registering multi-source information based on a least square rule and a maximum likelihood registration algorithm;
carrying out dynamic real-time calibration on the field real-time information and the 3D virtual model, and carrying out interaction on multi-source information on the model to obtain an automatic spraying field virtual-real fusion enhanced model;
if the automatic paint spraying process is monitored to be abnormal, diagnosing the fault according to the knowledge base, determining the type and the occurrence reason of the fault, and obtaining a solution;
after the solution is obtained, the monitoring mode is switched to a fault teleoperation mode, and the fault is processed through the teleoperation controller.
2. The method of claim 1, wherein operational data, fault data, historical data, process data, resource data, and safety process data used in teleoperational control are stored in a knowledge base comprising a fault instance knowledge base storing fault phenomena, fault sources, and fault causes of faults, and a fault diagnosis rule knowledge base storing rules for diagnosing, reasoning, determining, and handling faults.
3. The method of claim 2, wherein if it is detected that an abnormality occurs in the automatic painting process, the fault is diagnosed according to a knowledge base, the type and cause of the occurrence of the fault are determined, and a solution is obtained, comprising:
firstly, loading a fault phenomenon, determining a search strategy, and searching an instance library by using the search strategy to obtain a similar fault instance set;
obtaining an example meeting a similarity threshold value for reuse through example matching calculation;
and (3) performing analog analysis on similar examples, diagnosing the type of the fault which possibly occurs, and proposing a current fault handling method proposal according to the fault handling method in the examples to provide a basis for teleoperation control.
4. The method of claim 3, wherein after obtaining the solution, switching from the monitoring mode to the fault teleoperation mode, and processing the fault through the teleoperation controller comprises:
switching modes, namely switching from a normal automatic operation mode to a teleoperation safety processing mode;
determining the fault type and proposing a safety processing mode suggestion based on a fault mode and processing method knowledge base, and guiding teleoperation personnel to carry out remote safety processing;
and the teleoperation personnel operates the teleoperation controller to process the safety problem, the teleoperation controller generates a teleoperation signal, the teleoperation signal is transmitted to a PLC (programmable logic controller) of the paint spraying equipment through conversion, the field equipment is controlled to execute a teleoperation processing action, and after the safety processing is finished, the teleoperation processing process of the safety problem is ended.
5. A digital twin-based automated spray monitoring teleoperation system, the system comprising:
the monitoring module is used for monitoring an automatic paint spraying site in real time through a sensing network and establishing a site real-time enhancement model;
the monitoring module includes:
the determining unit is used for determining the composition and the layout of the automatic spraying teleoperation assembly control device;
the model establishing unit is used for realizing the establishment of the augmented reality modeling of the automatic spraying field through multi-source data processing, multi-source information registration and virtual-real information fusion in sequence;
the establishment of the automatic spraying field augmented reality modeling is realized through multi-source data processing, multi-source information registration and virtual-real information fusion in sequence, and the establishment comprises the following steps:
under the support of a workshop characteristic data model and an information expression template, rapidly extracting, identifying and optimizing characteristic data and key information of multi-source data acquired on site, and further realizing uniform expression of heterogeneous information;
registering multi-source information based on a least square rule and a maximum likelihood registration algorithm;
carrying out dynamic real-time calibration on the field real-time information and the 3D virtual model, and carrying out interaction on multi-source information on the model to obtain an automatic spraying field virtual-real fusion enhanced model;
the fault diagnosis and judgment module is used for diagnosing the fault according to the knowledge base if the abnormity of the automatic paint spraying process is monitored, determining the type and the occurrence reason of the fault and obtaining a solution;
and the processing module is used for switching the monitoring mode into a fault teleoperation mode after the solution is obtained, and processing the fault through the teleoperation controller.
6. The system of claim 5, wherein the fault diagnosis decision module comprises:
the first acquisition unit is used for loading the fault phenomenon, determining a search strategy and searching the instance library by using the search strategy to obtain a similar fault instance set;
the second acquisition unit is used for acquiring the instances meeting the similarity threshold value for reuse through instance matching calculation;
and the diagnosis and judgment unit is used for diagnosing the type of the fault which possibly occurs by carrying out analog analysis on the similar examples, and providing a current fault processing method suggestion according to the fault processing method in the examples so as to provide a basis for teleoperation control.
7. The system of claim 6, wherein the processing module comprises:
the mode switching unit is used for switching the mode from a normal automatic operation mode to a remote operation safety processing mode;
the remote control unit is used for determining the fault type and proposing a safety processing mode suggestion based on the fault mode and the processing method knowledge base and guiding teleoperation personnel to carry out remote safety processing;
and the processing unit is used for the teleoperation personnel to operate the teleoperation controller to process the safety problem, the teleoperation controller generates a teleoperation signal, the teleoperation signal is transmitted to the PLC of the paint spraying equipment through conversion, the field equipment is controlled to execute a teleoperation processing behavior, and after the safety processing is finished, the teleoperation processing process of the safety problem is ended.
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| CN113657524A (en) * | 2021-08-23 | 2021-11-16 | 北京奔驰汽车有限公司 | Method and device for detecting quality of full process flow of coating workshop |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106003076A (en) * | 2016-06-22 | 2016-10-12 | 潘小胜 | Powder spraying robot based on stereoscopic vision |
| KR20170106536A (en) * | 2016-03-10 | 2017-09-21 | 두림야스카와(주) | Method for Managing Data of Painting Robot System |
| CN110815224A (en) * | 2019-11-14 | 2020-02-21 | 华南智能机器人创新研究院 | Remote fault diagnosis pushing method and device for robot |
| CN111199573A (en) * | 2019-12-30 | 2020-05-26 | 成都索贝数码科技股份有限公司 | Virtual-real mutual reflection method, device, medium and equipment based on augmented reality |
| CN111596604A (en) * | 2020-06-12 | 2020-08-28 | 中国科学院重庆绿色智能技术研究院 | Intelligent fault diagnosis and self-healing control system and method for engineering equipment based on digital twinning |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11385613B2 (en) * | 2017-05-03 | 2022-07-12 | Siemens Aktiengesellschaft | Process image within controllers enabling visibility and accessibility of real world objects |
| CN111167668A (en) * | 2020-03-06 | 2020-05-19 | 广东工业大学 | Dispensing process optimization method for mobile phone manufacturing |
-
2020
- 2020-11-06 CN CN202011228212.7A patent/CN112547352B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20170106536A (en) * | 2016-03-10 | 2017-09-21 | 두림야스카와(주) | Method for Managing Data of Painting Robot System |
| CN106003076A (en) * | 2016-06-22 | 2016-10-12 | 潘小胜 | Powder spraying robot based on stereoscopic vision |
| CN110815224A (en) * | 2019-11-14 | 2020-02-21 | 华南智能机器人创新研究院 | Remote fault diagnosis pushing method and device for robot |
| CN111199573A (en) * | 2019-12-30 | 2020-05-26 | 成都索贝数码科技股份有限公司 | Virtual-real mutual reflection method, device, medium and equipment based on augmented reality |
| CN111596604A (en) * | 2020-06-12 | 2020-08-28 | 中国科学院重庆绿色智能技术研究院 | Intelligent fault diagnosis and self-healing control system and method for engineering equipment based on digital twinning |
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