CN115129430B - Robot remote control instruction issuing method and system based on 5g network - Google Patents
Robot remote control instruction issuing method and system based on 5g network Download PDFInfo
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Abstract
The invention provides a robot remote control instruction issuing method and system based on a 5g network, relating to the technical field of robot remote control, wherein the method comprises the following steps: modifying variables of the running program based on the 5g network platform; acquiring an operation parameter set; acquiring an operation state set; building a robot digital twin platform; acquiring an operation parameter random adjustment set and an operation state random adjustment set; acquiring a panel display information set; generating a remote diagnosis report of the robot; and obtaining a remote diagnosis result. The technical problem that equipment maintenance cannot be timely carried out on the robot due to the fact that the robot remote control instruction is not timely sent is solved, the technical effects that on the basis of a 5g network platform, the robot remote control instruction is timely sent, operation is assisted through a cloud processor, operation efficiency is improved, fault nodes are quickly located, a professional engineer is assisted in troubleshooting, fault processing time is shortened, and equipment maintenance is timely carried out on the robot are achieved.
Description
Technical Field
The invention relates to the technical field of robot remote control, in particular to a robot remote control instruction issuing method and system based on a 5g network.
Background
The robot is an anthropomorphic electromechanical device, has the capability of quickly reacting, analyzing and judging the environment state, has the capability of continuously working for a long time, has high accuracy and resists severe environment, is important production and service equipment in industry and non-industry, and is also indispensable automation equipment in the technical field of advanced manufacturing.
However, the remote control instruction of the robot is not sent timely, the control delay of the robot is easily caused, the cognition of the field management personnel of the robot on the state parameters of the robot is limited, and the potential problems of the robot existing in the real-time operation and maintenance system of the robot cannot be effectively monitored and early warned.
The technical problem that equipment maintenance cannot be timely performed on the robot due to the fact that the robot remote control instruction is not timely sent exists in the prior art.
Disclosure of Invention
The application provides a robot remote control instruction issuing method and system based on a 5g network, the technical problem that equipment maintenance cannot be performed on a robot in time due to the fact that the robot remote control instruction is not sent timely is solved, the technical problem that the robot remote control instruction cannot be timely sent on the basis of the 5g network platform is solved, the robot remote control instruction is timely sent, operation is assisted through a cloud processor, operation efficiency is improved, fault nodes are quickly located, a professional engineer is assisted in troubleshooting, fault processing time is shortened, and the technical effect of performing equipment maintenance on the robot in time is achieved.
In view of the above problems, the present application provides a robot remote control instruction issuing method and system based on a 5g network.
In a first aspect of the present application, a robot remote control instruction issuing method based on a 5g network is provided, where the method includes: modifying the variables of the running program of the robot based on a 5g network platform by combining a remote diagnosis calling instruction; synchronously acquiring the operation parameters of the robot to obtain an operation parameter set; monitoring the running state of the robot in real time by using a monitoring camera to obtain a running state set; importing the operation parameter set and the operation state set into simulation software, performing index reduction setting, and building a robot digital twin platform; randomly changing the number of variables of the robot, and acquiring an operation parameter random adjustment set and an operation state random adjustment set through the remote diagnosis call instruction; synchronously recording panel display information of the robot, and acquiring a panel display information set; integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set to generate a remote diagnosis report of the robot; and sending the remote diagnosis report to an equipment end based on the robot digital twin platform to obtain a remote diagnosis result.
