CN116229792B - Virtual simulation training system based on industrial robot - Google Patents
Virtual simulation training system based on industrial robot Download PDFInfo
- Publication number
- CN116229792B CN116229792B CN202310262380.5A CN202310262380A CN116229792B CN 116229792 B CN116229792 B CN 116229792B CN 202310262380 A CN202310262380 A CN 202310262380A CN 116229792 B CN116229792 B CN 116229792B
- Authority
- CN
- China
- Prior art keywords
- simulation
- signal
- industrial robot
- layout
- demand
- 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.)
- Active
Links
- 238000012549 training Methods 0.000 title claims abstract description 15
- 238000004088 simulation Methods 0.000 claims abstract description 254
- 238000004519 manufacturing process Methods 0.000 claims abstract description 197
- 238000004458 analytical method Methods 0.000 claims abstract description 60
- 238000012545 processing Methods 0.000 claims description 17
- 238000007667 floating Methods 0.000 claims description 15
- 238000012544 monitoring process Methods 0.000 claims description 10
- 238000012795 verification Methods 0.000 claims description 8
- 101100311460 Schizosaccharomyces pombe (strain 972 / ATCC 24843) sum2 gene Proteins 0.000 claims description 7
- 238000010606 normalization Methods 0.000 claims description 5
- 238000004891 communication Methods 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 abstract description 5
- 230000008901 benefit Effects 0.000 abstract description 4
- 238000007405 data analysis Methods 0.000 abstract description 3
- 238000000034 method Methods 0.000 description 20
- 238000004364 calculation method Methods 0.000 description 8
- 230000000694 effects Effects 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 230000010354 integration Effects 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 101100518501 Mus musculus Spp1 gene Proteins 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000011017 operating method Methods 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/04—Manufacturing
-
- 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
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Health & Medical Sciences (AREA)
- Marketing (AREA)
- Geometry (AREA)
- Manufacturing & Machinery (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- General Engineering & Computer Science (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Educational Technology (AREA)
- Manipulator (AREA)
Abstract
The invention relates to the technical field of industrial robots, and aims to solve the problems that the existing mode of virtual simulation training of the industrial robots is more ideal, the accuracy and rationality of the layout of the industrial robots in a manufacturing factory can not be ensured, and the production benefits of the industrial robots to the manufacturing factory can not be ensured; according to the invention, a mode of combining data analysis and simulation technology is adopted to carry out high-degree simulation analysis on the working environment and the working requirement of the manufacturing factory, and a powerful support is provided for realizing reasonable simulation layout of the industrial robot of the manufacturing factory, so that the productivity of the manufacturing factory is improved.
Description
Technical Field
The invention relates to the technical field of industrial robots, in particular to a virtual simulation training system based on an industrial robot.
Background
Industrial robots play an extremely important role in modern manufacturing. Because the industrial robot has high working efficiency, can adapt to extreme environments, has programmable advantages, and can be applied to working environments with large repeated labor demands and dangers. With the continuous development of robot technology, the virtual simulation technology of robots is also paid attention to. Virtual simulation techniques refer to time-highly simulated simulation of the operating environment and operating procedures required for various skill training.
However, in the existing virtual simulation training method of the industrial robot, the industrial robot and the working environment thereof and even the production process are subjected to simple simulation, and then the motion mode of the industrial robot is displayed in an animation mode, so that the combination of the environment and the requirements of a manufacturing factory is difficult to achieve, and further the manufacturing factory has larger deviation in the actual industrial robot layout, so that the reasonable layout of the industrial robot cannot be effectively assisted by the manufacturing factory, and the production benefit of the industrial robot for the manufacturing factory cannot be ensured.
In order to solve the above-mentioned defect, a technical scheme is provided.
Disclosure of Invention
The invention aims to solve the problems that the existing method for virtual simulation training of the industrial robot is more ideal, the accuracy and rationality of the layout of the industrial robot of a manufacturing factory cannot be ensured, and the production benefit of the industrial robot to the manufacturing factory cannot be ensured.