In a second aspect of the present application, a system for issuing a remote control command of a robot based on a 5g network is provided, where the system includes: the variable modification unit is used for modifying the variable of the running program of the robot based on a 5g network platform by combining a remote diagnosis call instruction; the robot control system comprises a parameter acquisition unit, a parameter processing unit and a control unit, wherein the parameter acquisition unit is used for synchronously acquiring the operation parameters of the robot and acquiring an operation parameter set; the system comprises an operation state acquisition unit, a monitoring camera and a control unit, wherein the operation state acquisition unit is used for monitoring the operation state of the robot in real time by using the monitoring camera to acquire an operation state set; the digital platform building unit is used for importing the operation parameter set and the operation state set into simulation software, performing index reduction setting and building a robot digital twin platform; the random adjusting unit is used for randomly changing the number of variables of the robot and acquiring a running parameter random adjusting set and a running state random adjusting set through the remote diagnosis calling instruction; the synchronous recording unit is used for synchronously recording panel display information of the robot and acquiring a panel display information set; the diagnosis report generating unit is used for integrating the running parameter random adjusting set, the running state random adjusting set and a panel display information set to generate a remote diagnosis report of the robot; and the diagnosis result acquisition unit is used for sending the remote diagnosis report to an equipment end based on the digital twin platform of the robot to acquire a remote diagnosis result.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
because a 5 g-based network platform is adopted, and a remote diagnosis call instruction is combined, the variable of the running program of the robot is modified; synchronously acquiring the running parameters of the robot and acquiring a running parameter set; monitoring the running state of the robot in real time by using a monitoring camera to obtain a running state set; constructing a robot digital twin platform; acquiring an operation parameter random adjustment set and an operation state random adjustment set; synchronously recording panel display information of the robot, and acquiring a panel display information set; integrating the running parameter random adjustment set, the running state random adjustment set and the panel display information set to generate a remote diagnosis report of the robot; and sending the remote diagnosis report to the equipment side based on the robot digital twin platform to obtain a remote diagnosis result. This application has reached and has used 5g network platform as the basis, in time sends the robot remote control instruction, through the supplementary operation of cloud treater, improves the operating efficiency, fixes a position trouble node fast, and supplementary professional engineer carries out troubleshooting, reduces the fault handling time, in time carries out the technological effect of equipment maintenance to the robot.
Drawings
Fig. 1 is a schematic flow chart of a robot remote control instruction issuing method based on a 5g network according to the present application;
fig. 2 is a schematic flow chart of a robot remote control instruction issuing method based on a 5g network for generating a remote diagnosis report of a robot according to the present application;
fig. 3 is a schematic flow chart illustrating dynamic output of a remote diagnosis report according to a method for issuing a remote control command of a robot based on a 5g network according to the present application;
fig. 4 is a schematic structural diagram of a robot remote control instruction issuing system based on a 5g network according to the present application.
Description of the reference numerals: the system comprises a variable modification unit 11, a parameter acquisition unit 12, an operation state acquisition unit 13, a digital platform construction unit 14, a random adjustment unit 15, a synchronous recording unit 16, a diagnosis report generation unit 17 and a diagnosis result acquisition unit 18.
Detailed Description
The application provides a robot remote control instruction issuing method and system based on a 5g network, the technical problem that the robot remote control instruction cannot be timely sent to cause the problem that equipment maintenance cannot be timely carried out on the robot is solved, the purpose that the robot remote control instruction is timely sent based on the 5g network platform is achieved, operation is assisted through a cloud processor, operation efficiency is improved, fault nodes are quickly located, a professional engineer is assisted in troubleshooting, fault processing time is shortened, and the technical effect of equipment maintenance is timely carried out on the robot. This application can be applicable to industrial robot, cooperation robot, AGV transfer robot etc. like four-axis robot or six robots.
Example one
As shown in fig. 1, the present application provides a robot remote control instruction issuing method based on a 5g network, wherein the method includes:
step S100: based on a 5g network platform, modifying the variables of the running program of the robot by combining a remote diagnosis call instruction;
step S200: synchronously acquiring the running parameters of the robot and acquiring a running parameter set;
step S300: monitoring the running state of the robot in real time by using a monitoring camera to obtain a running state set;
specifically, the embodiment of the application issues a remote control instruction from the perspective of robot detection and maintenance, synchronously detects the fault of the robot, and improves the timeliness of operation, maintenance and synchronous monitoring through high-speed 5g network connection.
Specifically, the field manager of the robot has limited cognition on the state parameters of the robot, cannot effectively monitor and early warn potential problems of the robot, and monitors various current and historical states of the robot in real time on the basis of a 5g network platform.
Further specifically, the remote diagnosis call instruction is a diagnosis start signal sent by a professional engineer at a remote debugging end, the remote diagnosis call instruction is synchronously sent to a machine end through a 5g network platform, a variable of an operation program of the robot is modified, the variable can be related index parameters such as working speed, operation acceleration, working load and repetition precision, the variable is modified through the remote diagnosis call instruction, operation parameter collection of the robot is synchronously performed, and an operation parameter set is obtained; the monitoring camera is a multi-channel high-definition video remote real-time monitoring device, and is used for monitoring the running state of the robot in real time, acquiring a running state set and providing a data basis for subsequent data processing.