The aim of the invention can be achieved by the following technical scheme:
the virtual simulation training system based on the industrial robot comprises a server, wherein the server is in communication connection with a data acquisition unit, a simulation demand qualitative unit, a simulation environment qualitative unit, a simulation layout planning unit, a layout feasibility analysis unit, a re-simulation layout planning unit and a display terminal;
the data acquisition unit is used for acquiring simulation demand parameter information, simulation working environment information and simulation operation data parameters of a manufacturing factory to be applied by the industrial robot and respectively transmitting the simulation demand parameter information, the simulation working environment information and the simulation operation data parameters to the simulation demand qualitative unit, the simulation environment qualitative unit and the layout feasibility analysis unit;
the simulation demand qualitative unit is used for receiving simulation demand parameter information of a manufacturing factory to be applied by the industrial robot, judging, analyzing and processing the simulation demand of the industrial robot, obtaining a high demand signal, a medium demand signal and a low demand signal according to the simulation demand parameter information, and sending the high demand signal, the medium demand signal and the low demand signal to the simulation layout planning unit;
the simulation environment qualitative unit is used for receiving the simulation working environment information of the manufacturing factory, judging, analyzing and processing the simulation environment of the manufacturing factory, generating a high-environment signal and a general environment signal according to the simulation working environment information, and sending the high-environment signal and the general environment signal to the simulation layout planning unit;
the simulation layout planning unit performs layout comprehensive simulation planning analysis processing according to the received demand type judging signals and environment type judging signals, so as to obtain a simulation planning layout scheme of the industrial robot, and sends the simulation planning layout scheme to the layout feasibility analysis unit, wherein the simulation planning layout scheme of the industrial robot comprises the steps of distributing k1 or k2 or k3 or k4 industrial robot stations to a manufacturing factory;
the layout feasibility analysis unit is used for receiving a simulation planning layout scheme of the industrial robot, calling simulation operation data parameters of the industrial robot according to the simulation planning layout scheme, performing virtual layout feasibility verification analysis of the industrial robot, generating a manufacturing plant industrial robot simulation layout standard reaching signal and a manufacturing plant industrial robot simulation layout non-standard reaching signal according to the simulation operation data parameters, and sending the manufacturing plant industrial robot simulation layout non-standard reaching signal to the re-simulation layout planning unit;
the re-simulation layout planning unit monitors a first simulation area value and a second simulation area value in a simulation environment where the industrial robot is located according to the received manufacturing plant industrial robot simulation layout substandard signal, performs re-simulation layout operation, and repeats the layout feasibility analysis unit after the completion of the re-simulation layout operation until the manufacturing plant industrial robot simulation layout substandard signal is obtained, and sends the generated simulation layout plan layout scheme of the industrial robot to the display terminal for display description according to the generated manufacturing plant industrial robot simulation layout substandard signal.
Further, the specific operation steps of the simulation demand judging, analyzing and processing of the industrial robot are as follows:
real-time monitoring the production line number, the production point number and the artificial quantity value in the simulation demand parameter information of the manufacturing factory applied by the industrial robot, and calibrating the production line number, the production point number and the artificial quantity value as pl and pn respectively pl And qv, and performing normalized analysis on the same according to a set formulaWherein pl=1, 2,3 … … n, obtaining a demand coefficient req introduced by a manufacturing factory to the industrial robot, wherein δ1, δ2 and δ3 are weight factor coefficients of the production line number, the production point number and the artificial quantity value respectively;
the method comprises the steps of gradient setting 3 demand comparison intervals of a demand coefficient introduced by a manufacturing factory to an industrial robot, wherein the demand comparison intervals are a first gradient demand comparison interval grad1, a second gradient demand comparison interval grad2 and a third gradient demand comparison interval grad3 respectively, and grad3=mu+grad2=2mu+grad1;
when a demand coefficient introduced by a manufacturing factory to an industrial robot is within a preset first gradient demand comparison interval grad1, generating a low demand signal; when the demand coefficient introduced by the manufacturing factory to the industrial robot is within a preset second gradient demand comparison interval grad2, generating a medium demand signal; when the demand coefficient introduced by the manufacturing factory to the industrial robot is within a preset first gradient demand comparison interval grad3, a high demand signal is generated.
Further, the specific operation steps of the simulation environment judgment analysis processing of the manufacturing factory are as follows:
real-time monitoring an active area value, a line supply value and a line smoothness value in simulation working environment information of a manufacturing factory applied by an industrial robot, calibrating the active area value, the line supply value and the line smoothness value as hs, xg and xc respectively, carrying out normalization analysis, and obtaining an environment matching value bx according to a set formula bx=γ1xhs+γ2xg+γ3xc, wherein λ1, γ2 and γ3 are weight factor coefficients of the active area value, the line supply value and the line smoothness value respectively, and the components of γ1, γ2 and γ3 are natural numbers larger than 0;
setting a reference threshold value1 of the environment matching value, comparing and analyzing the environment matching value with a preset reference threshold value1, generating a high environment signal when the environment matching value is larger than or equal to the preset reference threshold value1, otherwise, generating a general environment signal when the environment matching value is smaller than the preset reference threshold value 1.
Further, the specific operation steps of the comprehensive layout simulation planning analysis processing are as follows:
when capturing a high-demand signal and a high-environment signal at the same time, generating a first-order matching signal, and distributing k1 industrial robot stations to a manufacturing factory according to the generated first-order matching signal;
when capturing a high-demand signal and a general environment signal or a medium-demand signal and a high-environment signal at the same time, generating a second-order matching signal, and distributing k2 industrial robot stations to a manufacturing factory according to the generated second-order matching signal;
when the medium demand signal and the general environment signal or the low demand signal and the high environment signal are captured at the same time, generating a third-order matching signal, and distributing k3 industrial robot stations to a manufacturing factory according to the generated third-order matching signal;
when the low-demand signal and the general environment signal are captured at the same time, a fourth-order matching signal is generated, and k4 industrial robot stations are distributed to a manufacturing factory according to the generated fourth-order matching signal.