Further specifically, once a factory robot fails, field debugging is required, and the robots are generally high in failure rate in various sizes, so that the debugging cost is high, the workload of professional operation and maintenance personnel is complicated, the working efficiency is low, a monitoring device (namely a monitoring camera) is additionally arranged on the field to monitor the running conditions of the robots and equipment, and data support is provided for assisting professional engineers at a remote debugging end to control field personnel to complete debugging.
Step S400: importing the operation parameter set and the operation state set into simulation software, performing index reduction setting, and building a robot digital twin platform;
specifically, based on a web streaming media based on ffmpeg (video editing and converting software) + jsmpeg (video and audio decoder) + node.js (scripting language of server language), based on the running state set, ffmpeg converts an RTSP stream (file format) of a monitoring camera into an MPEG stream (file format), changes video coding from h.264 (video compression coding standard) to MPEG-1video (MPEG-1 is the first video and audio lossy compression standard established by MPEG organization), stably pushes the video stream to a cloud processor at high speed, receives the video stream pushed by ffmpeg under the node.js running environment, provides a WebSocket port to the outside, imports the running parameter set, realizes multi-channel video high-efficiency transmission based on the WebSocket protocol, ensures low delay and continuity of the video, and sets up a basic digital machine restoration framework by taking a Vue framework (progressive framework) as a client side and taking a node.js environment as a cloud processor base, and sets up an initialization index.
Further specifically, the key technology of multipath real-time video transmission uses a web streaming media scheme based on ffmpeg + jsmpeg + nodejs and a WebSocket protocol, wherein ffmpeg provides a leading audio and video coding capability, jsmpeg and WebSocket ensure low delay and continuity of video streams, and in addition, the WebSocket protocol can reduce communication traffic, so long as WebSocket connection is established, the connection is kept all the time, and messages can be continuously transmitted.
Step S500: randomly changing the number of variables of the robot, and acquiring a running parameter random adjustment set and a running state random adjustment set through the remote diagnosis call instruction;
further, the number of variables of the robot is randomly changed, and the running parameter random adjustment set and the running state random adjustment set are obtained through the remote diagnosis call instruction, wherein the step S500 includes:
step S510: positioning variables of an operation program of the marking robot, and generating variable marking information;
step S520: generating random numbers through a random algorithm, wherein the number of the random numbers is consistent with the number of the running program variables;
step S530: and modifying the variable mark information through a random number change rule and the random number, synchronously acquiring information, and acquiring an operation parameter random adjustment set and an operation state random adjustment set.
Specifically, the method includes the steps of positioning variables of an operation program of a marking robot through variable marking signals, obtaining variable marking information after positioning is completed, wherein the variable marking information is variable information after marking positioning is completed, generating a group of random numbers through a random algorithm, the number of the random numbers is consistent with the number of the operation program variables, determining a random number change rule to be that the operation program variables corresponding to the random numbers of which the random numbers are integral multiples of 3 need to be modified, the random number change rule is a preset index parameter, exemplarily, the random numbers are [10, 15, 13, 6, 8], correspondingly, a second operation program variable and a fourth operation program variable need to be modified, the modification direction of the operation program variables is not unique, full-stage modification can be carried out, information acquisition is carried out synchronously, an operation parameter random adjustment set and an operation state random adjustment set are obtained, the operation parameter random adjustment set and the operation state random adjustment set synchronously acquire the operation parameters of the robot, and the operation parameter random adjustment set synchronously acquires the full-stage modified operation parameters of the robot, and the operation state random adjustment set, namely the monitoring camera is used for real-time monitoring and the full-stage modification support evaluation of the robot.
Step S600: synchronously recording panel display information of the robot, and acquiring a panel display information set;
step S700: integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set to generate a remote diagnosis report of the robot;
step S800: and sending the remote diagnosis report to an equipment side based on the robot digital twin platform to obtain a remote diagnosis result.
Further, the method further comprises:
step S910: judging whether the robot has a fault or not according to the remote diagnosis result;
step S920: if the fault occurs, the fault is positioned and marked through an abnormal alarm module, and a fault abnormal marking result is obtained;
step S930: and outputting the fault abnormity marking result to a remote debugging end through a cloud processor, and assisting a professional engineer of the remote debugging end to debug.
Specifically, the panel display information includes, but is not limited to, relevant parameter indexes such as motion mode, absolute accuracy, working coordinates, tool coordinates, and payload, and is specifically determined by specifically combining module function information of a robot production process, and the panel display information of the robot is synchronously recorded in the process of acquiring an operation parameter random adjustment set and an operation state random adjustment set, so as to generate a panel display information set, wherein the panel display information set, the operation parameter random adjustment set and the operation state random adjustment set are synchronous related information, and the operation parameter random adjustment set, the operation state random adjustment set and the panel display information set are integrated to generate a remote diagnosis report of the robot.
Specifically, based on the remote connection between a cloud processor and a remote debugging end, the remote diagnosis result is transmitted to the remote debugging end, and operation simulation is performed at the remote debugging end through the robot digital twin platform and the implanted remote diagnosis report to judge whether the robot breaks down; if the fault occurs, the fault is positioned and marked through the abnormal alarm module, a fault abnormal marking result is obtained, the fault abnormal marking result can be used for prominently marking the position coordinate of the fault and outputting the fault abnormal marking result to the remote debugging end, and a professional engineer at the auxiliary remote debugging end conducts debugging, so that the fault solving speed is increased while the operation cost of an enterprise is saved, the fault is quickly positioned, the professional engineer at the auxiliary remote debugging end conducts debugging, fault removal is conducted, the fault processing time is shortened, and the fault one-time restoration rate is increased.
Further, the operation parameter random adjustment set, the operation state random adjustment set and the panel display information set are integrated to generate a remote diagnosis report of the robot, and the step S700 includes:
step S710: acquiring data backup filing information;
step S720: through the data backup filing information, filing and sorting the programs corresponding to the operation parameter random adjustment set to obtain an operation program backup data packet;
step S730: and importing the running program backup data packet into a cloud processor, and integrating the running parameter random adjustment set, the running state random adjustment set and the panel display information set to generate a remote diagnosis report of the robot.
Specifically, in the adjustment process, in order to avoid covering of original data, timely data backup filing processing is required, the data backup filing information comprises other related index information such as an operating program of the robot, a data backup signal is obtained before data adjustment, data backup filing information is extracted through the data backup signal, data random adjustment is performed after data backup is completed, a data filing signal is obtained after data adjustment is completed, in combination with the data backup filing information, a program corresponding to the operating parameter random adjustment set is filed and sorted, an operating program backup data package is obtained, the operating program backup data package comprises the operating program of the robot before data adjustment and the program corresponding to the operating parameter random adjustment set, after filing and sorting is completed, the operating parameter random adjustment set, the operating state random adjustment set and a panel display information set are integrated through remote connection of the equipment end and the cloud processor, the operating parameter random adjustment set, the operating state random adjustment set and the panel display information set are integrated, and a diagnostic support report for ensuring the integrity of a diagnostic result of a diagnostic report for the remote diagnosis support of the operating parameter random adjustment set, the operating parameter random adjustment set, the operating state adjustment set and the panel display information is provided, and a diagnostic support report for the remote diagnosis support of the diagnostic report is provided.
Further, as shown in fig. 2, the running program backup data package is imported into a cloud processor, the running parameter random adjustment set, the running state random adjustment set and the panel display information set are integrated, and a remote diagnosis report of the robot is generated, where step S730 includes:
step S731: after the running program backup data packet is imported into a cloud processor, a Node signal is obtained through the robot digital twin platform in a Node.
Step S732: integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set through a non-blocking I/O interface based on the Node signal to generate a digital twin model;
step S733: receiving, by the cloud processor, an operating state request of a client;
step S734: and generating a remote diagnosis report of the robot through the running state request and the digital twin model.
Further, as shown in fig. 3, the method further includes:
step S734-1: based on node.js environment, node.js is used as http server to provide a web access interface, and a running state request of a client is received through a cloud processor;
step S734-2: and pushing the remote diagnosis report to a client, and dynamically outputting the remote diagnosis report by the client based on an Echarts library.