Further, the specific operation steps of the industrial robot virtual layout feasibility verification analysis are as follows:
based on the simulation planning layout scheme of the industrial robots, the simulation intensity, the simulation fault value and the collision risk coefficient in the simulation operation data parameters of the industrial robots of each production line are obtained, and are respectively calibrated to be ms ij 、ful ij And chc ij And carrying out formulated analysis on the sample according to a set formulaObtaining the individual simulation running state value ISR of each industrial robot of each production line ij Wherein λ1, λ2 and λ3 are weight factor coefficients of the simulation intensity, the simulation failure value and the collision risk coefficient, respectively, and each of λ1, λ2 and λ3 is a natural number greater than 0;
summing and analyzing individual simulation running state values of all industrial robots of all production lines, and according to a set formulaObtaining the production line simulation running state value LSR of each production line i ；
Setting a reference threshold value2 of the production line simulation running state value, and comparing and analyzing the production line simulation running state value of each production line with the preset reference threshold value 2;
generating a line operation feedback unqualified signal when the line simulation operation state value is greater than or equal to a preset reference threshold value2, and generating a line operation feedback qualified signal when the line simulation operation state value is less than the preset reference threshold value 2;
counting the number of production lines marked as production line operation feedback qualified signals and production line operation feedback unqualified signals in an industrial manufacturing factory respectively, marking the production lines as sum1 and sum2 respectively, and generating a manufacturing factory industrial robot simulation layout unqualified signal if sum1 is less than or equal to sum 2;
otherwise, if sum1 is larger than sum2, generating a simulation layout standard signal of the industrial robot of the manufacturing plant, and generating the simulation layout standard signal of the industrial robot of the manufacturing plant.
Further, the specific operation steps of the re-simulation layout operation are as follows:
the method comprises the steps of monitoring a first simulation area value and a second simulation area value in a simulation environment where an industrial robot is located in real time, calibrating the first simulation area value and the second simulation area value into area1 and area2 respectively, performing differential analysis on the first simulation area value and the second simulation area value, and obtaining an area floating value sx according to a formula sx=area 1-area 2;
setting a reference threshold value3 of the regional floating value, comparing and analyzing the regional floating value with a preset reference threshold value3, and adding h1 stations of the industrial robot on the original simulation planning layout scheme of the industrial robot when the regional floating value is greater than or equal to the preset reference threshold value 3;
otherwise, when the regional floating value is smaller than a preset reference threshold value3, the stations of the h2 industrial robots are reduced on the simulation planning layout scheme of the industrial robots.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the judgment and analysis of the simulation demand state of the manufacturing factory are realized by means of normalization analysis, gradient interval setting and data comparison; the simulation environment state of the manufacturing factory is definitely judged and analyzed by means of symbolized calibration, formula calculation and threshold comparison;
the method realizes the definite setting of the number of stations of the industrial robot required by a manufacturing factory by utilizing the modes of data integration analysis and station quantitative setting, further confirms the simulation planning layout scheme of the industrial robot, and based on the scheme, realizes the verification of the layout feasibility of the virtual simulation industrial robot while confirming the reasonable state of the virtual simulation industrial robot layout of the manufacturing factory by utilizing the modes of data calculation, data statistical analysis and numerical comparison analysis;
the method adopts the re-simulation layout operation to realize reasonable virtual simulation training analysis of the stations of the industrial robots of the manufacturing factory, and lays a foundation for avoiding investment loss brought by layout errors to the manufacturing factory;
the method combines data analysis and simulation technology, performs high-degree simulation analysis on the working environment and the working requirement of the manufacturing factory, provides powerful support for realizing reasonable simulation layout of industrial robots of the manufacturing factory, and further improves the productivity of the manufacturing factory.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
fig. 1 is a general block diagram of the system of the present invention.
Description of the embodiments
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in FIG. 1, the virtual simulation training system based on the industrial robot comprises a server, wherein the server is in communication connection with a data acquisition unit, a simulation demand qualitative unit, a simulation environment qualitative unit, a simulation layout planning unit, a layout feasibility analysis unit, a re-simulation layout planning unit and a display terminal;
the data acquisition unit is used for acquiring simulation demand parameter information, simulation working environment information and simulation operation data parameters of a manufacturing factory to be applied by the industrial robot, and respectively transmitting the simulation demand parameter information, the simulation working environment information and the simulation operation data parameters to the simulation demand qualitative unit, the simulation environment qualitative unit and the layout feasibility analysis unit through the server;
when the simulation demand qualitative unit receives the simulation demand parameter information of the manufacturing factory to be applied by the industrial robot, the simulation demand qualitative unit judges, analyzes and processes the simulation demand of the industrial robot according to the simulation demand parameter information, and the specific operation process is as follows:
real-time monitoring the production line number, the production point number and the artificial quantity value in the simulation demand parameter information of the manufacturing factory applied by the industrial robot, and calibrating the production line number, the production point number and the artificial quantity value as pl and pn respectively pl And qv, and performing normalized analysis on the same according to a set formulaWherein pl=1, 2,3 … … n, obtaining a demand coefficient req introduced by a manufacturing factory to the industrial robot, wherein δ1, δ2 and δ3 are weight factor coefficients of the number of production lines, the number of production points and an artificial quantity value respectively, setting specific numerical values of δ1, δ2 and δ3 is specifically set in a specific industrial robot virtual simulation training case by a person skilled in the art, and the weight factor coefficients are used for balancing the duty ratio weights of various data in formula calculation so as to promote the accuracy of calculation results;
the number of production lines refers to the number of production lines contained in a manufacturing plant, the number of production points refers to the number of main production nodes contained in each production line in the manufacturing plant, and the manually-operated quantity refers to the ratio of the manual work workload of the manufacturing plant to the total work workload;
setting 3 demand comparison intervals of a demand coefficient introduced to an industrial robot by a manufacturing factory in a gradient manner, wherein the 3 demand comparison intervals are a first gradient demand comparison interval grad1, a second gradient demand comparison interval grad2 and a third gradient demand comparison interval grad3 respectively, and grad3=μ+grad2=2μ+grad1, μ represents a multiple of the gradient, and setting of a specific numerical value of μ is specifically set in a specific industrial robot virtual simulation training case by a person skilled in the art;
when a demand coefficient introduced by a manufacturing factory to an industrial robot is within a preset first gradient demand comparison interval grad1, generating a low demand signal; when the demand coefficient introduced by the manufacturing factory to the industrial robot is within a preset second gradient demand comparison interval grad2, generating a medium demand signal; when a demand coefficient introduced by a manufacturing factory to an industrial robot is within a preset first gradient demand comparison interval grad3, a high demand signal is generated;
and the generated high-demand signal, medium-demand signal and low-demand signal are sent to the simulation layout planning unit through the server.