Specifically, the Node signals are used for monitoring the operation of each part of the monitoring camera, the equipment end, the cloud server and the robot, and support is provided for realizing the cooperation and coordination of the communication of the electrical information of each part.
Further specifically, in a node.js environment, after data integration and transmission are completed, a Node is notified, a Node signal is acquired through the digital twin platform of the robot, and the running parameter random adjustment set, the running state random adjustment set and the panel display information set are accessed and called through a non-blocking I/O interface, so that data iteration training is performed, and a digital twin model is generated; in the embodiment of the application, the remote connection can perform data communication transmission through a 5g network, receive an operation state request of a client based on the remote connection between the cloud processor and the client, and receive the operation state request to the cloud processor; and comparing the digital twin model output with the running state request to obtain a remote diagnosis report of the robot. Through Node signals, the access flow to resources is simplified, the development complexity is reduced, and the coordination working performance of each component is effectively improved.
Further specifically, in order to realize visual dynamic management of data, dynamic data in the adjustment process is pushed to a service end which operates based on a node.js environment, the node.js serves as an http server to provide a web access interface, and the service end receives a data request of a client and then receives an operation state request of the client through a cloud processor; and performing correlation mapping output on the dynamic data and the running state request to obtain a correlation mapping output result, pushing the correlation mapping output result and the remote diagnosis report to a client, and dynamically outputting the remote diagnosis report by the client based on an Echarts library to realize visual dynamic management of the dynamic data.
Further, based on the Node signal, the operation parameter random adjustment set, the operation state random adjustment set, and the panel display information set are integrated through a non-blocking I/O interface to generate a digital twin model, and step S732 includes:
step S732-1: based on the RBF network as a model, inputting the operation parameter random adjustment set and the operation state random adjustment set to the input end of the RBF network, and performing supervised training by taking a panel display information set as supervision data;
step S732-2: setting a node center and a node base width parameter of the RBF network;
step S732-3: inputting the running parameter random adjustment set, the running state random adjustment set and the panel display information set through an identification network at the front end of the RBF network;
step S732-4: and performing data iterative operation based on the node center and the node base width parameters, and generating a digital twin model after an error threshold value meets a preset error threshold value.
Specifically, iterative operation is carried out through a network model to ensure the precision of the digital twin model, an RBF network is taken as a model base, the operation parameter random adjustment set, the operation state random adjustment set and the panel display information set are grouped, the panel display information set, the operation parameter random adjustment set and the operation state random adjustment set are synchronous associated information, data grouping is carried out, each group of data comprises operation parameter random adjustment data, operation state random adjustment data and panel display information which are limited by the synchronous associated information, multiple groups of sequential operation parameter random adjustment data and operation state random adjustment data are input to the input end of the RBF network, and panel display information limited by the synchronous associated information is taken as supervision data to carry out supervision training; setting a node center and a node base width parameter of the RBF network through the output of an identification algorithm, wherein the node center and the node base width parameter both belong to parameter indexes in a Gaussian basis function of the RBF network; and based on the node center and the node base width parameters, inputting the operation parameter random adjustment set, the operation state random adjustment set and the panel display information set, performing data iterative operation, determining a digital twin model after the error threshold of the model output and the supervision data meets a preset error threshold, providing a model foundation for subsequent data processing, and providing data support for assisting a professional engineer at a remote debugging end to determine a modulation scheme by performing comparison analysis on the operation state request and the output of the digital twin model.
In summary, the method and system for issuing the robot remote control instruction based on the 5g network provided by the present application have the following technical effects:
because a 5 g-based network platform is adopted, and a remote diagnosis call instruction is combined, the variable of the running program of the robot is modified; synchronously acquiring the operation parameters of the robot to obtain an operation parameter set; monitoring the running state of the robot in real time by using a monitoring camera to obtain a running state set; building a robot digital twin platform; acquiring a running parameter random adjustment set and a running state random adjustment set; synchronously recording panel display information of the robot, and acquiring a panel display information set; integrating the running parameter random adjustment set, the running state random adjustment set and the panel display information set to generate a remote diagnosis report of the robot; and sending the remote diagnosis report to the equipment side based on the robot digital twin platform to obtain a remote diagnosis result. The application provides a robot remote control instruction issuing method and system based on a 5g network, and achieves the technical effects that the robot remote control instruction is sent in time on the basis of a 5g network platform, the operation is assisted through a cloud processor, the operation efficiency is improved, fault nodes are quickly positioned, a professional engineer is assisted in troubleshooting, the fault processing time is shortened, and equipment maintenance is performed on the robot in time.
The remote diagnosis result is adopted to judge whether the robot has a fault; if the fault occurs, the fault is positioned and marked through an abnormal alarm module, and a fault abnormal marking result is obtained; through the cloud treater, export the unusual mark result of trouble to the remote debugging end, the professional engineer of supplementary remote debugging end debugs, improves the trouble solution speed when saving the operation cost of enterprise, carries out the quick location of trouble, and the professional engineer of supplementary remote debugging end debugs, carries out troubleshooting, reduces the fault handling time, improves the disposable repair rate of trouble.
After the operating program backup data packet is led into the cloud processor, in a node.js environment, a Node signal is obtained through a digital twin platform of a robot, and an operating parameter random adjustment set, an operating state random adjustment set and a panel display information set are integrated through a non-blocking I/O interface to generate a digital twin model; receiving an operation state request of a client through a cloud processor; and generating a remote diagnosis report of the robot by the running state request and the digital twin model. Through Node signals, the access flow to resources is simplified, the development complexity is reduced, and the coordination working performance of each component is effectively improved.
Example two
Based on the same inventive concept as the method for issuing the remote control command of the robot based on the 5g network in the foregoing embodiment, as shown in fig. 4, the present application provides a system for issuing the remote control command of the robot based on the 5g network, wherein the system includes:
the variable modification unit 11 is used for modifying the variable of the running program of the robot based on a 5g network platform by combining a remote diagnosis call instruction;
the parameter acquiring unit 12 is used for acquiring the operation parameters of the robot synchronously and acquiring an operation parameter set;
an operation state acquiring unit 13, where the operation state acquiring unit 13 is configured to use a monitoring camera to monitor an operation state of the robot in real time, and acquire an operation state set;
the digital platform building unit 14 is used for importing the operation parameter set and the operation state set into simulation software, performing index reduction setting and building a robot digital twin platform;
a random adjusting unit 15, wherein the random adjusting unit 15 is used for randomly changing the number of variables of the robot and acquiring a running parameter random adjusting set and a running state random adjusting set through the remote diagnosis calling instruction;
the synchronous recording unit 16 is used for synchronously recording panel display information of the robot and acquiring a panel display information set;
a diagnostic report generating unit 17, wherein the diagnostic report generating unit 17 is configured to integrate the operation parameter random adjustment set, the operation state random adjustment set, and the panel display information set to generate a remote diagnostic report of the robot;
and the diagnosis result acquisition unit 18 is used for sending the remote diagnosis report to an equipment side based on the digital twin platform of the robot to acquire a remote diagnosis result.
Further, the system comprises:
a variable mark generation unit for positioning a variable of an operating program of a marking robot and generating variable mark information;
the random number generating unit is used for generating random numbers through a random algorithm, wherein the number of the random numbers is consistent with the number of the running program variables;
and the information acquisition unit is used for modifying the variable mark information through a random number change rule and the random number, synchronously acquiring information and acquiring an operation parameter random adjustment set and an operation state random adjustment set.
Further, the system comprises:
the backup archiving unit is used for acquiring data backup archiving information;
the filing and sorting unit is used for filing and sorting the programs corresponding to the operation parameter random adjustment set through the data backup filing information to obtain an operation program backup data packet;
and the diagnosis report generation unit is used for importing the running program backup data packet into a cloud processor, integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set, and generating a remote diagnosis report of the robot.
Further, the system comprises:
a signal acquisition unit, configured to acquire a Node signal in a node.js environment through the robot digital twin platform after the operating program backup data packet is imported to a cloud processor;
the twin model generation unit is used for integrating the running parameter random adjustment set, the running state random adjustment set and the panel display information set through a non-blocking I/O interface based on the Node signal to generate a digital twin model;
a request receiving unit, configured to receive, by the cloud processor, an operation state request of a client;
a diagnostic report generation unit for generating a remote diagnostic report of the robot by the operation state request and the digital twin model.