When the simulation environment qualitative unit receives the simulation working environment information of the manufacturing factory, the simulation environment determination analysis processing of the manufacturing factory is carried out according to the simulation working environment information, and the specific operation process is as follows:
real-time monitoring an active area value, a line supply value and a line smoothness value in simulation working environment information of a manufacturing factory applied by an industrial robot, calibrating the active area value, the line supply value and the line smoothness value as hs, xg and xc respectively, carrying out normalization analysis, and obtaining an environment matching value bx according to a set formula bx=γ1xhs+γ2xg+γ3xc, wherein λ1, γ2 and γ3 are weight factor coefficients of the active area value, the line supply value and the line smoothness value respectively, and the components of γ1, γ2 and γ3 are natural numbers larger than 0;
it should be noted that, the activity area value refers to a maximum working activity area value that the manufacturing factory can provide for the industrial robot, and the line supply value refers to a data value of the line supply perfection degree of the manufacturing factory, wherein the line includes lines such as water, electricity, steam, network, communication, etc., and if the types of the lines are 5, and the manufacturing factory can provide three types of lines such as water, electricity and steam for the industrial robot, at this time, the line supply value of the manufacturing co-production is (3/5) ×100%; the line smoothness value refers to the smoothness of each production line in the manufacturing plant;
setting a reference threshold value1 of the environment matching value, comparing and analyzing the environment matching value with a preset reference threshold value1, generating a high environment signal when the environment matching value is larger than or equal to the preset reference threshold value1, otherwise, generating a general environment signal when the environment matching value is smaller than the preset reference threshold value 1;
and the generated high-environment signals and the generated general-environment signals are sent to the simulation layout planning unit through the server.
When the simulation layout planning unit receives a demand type judgment signal and an environment type judgment signal, wherein the demand type judgment signal comprises a high demand signal, a medium demand signal and a low demand signal, and the environment type judgment signal comprises a high environment signal and a general environment signal, the simulation layout planning unit performs layout comprehensive simulation planning analysis processing according to the high environment signal and the general environment signal, and the specific operation process is as follows:
when capturing a high-demand signal and a high-environment signal at the same time, generating a first-order matching signal, and distributing k1 industrial robot stations to a manufacturing factory according to the generated first-order matching signal;
when capturing a high-demand signal and a general environment signal or a medium-demand signal and a high-environment signal at the same time, generating a second-order matching signal, and distributing k2 industrial robot stations to a manufacturing factory according to the generated second-order matching signal;
when the medium demand signal and the general environment signal or the low demand signal and the high environment signal are captured at the same time, generating a third-order matching signal, and distributing k3 industrial robot stations to a manufacturing factory according to the generated third-order matching signal;
when the low-demand signal and the general environment signal are captured at the same time, generating a fourth-order matching signal, and distributing k4 industrial robot stations to a manufacturing factory according to the generated fourth-order matching signal;
wherein k1 > k2 > k3 > k4, and the setting of the specific values of k1, k2, k3 and k4 is specifically set by the person skilled in the art in specific cases;
the obtained simulation planning layout scheme of the industrial robot is sent to a layout feasibility analysis unit;
when the layout feasibility analysis unit is used for receiving a simulated planning layout scheme of the industrial robot, calling simulated operation data parameters of the industrial robot according to the simulated planning layout scheme, and carrying out virtual layout feasibility verification analysis of the industrial robot, the specific operation process is as follows:
based on the simulation planning layout scheme of the industrial robots, the simulation intensity, the simulation fault value and the collision risk coefficient in the simulation operation data parameters of the industrial robots of each production line are obtained, and are respectively calibrated to be ms ij 、ful ij And chc ij And carrying out formulated analysis on the sample according to a set formulaObtaining the individual simulation running state value ISR of each industrial robot of each production line ij Wherein λ1, λ2 and λ3 are weight factor coefficients of the simulation intensity, the simulation failure value and the collision risk coefficient, respectively, and λ1, λ2 and λ3 are natural numbers larger than 0, i=pl, so i represents each production line, j represents each industrial robot;
it should be noted that the simulation strength refers to the workload of the industrial robot completed in a unit time, and the simulation fault value refers to the data value of abnormal operation or wrong operation times of the industrial robot in a unit time;
the specific solving process of the collision risk coefficient is as follows:
real-time monitoring effective load value, motion track deviation value, coverage rate and service life in simulation operation parameters of industrial robots of each production line, and calibrating the effective load value, the motion track deviation value, the coverage rate and the service life as lod respectively ij 、tdv ij 、foc ij Sum of ages ij And carrying out formulated analysis on the sample according to the settingFormula of (2)Obtaining collision risk coefficient chc of each industrial robot of each production line ij Wherein, eta 1, eta 2, eta 3 and eta 4 are correction factor coefficients of effective load value, motion track deviation value, coverage rate and service life respectively, and the correction factor coefficients are used for correcting the deviation of each parameter in the formula calculation process, thereby enabling the calculation of more accurate parameter data;
it should be noted that, the service life refers to a data value of the service life of the industrial robot to be applied in the industrial manufacturing factory, and the larger the expression value of the service life of the industrial robot is, the lower the collision risk generated by the industrial robot during operation is, the coverage rate refers to the coverage area ratio of the detection range of the industrial robot, and the larger the expression value of the coverage rate is, the lower the collision risk generated by the industrial robot during operation is; the effective load value refers to the maximum load weight which can be processed when the robot works, and the larger the expression value of the effective load value is, the lower the collision risk generated in the working process of the industrial robot is;
it should also be noted that the equipment applied by each line is not exactly identical in the actual production of the manufacturing plant, and therefore the efficiency of the simulation application of each line to the industrial robot is not identical;
summing and analyzing individual simulation running state values of all industrial robots of all production lines, and according to a set formulaObtaining the production line simulation running state value LSR of each production line i ；
Setting a reference threshold value2 of the production line simulation running state value, and comparing and analyzing the production line simulation running state value of each production line with the preset reference threshold value 2;
generating a line operation feedback unqualified signal when the line simulation operation state value is greater than or equal to a preset reference threshold value2, and generating a line operation feedback qualified signal when the line simulation operation state value is less than the preset reference threshold value 2;
counting the number of production lines marked as production line operation feedback qualified signals and production line operation feedback unqualified signals in an industrial manufacturing factory respectively, marking the production lines as sum1 and sum2 respectively, generating a manufacturing factory industrial robot simulation layout standard-reaching signal if sum1 is more than sum2, and transmitting a generated simulation planning layout scheme of the industrial robot to a display terminal for display description according to the generated manufacturing factory industrial robot simulation layout standard-reaching signal;
if sum1 is less than or equal to sum2, generating a manufacturing plant industrial robot simulation layout non-standard signal, and transmitting the manufacturing plant industrial robot simulation layout non-standard signal to a re-simulation layout planning unit according to the generated manufacturing plant industrial robot simulation layout non-standard signal;
when the re-simulation layout planning unit receives a signal that the simulation layout of the industrial robot of the manufacturing factory does not reach the standard, the re-simulation layout operation is carried out according to the signal, and the specific operation process is as follows:
the method comprises the steps of monitoring a first simulation area value and a second simulation area value in a simulation environment where an industrial robot is located in real time, calibrating the first simulation area value and the second simulation area value into area1 and area2 respectively, performing differential analysis on the first simulation area value and the second simulation area value, and obtaining an area floating value sx according to a formula sx=area 1-area 2;
it should be noted that the first simulation area value refers to a maximum work activity area value that can be provided by the manufacturing factory for each industrial robot, and the second simulation area value refers to a minimum work activity area value required by each industrial robot;
setting a reference threshold value3 of the regional floating value, comparing and analyzing the regional floating value with a preset reference threshold value3, and when the regional floating value is greater than or equal to the preset reference threshold value3, adding the stations of the h1 industrial robots on the original simulation planning layout scheme of the industrial robots, namely if the original simulation planning layout scheme of the industrial robots is to distribute k1 industrial robot stations to a manufacturing factory, after adding the stations of the h1 industrial robots, replacing the simulation planning layout scheme of the existing industrial robots with the stations of the k1+h1 industrial robots to the manufacturing factory;
when the area floating value is smaller than a preset reference threshold value3, reducing the stations of the h2 industrial robots on the simulation planning layout scheme of the industrial robots, namely if the original simulation planning layout scheme of the industrial robots is to distribute k2 industrial robot stations to a manufacturing factory, after reducing the stations of the h2 industrial robots, replacing the simulation planning layout scheme of the existing industrial robots with distributing k2-h2 industrial robot stations to the manufacturing factory;
wherein, the specific values of h1 and h2 are set by a person skilled in the art in specific cases;
and repeating the layout feasibility analysis unit after the re-simulation layout operation is completed until a manufacturing plant industrial robot simulation layout standard signal is obtained, and sending the generated simulation planning layout scheme of the industrial robot to a display terminal for display description according to the generated manufacturing plant industrial robot simulation layout standard signal.