Further, the system comprises:
the monitoring training unit is used for inputting the running parameter random adjustment set and the running state random adjustment set to the input end of the RBF network on the basis of taking the RBF network as a model, and performing monitoring training by taking the panel display information set as monitoring data;
the parameter setting unit is used for setting the node center and the node base width parameter of the RBF network;
the data input unit is used for inputting the running parameter random adjustment set, the running state random adjustment set and the panel display information set through an identification network at the front end of the RBF network;
and the iterative operation unit is used for performing data iterative operation based on the node center and the node base width parameter, and generating a digital twin model after an error threshold value meets a preset error threshold value.
Further, the system comprises:
the access interface determining unit is used for providing a web access interface by taking node.js as an http server based on node.js environment, and receiving an operation state request of a client through a cloud processor;
and the dynamic output unit is used for pushing the remote diagnosis report to a client, and the client dynamically outputs the remote diagnosis report based on an Echarts library.
Further, the system comprises:
the fault judgment unit is used for judging whether the robot has a fault or not according to the remote diagnosis result;
the positioning and marking unit is used for positioning and marking the fault through the abnormal alarm module if the fault occurs, and acquiring a fault abnormal marking result;
the debugging unit of supplementary remote debugging end, the debugging unit of supplementary remote debugging end is used for through the cloud treater, will the unusual mark result of trouble exports to the remote debugging end, and the professional engineer of supplementary remote debugging end debugs.
The specification and drawings are merely exemplary of the application and various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Such modifications and variations of the present application are within the scope of the claims of the present application and their equivalents, and the present application is intended to include such modifications and variations.
Claims (5)
1. A robot remote control instruction issuing method based on a 5g network is characterized by comprising the following steps:
based on a 5g network platform, modifying the variables of the running program of the robot by combining a remote diagnosis call instruction;
synchronously acquiring the running parameters of the robot and acquiring a running parameter set;
monitoring the running state of the robot in real time by using a monitoring camera to obtain a running state set;
importing the operation parameter set and the operation state set into simulation software, performing index reduction setting, and building a robot digital twin platform;
randomly changing the number of variables of the robot, and acquiring a running parameter random adjustment set and a running state random adjustment set through the remote diagnosis call instruction;
synchronously recording panel display information of the robot, and acquiring a panel display information set;
integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set to generate a remote diagnosis report of the robot;
sending the remote diagnosis report to an equipment side based on the robot digital twin platform to obtain a remote diagnosis result;
the method comprises the following steps of integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set to generate a remote diagnosis report of the robot, wherein the method comprises the following steps:
acquiring data backup filing information;
through the data backup filing information, filing and sorting the programs corresponding to the operation parameter random adjustment set to obtain an operation program backup data packet;
importing the running program backup data packet into a cloud processor, integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set, and generating a remote diagnosis report of the robot;
the method comprises the following steps of importing the running program backup data packet into a cloud processor, integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set, and generating a remote diagnosis report of the robot, wherein the method comprises the following steps:
after the running program backup data packet is imported into a cloud processor, a Node signal is obtained through the robot digital twin platform in a Node.
Integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set through a non-blocking I/O interface based on the Node signal to generate a digital twin model;
receiving, by the cloud processor, an operating state request of a client;
generating a remote diagnosis report of the robot through the running state request and the digital twin model;
the method comprises the following steps of integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set through a non-blocking I/O interface based on the Node signals to generate a digital twin model, wherein the method comprises the following steps:
based on the RBF network as a model, inputting the running parameter random adjustment set and the running state random adjustment set to the input end of the RBF network, and performing supervised training by taking a panel display information set as supervision data;
setting a node center and a node base width parameter of the RBF network;
inputting the running parameter random adjustment set, the running state random adjustment set and the panel display information set through an identification network at the front end of the RBF network;
and performing data iterative operation based on the node center and the node base width parameters, and generating a digital twin model after an error threshold value meets a preset error threshold value.
2. The method of claim 1, wherein the number of variables of the robot is randomly changed, and the random adjustment set of operating parameters and the random adjustment set of operating states are obtained through the remote diagnosis call instruction, the method comprising:
positioning variables of an operating program of the marking robot to generate variable marking information;
generating random numbers through a random algorithm, wherein the number of the random numbers is consistent with the number of the running program variables;
and modifying the variable mark information through a random number change rule and the random number, synchronously acquiring information, and acquiring an operation parameter random adjustment set and an operation state random adjustment set.
3. The method of claim 1, wherein the method further comprises:
based on node.js environment, node.js is used as http server to provide a web access interface, and a running state request of a client is received through a cloud processor;
and pushing the remote diagnosis report to a client, and dynamically outputting the remote diagnosis report by the client based on an Echarts library.
4. The method of claim 1, wherein the method further comprises:
judging whether the robot has a fault or not according to the remote diagnosis result;
if the fault occurs, the fault is positioned and marked through an abnormal alarm module, and a fault abnormal marking result is obtained;
and outputting the fault abnormity marking result to a remote debugging end through a cloud processor, and assisting a professional engineer of the remote debugging end to debug.
5. A robot remote control instruction issuing system based on a 5g network is characterized by comprising:
the variable modification unit is used for modifying the variable of the running program of the robot based on a 5g network platform by combining a remote diagnosis call instruction;
the robot control system comprises a parameter acquisition unit, a parameter processing unit and a control unit, wherein the parameter acquisition unit is used for synchronously acquiring the operation parameters of the robot and acquiring an operation parameter set;
the system comprises an operation state acquisition unit, a monitoring camera and a control unit, wherein the operation state acquisition unit is used for monitoring the operation state of the robot in real time by using the monitoring camera to acquire an operation state set;
the digital platform building unit is used for importing the operation parameter set and the operation state set into simulation software, carrying out index reduction setting and building a robot digital twin platform;
the random adjusting unit is used for randomly changing the number of variables of the robot and acquiring a running parameter random adjusting set and a running state random adjusting set through the remote diagnosis calling instruction;
the synchronous recording unit is used for synchronously recording panel display information of the robot and acquiring a panel display information set;
the diagnosis report generating unit is used for integrating the running parameter random adjusting set, the running state random adjusting set and a panel display information set to generate a remote diagnosis report of the robot;
the diagnosis result acquisition unit is used for sending the remote diagnosis report to an equipment end based on the robot digital twin platform to acquire a remote diagnosis result;
the backup archiving unit is used for acquiring data backup archiving information;
the filing and sorting unit is used for filing and sorting the programs corresponding to the operation parameter random adjustment set through the data backup filing information to obtain an operation program backup data packet;
the diagnostic report generating unit is used for importing the running program backup data packet into a cloud processor, integrating the running parameter random adjustment set, the running state random adjustment set and a panel display information set, and generating a remote diagnostic report of the robot;
a signal acquisition unit, configured to acquire a Node signal in a node.js environment through the robot digital twin platform after the operating program backup data packet is imported to a cloud processor;
the twin model generation unit is used for integrating the running parameter random adjustment set, the running state random adjustment set and the panel display information set through a non-blocking I/O interface based on the Node signal to generate a digital twin model;
a request receiving unit, configured to receive, by the cloud processor, an operation state request of a client;
a diagnostic report generation unit for generating a remote diagnostic report of the robot by the operation state request and the digital twin model;
the system comprises a supervision training unit, a monitoring training unit and a monitoring training unit, wherein the supervision training unit is used for inputting a running parameter random adjustment set and a running state random adjustment set to the input end of an RB F network on the basis of taking the RBF network as a model, and carrying out supervision training by taking a panel display information set as supervision data;
the parameter setting unit is used for setting the node center and the node base width parameter of the RBF network;
the data input unit is used for inputting the running parameter random adjustment set, the running state random adjustment set and the panel display information set through an identification network at the front end of the RBF network;
and the iterative operation unit is used for performing data iterative operation based on the node center and the node base width parameter, and generating a digital twin model after an error threshold value meets a preset error threshold value.
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| CN115396418B (en) * | 2022-10-26 | 2023-03-21 | 山东德晟机器人股份有限公司 | Method for realizing real-time acquisition and transmission of multi-channel video stream based on 5G network |
| CN116319260B (en) * | 2023-05-09 | 2023-08-18 | 新华三技术有限公司 | Network fault diagnosis method, device, equipment and storage medium |
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