When the simulation demand analysis method is used, simulation demand parameter information of a manufacturing factory to be applied by the industrial robot is collected, simulation demand judgment analysis processing of the industrial robot is carried out, and judgment analysis of simulation demand states of the manufacturing factory is realized by means of normalization analysis, gradient interval setting and data comparison;
the simulation environment state of the manufacturing factory is clearly judged and analyzed by obtaining the simulation working environment information of the manufacturing factory and carrying out simulation environment judgment and analysis processing of the manufacturing factory and adopting a symbolized calibration mode, a formula calculation mode and a threshold comparison mode;
the demand type judgment signal and the environment type judgment signal are subjected to layout comprehensive simulation planning analysis processing, and the method of data integration analysis and station quantitative setting is utilized to realize the definite setting of the number of stations of the industrial robot required by a manufacturing factory, so that the simulation planning layout scheme of the industrial robot is further defined;
taking the simulation planning layout scheme of the industrial robot as a basis, calling the simulation operation data parameters of the industrial robot, carrying out the virtual layout feasibility verification analysis of the industrial robot, and adopting the modes of data calculation, data statistical analysis and numerical comparison analysis, thereby realizing the verification of the virtual simulation industrial robot layout feasibility while defining the reasonable state of the virtual simulation industrial robot layout of the manufacturing factory; aiming at the standard signal of the industrial robot simulation layout of the manufacturing factory, the generated simulation planning layout scheme of the industrial robot is sent to a display terminal for display description;
aiming at the generated signals that the simulation layout of the industrial robot of the manufacturing factory does not reach the standard, adopting the re-simulation layout operation to realize reasonable virtual simulation training analysis of the stations of the industrial robot of the manufacturing factory, laying a foundation for avoiding investment loss brought by layout errors to the manufacturing factory, and providing powerful support for effectively assisting the manufacturing factory to reasonably layout the industrial robot;
the method combines data analysis and simulation technology, performs high-degree simulation analysis on the working environment and the working requirement of the manufacturing factory, provides powerful support for realizing reasonable simulation layout of industrial robots of the manufacturing factory, and further improves the productivity of the manufacturing factory.
The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (2)
1. The virtual simulation training system based on the industrial robot is characterized by comprising a server, wherein the server is connected with a data acquisition unit, a simulation demand qualitative unit, a simulation environment qualitative unit, a simulation layout planning unit, a layout feasibility analysis unit, a re-simulation layout planning unit and a display terminal in a communication manner;
the data acquisition unit is used for acquiring simulation demand parameter information, simulation working environment information and simulation operation data parameters of a manufacturing factory to be applied by the industrial robot and respectively transmitting the simulation demand parameter information, the simulation working environment information and the simulation operation data parameters to the simulation demand qualitative unit, the simulation environment qualitative unit and the layout feasibility analysis unit;
the simulation demand qualitative unit is used for receiving simulation demand parameter information of a manufacturing factory to be applied by the industrial robot, judging, analyzing and processing the simulation demand of the industrial robot, obtaining a high demand signal, a medium demand signal and a low demand signal according to the simulation demand parameter information, and sending the high demand signal, the medium demand signal and the low demand signal to the simulation layout planning unit;
the simulation environment qualitative unit is used for receiving the simulation working environment information of the manufacturing factory, judging, analyzing and processing the simulation environment of the manufacturing factory, generating a high-environment signal and a general environment signal according to the simulation working environment information, and sending the high-environment signal and the general environment signal to the simulation layout planning unit;
the simulation layout planning unit performs layout comprehensive simulation planning analysis processing according to the received demand type judgment signals and environment type judgment signals, so as to obtain a simulation planning layout scheme of the industrial robot, and sends the simulation planning layout scheme to the layout feasibility analysis unit;
the layout feasibility analysis unit is used for receiving a simulation planning layout scheme of the industrial robot, calling simulation operation data parameters of the industrial robot according to the simulation planning layout scheme, performing virtual layout feasibility verification analysis of the industrial robot, generating a manufacturing plant industrial robot simulation layout standard reaching signal and a manufacturing plant industrial robot simulation layout non-standard reaching signal according to the simulation operation data parameters, and sending the manufacturing plant industrial robot simulation layout non-standard reaching signal to the re-simulation layout planning unit;
the re-simulation layout planning unit monitors a first simulation area value and a second simulation area value in a simulation environment where the industrial robot is located according to the received manufacturing plant industrial robot simulation layout substandard signal, performs re-simulation layout operation, and repeats the layout feasibility analysis unit after the completion of the re-simulation layout operation until the manufacturing plant industrial robot simulation layout substandard signal is obtained, and sends a generated simulation layout plan layout scheme of the industrial robot to a display terminal for display explanation according to the generated manufacturing plant industrial robot simulation layout substandard signal;
the specific operation steps of the simulation demand judging, analyzing and processing of the industrial robot are as follows:
real-time monitoring the production line number, the production point number and the artificial quantity value in the simulation demand parameter information of the manufacturing factory applied by the industrial robot, and calibrating the production line number, the production point number and the artificial quantity value as pl and pn respectively pl And qv, and performing normalized analysis on the same according to a set formulaWherein pl=1, 2,3 … … n, obtaining a demand coefficient req introduced by a manufacturing factory to the industrial robot, wherein δ1, δ2 and δ3 are weight factor coefficients of the production line number, the production point number and the artificial quantity value respectively;
setting a first gradient demand comparison section grad1, a second gradient demand comparison section grad2 and a third gradient demand comparison section grad3 of a demand coefficient introduced by a manufacturing factory to the industrial robot;
when a demand coefficient introduced by a manufacturing factory to an industrial robot is within a preset first gradient demand comparison interval grad1, generating a low demand signal; when the demand coefficient introduced by the manufacturing factory to the industrial robot is within a preset second gradient demand comparison interval grad2, generating a medium demand signal; when a demand coefficient introduced by a manufacturing factory to an industrial robot is within a preset first gradient demand comparison interval grad3, a high demand signal is generated;
the specific operation steps of the simulation environment judgment analysis processing of the manufacturing factory are as follows:
real-time monitoring an active area value, a line supply value and a line smoothness value in simulation working environment information of a manufacturing factory applied by an industrial robot, respectively calibrating the active area value, the line supply value and the line smoothness value as hs, xg and xc, carrying out normalization analysis, and obtaining an environment matching value bx according to a set formula bx=γ1hs+γ2xg+γ3xc, wherein λ1, γ2 and γ3 are weight factor coefficients of the active area value, the line supply value and the line smoothness value respectively;
setting a reference threshold value1 of the environment matching value, comparing and analyzing the environment matching value with a preset reference threshold value1, generating a high environment signal when the environment matching value is larger than or equal to the preset reference threshold value1, otherwise, generating a general environment signal when the environment matching value is smaller than the preset reference threshold value 1;
the specific operation steps of the comprehensive layout simulation planning analysis processing are as follows:
when capturing a high-demand signal and a high-environment signal at the same time, generating a first-order matching signal, and distributing k1 industrial robot stations to a manufacturing factory according to the generated first-order matching signal;
when capturing a high-demand signal and a general environment signal or a medium-demand signal and a high-environment signal at the same time, generating a second-order matching signal, and distributing k2 industrial robot stations to a manufacturing factory according to the generated second-order matching signal;
when the medium demand signal and the general environment signal or the low demand signal and the high environment signal are captured at the same time, generating a third-order matching signal, and distributing k3 industrial robot stations to a manufacturing factory according to the generated third-order matching signal;
when the low-demand signal and the general environment signal are captured at the same time, generating a fourth-order matching signal, and distributing k4 industrial robot stations to a manufacturing factory according to the generated fourth-order matching signal;
the specific operation steps of the re-simulation layout operation are as follows:
monitoring a first simulation area value and a second simulation area value in a simulation environment where the industrial robot is located in real time, and performing differential analysis on the first simulation area value and the second simulation area value to obtain an area floating value;
setting a reference threshold value3 of the regional floating value, comparing and analyzing the regional floating value with a preset reference threshold value3, and adding h1 stations of the industrial robot on the original simulation planning layout scheme of the industrial robot when the regional floating value is greater than or equal to the preset reference threshold value 3;
otherwise, when the regional floating value is smaller than a preset reference threshold value3, the stations of the h2 industrial robots are reduced on the simulation planning layout scheme of the industrial robots.
2. The industrial robot-based virtual simulation training system of claim 1, wherein the specific operation steps of the industrial robot virtual layout feasibility verification analysis are as follows:
based on a simulation planning layout scheme of the industrial robots, obtaining simulation intensity, simulation fault values and collision risk coefficients in simulation operation data parameters of the industrial robots of each production line, and carrying out formulated analysis on the simulation intensity, the simulation fault values and the collision risk coefficients to obtain individual simulation operation state values of the industrial robots of each production line;
carrying out summation analysis on individual simulation running state values of all industrial robots of all production lines to obtain production line simulation running states of all production lines;
setting a reference threshold value2 of the production line simulation running state value, and comparing and analyzing the production line simulation running state value of each production line with the preset reference threshold value 2;
generating a line operation feedback unqualified signal when the line simulation operation state value is greater than or equal to a preset reference threshold value2, and generating a line operation feedback qualified signal when the line simulation operation state value is less than the preset reference threshold value 2;
counting the number of production lines marked as production line operation feedback qualified signals and production line operation feedback unqualified signals in an industrial manufacturing factory respectively, marking the production lines as sum1 and sum2 respectively, and generating a manufacturing factory industrial robot simulation layout unqualified signal if sum1 is less than or equal to sum 2;
otherwise, if sum1 is larger than sum2, generating a simulation layout standard signal of the industrial robot of the manufacturing plant, and generating the simulation layout standard signal of the industrial robot of the manufacturing plant.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310262380.5A CN116229792B (en) | 2023-03-17 | 2023-03-17 | Virtual simulation training system based on industrial robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310262380.5A CN116229792B (en) | 2023-03-17 | 2023-03-17 | Virtual simulation training system based on industrial robot |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116229792A CN116229792A (en) | 2023-06-06 |
| CN116229792B true CN116229792B (en) | 2024-01-16 |
Family
ID=86582443
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310262380.5A Active CN116229792B (en) | 2023-03-17 | 2023-03-17 | Virtual simulation training system based on industrial robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116229792B (en) |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08187648A (en) * | 1995-01-10 | 1996-07-23 | Yokogawa Sogo Kenkyusho:Kk | Production line construction method and production line control system |
| KR20090123052A (en) * | 2008-05-27 | 2009-12-02 | 재단법인서울대학교산학협력재단 | Apparatus and method for consulting layout of shipyard based simulation |
| KR20090123053A (en) * | 2008-05-27 | 2009-12-02 | 재단법인서울대학교산학협력재단 | Apparatus and method for consulting layout of factory based simulation |
| WO2019112379A1 (en) * | 2017-12-08 | 2019-06-13 | 에스케이 주식회사 | Method and system for designing layout of smart factory |
| CN111240283A (en) * | 2020-01-14 | 2020-06-05 | 天津大学 | Construction method of adaptable planning design simulation platform for intelligent manufacturing system |
| CN111553076A (en) * | 2020-04-27 | 2020-08-18 | 南京晓庄学院 | City planning and environment protection method and system based on virtual simulation experience |
| CN114722623A (en) * | 2022-04-22 | 2022-07-08 | 东风设计研究院有限公司 | Intelligent factory design simulation rapid layout system and method |
| CN114943465A (en) * | 2022-06-07 | 2022-08-26 | 大连卓居科技有限公司 | Enterprise management consultation service system based on data analysis |
| CN115048815A (en) * | 2022-08-11 | 2022-09-13 | 广州海颐软件有限公司 | Database-based intelligent simulation management system and method for power service |
| CN115758652A (en) * | 2022-08-31 | 2023-03-07 | 天津大学 | Manufacturing system processing capacity re-promotion optimization method and system based on digital twinning |
-
2023
- 2023-03-17 CN CN202310262380.5A patent/CN116229792B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08187648A (en) * | 1995-01-10 | 1996-07-23 | Yokogawa Sogo Kenkyusho:Kk | Production line construction method and production line control system |
| KR20090123052A (en) * | 2008-05-27 | 2009-12-02 | 재단법인서울대학교산학협력재단 | Apparatus and method for consulting layout of shipyard based simulation |
| KR20090123053A (en) * | 2008-05-27 | 2009-12-02 | 재단법인서울대학교산학협력재단 | Apparatus and method for consulting layout of factory based simulation |
| WO2019112379A1 (en) * | 2017-12-08 | 2019-06-13 | 에스케이 주식회사 | Method and system for designing layout of smart factory |
| CN111240283A (en) * | 2020-01-14 | 2020-06-05 | 天津大学 | Construction method of adaptable planning design simulation platform for intelligent manufacturing system |
| CN111553076A (en) * | 2020-04-27 | 2020-08-18 | 南京晓庄学院 | City planning and environment protection method and system based on virtual simulation experience |
| CN114722623A (en) * | 2022-04-22 | 2022-07-08 | 东风设计研究院有限公司 | Intelligent factory design simulation rapid layout system and method |
| CN114943465A (en) * | 2022-06-07 | 2022-08-26 | 大连卓居科技有限公司 | Enterprise management consultation service system based on data analysis |
| CN115048815A (en) * | 2022-08-11 | 2022-09-13 | 广州海颐软件有限公司 | Database-based intelligent simulation management system and method for power service |
| CN115758652A (en) * | 2022-08-31 | 2023-03-07 | 天津大学 | Manufacturing system processing capacity re-promotion optimization method and system based on digital twinning |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116229792A (en) | 2023-06-06 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106643765B (en) | Method for calculating acquisition abnormal maintenance time length | |
| CN107194565B (en) | Power grid scheduling optimization method and system based on cloud decision | |
| CN112098715B (en) | Electric energy monitoring and early warning system based on 5G and correction GCN graph neural network | |
| CN109664008A (en) | A kind of repair welding system and intelligent repair method | |
| CN116823531B (en) | Building energy consumption management system based on BIM building | |
| CN117151631A (en) | Construction progress monitoring and management system based on wisdom building site | |
| CN116229792B (en) | Virtual simulation training system based on industrial robot | |
| CN103914740B (en) | A kind of powerline ice-covering prediction and automatic correcting method based on data-driven | |
| CN109858712A (en) | The transregional automated transaction of the stock a few days ago strategy of one kind and economic evaluation method | |
| CN115545868A (en) | Financial service integrated fund management system for enterprise operation | |
| CN117932976A (en) | Method and device for acquiring process machine set energy data | |
| CN113671922A (en) | Production plan management system based on block chain | |
| CN116050716B (en) | Intelligent park management control platform based on Internet | |
| CN117114442A (en) | Edge computing center layout optimization method | |
| CN110556921A (en) | safety monitoring system for real-time operation of power grid | |
| CN115933477A (en) | Centralized display system for production state of storage battery | |
| CN108764751A (en) | A kind of assembling line efficiency estimation method | |
| CN113869502A (en) | Deep neural network-based bolt tightening failure reason analysis method | |
| CN113705836A (en) | System and device for power grid field operation guidance | |
| CN117134508B (en) | Multi-data fusion monitoring system of power distribution one-key centralized control device | |
| CN118071178B (en) | Method and device for evaluating abnormal state of power station, electronic equipment and storage medium | |
| CN117232041A (en) | GIS-based visual heat supply regulation and control system and method | |
| CN110244096A (en) | Code is expired to ammeter in a kind of electric energy metering system and finds method with processing automatically | |
| CN117543564B (en) | Power grid regulation and control method and system based on countermeasure type neural network | |
| CN103927593A (en) | Photovoltaic generation power prediction method based on self-learning composite data source autoregression model |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |