CN117236138B - Digital twinning-based robot motion control and state monitoring method and system - Google Patents
Digital twinning-based robot motion control and state monitoring method and system Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 48
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- 238000012423 maintenance Methods 0.000 claims abstract description 343
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- 238000004088 simulation Methods 0.000 claims abstract description 167
- 238000011156 evaluation Methods 0.000 claims abstract description 71
- 230000008569 process Effects 0.000 claims abstract description 19
- 238000003466 welding Methods 0.000 claims description 101
- 238000005520 cutting process Methods 0.000 claims description 62
- 230000008439 repair process Effects 0.000 claims description 28
- 238000005336 cracking Methods 0.000 claims description 27
- 238000001514 detection method Methods 0.000 claims description 16
- 238000004364 calculation method Methods 0.000 claims description 13
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Abstract
The invention relates to the technical field of robots, in particular to a digital twinning-based robot motion control and state monitoring method and system, wherein the method comprises the following steps of S01, collecting three-dimensional space data of a part to be maintained; s02, constructing a real-time simulation model of the part to be maintained and determining defects and maintenance modes of the part to be maintained; s03, repairing the defects in real time by using the repairing parameters determined by the defect grades, updating the real-time simulation model in the repairing process, and adjusting the repairing parameters based on the difference between the updated real-time simulation model and the standard simulation model; s04, detecting defects, calculating to obtain defect indexes, determining maintenance results, and determining that the maintenance tool is finished to be maintained or to continue to be maintained according to the maintenance results; s05, calculating the maintenance evaluation value and determining the evaluation grade. According to the invention, the real-time simulation analysis of the digital twin module and the motion control of the robot are performed cooperatively, so that the accuracy of the motion control of the robot is improved.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a digital twinning-based robot motion control and state monitoring method and system.
Background
With the development of robot technology, more and more movable robots are applied, and the production and the living of human beings are greatly facilitated. Robot motion control is an important part in robot technology, and mainly relates to control of a robot motion track, joints and joint angles so as to realize accurate motion of a robot. In the motion control process of the robot, real-time data of the motion of the robot are required to be subjected to depth analysis, so that the motion state of the robot is regulated and controlled more accurately. The digital twin is to integrate multi-discipline, multi-physical quantity, multi-scale and multi-probability simulation processes by using the data of the physical model, the sensor and the operation history, and complete mapping in the virtual space, thereby reflecting the full life cycle process of the corresponding entity equipment. Digital twinning is a universally adapted theoretical technology system and can be applied in a plurality of fields, such as product design, product manufacturing, medical analysis, engineering construction and the like. Therefore, the real-time analysis is performed based on digital twinning in the application process of the robot, so that the analysis process and the analysis result are performed cooperatively with the motion control of the robot, and the method has very important significance for the motion control of the robot.
Patent document publication No. CN113070882a discloses an inspection robot control system, method, apparatus, and electronic device, the system including an electronic device and an inspection robot including a moving mechanism and a depth sensor; the depth sensor is used for sending the acquired image data to the electronic equipment; the electronic equipment is used for detecting whether an obstacle exists in the overhaul tunnel according to the data acquired by the depth sensor, and calculating the running path of the overhaul robot according to the detection result; the moving mechanism is used for moving the position according to the running path calculated by the electronic equipment so as to drive the maintenance robot to move.
However, in the prior art, the analysis conditions for the movement control of the maintenance robot are single, which results in inaccurate movement control of the robot.
Disclosure of Invention
Therefore, the invention provides a method and a system for controlling the movement of a robot and monitoring the state based on digital twinning, which are cooperatively carried out by real-time analysis of a digital twinning module and the movement control of the robot so as to solve the problem of inaccurate movement control of the robot in the prior art.
To achieve the above object, the present invention provides a digital twin-based robot motion control and status monitoring method, the method comprising:
S01, collecting three-dimensional space data of a part to be maintained;
s02, constructing a real-time simulation model of the part to be maintained, determining defects of the part to be maintained according to the difference between a preset standard simulation model and the real-time simulation model, determining a maintenance mode according to the defects, and selecting a maintenance tool of the robot;
s03, determining a defect grade and repairing the defect in real time according to the repairing parameters determined by the defect grade,
updating the real-time simulation model during maintenance,
and adjusting the maintenance parameters based on differences between the updated real-time simulation model and the standard simulation model;
s04, detecting the defects and calculating to obtain defect indexes, determining maintenance results according to the defect indexes, and determining that the maintenance tool is finished to be maintained or to continue to be maintained according to the maintenance results;
s05, calculating to obtain a maintenance evaluation value, comparing the evaluation value with a preset standard evaluation value to obtain a comparison result, and determining an evaluation grade according to the comparison result;
calculating according to a preset maintenance result evaluation model to obtain a maintenance evaluation value P= (γd multiplied by β1+γh multiplied by β2+γw multiplied by β3) multiplied by 100/(β1+β2+β3), wherein P is an evaluation value of the robot for maintaining the part to be maintained, β1 is a maintenance weight of the first part to be maintained, β2 is a maintenance weight of the second part to be maintained, β3 is a maintenance weight of the third part to be maintained, γd is a concave defect index, γh is a convex defect index, and γw is a cracking defect index;
The conditions for determining the evaluation level are: p epsilon [0, P0] is first-level maintenance, P epsilon (P0, 2 x P0) is second-level maintenance, P epsilon (2 x P0, ++ infinity) is third-level maintenance, wherein P0 is a preset standard evaluation value;
wherein, the step S02 of constructing a real-time simulation model of the component to be maintained comprises the following steps:
s021, establishing a three-dimensional space standard coordinate system and determining the three-dimensional space data as international unit system data under the standard coordinate system;
s022, carrying out data processing on the three-dimensional space data and obtaining a plurality of finite element grid data of the part to be maintained;
s023, generating a real-time simulation model of the part to be maintained under the three-dimensional space standard coordinate system according to the finite element grid data.
Further, the step S02 of determining a defect of the component to be repaired according to a difference between a preset standard simulation model and the real-time simulation model, determining a repair mode according to the defect, and selecting a repair tool of the robot, includes:
when the surface depression depth D of the part to be maintained is larger than the standard depression depth D0, determining a part to be maintained of the part to be maintained as a first part to be maintained, determining a defect of the first part to be maintained as a depression, determining a maintenance mode as reverse knocking, and selecting a maintenance tool of a robot as a hammer;
When the surface protrusion height H of the part to be maintained is larger than the standard protrusion height H0, determining the part to be maintained of the part to be maintained as a second part to be maintained and determining the defect of the second part to be maintained as a protrusion, determining the maintenance mode as cutting and selecting a maintenance tool of a robot as a cutting knife;
when the crack width W of the part to be maintained is larger than the standard crack width W0, determining the part to be maintained of the part to be maintained as a third part to be maintained and determining the defect of the third part to be maintained as cracking, determining the maintenance mode as welding and selecting a maintenance tool of a robot as a welding gun.
Further, determining a defect level and repairing the defect in real time with a repair parameter determined by the defect level, comprising:
the conditions for determining the dent level are:
the surface pit depth D epsilon [ D0, 2X D0] is a first pit level, and the surface pit depth D epsilon (2X D0, ++ infinity) is a second pit level;
the first concave maintenance parameter determined by the first concave grade is that the knocking acting force of the hammer is standard knocking acting force F0 and the knocking speed of the hammer is standard knocking speed Vf0, the second concave maintenance parameter determined by the second concave grade is that the knocking acting force of the hammer is maximum knocking acting force Fm and the knocking speed of the hammer is maximum knocking speed Vfm, wherein Fm=2×F0, F0 is preset standard knocking acting force, vfm=2×vf0, and Vf0 is preset standard knocking speed;
The conditions for determining the bump level are:
the surface protrusion height H epsilon [ H0, 2X H0] is a first protrusion level, and the surface protrusion height H epsilon (2X H0, ++ infinity) is a second protrusion level;
the first bulge maintenance parameter determined by the first bulge level is that the cutting acting force of the cutting knife is standard cutting acting force Q0 and the cutting speed of the cutting knife is standard cutting speed Vq0, the second bulge maintenance parameter determined by the second bulge level is that the cutting acting force of the cutting knife is maximum cutting acting force Qm and the cutting speed of the cutting knife is maximum cutting speed Vqm, wherein qm=2×Q0, Q0 is preset standard cutting acting force, vqm =2×Vq0 and Vq0 is preset standard cutting speed;
the conditions for determining the welding grade are:
the crack width W epsilon [ W0,2 XW 0] is a first welding grade, and the crack width W epsilon (2 XW 0, ++ infinity) is a second welding grade;
the first welding maintenance parameter determined by the first welding grade is that the welding strength of the welding gun is standard welding strength H0 and the welding speed of the welding gun is standard welding speed Vh0, the second welding maintenance parameter determined by the second welding grade is that the welding strength of the welding gun is maximum welding strength Hm and the welding speed of the welding gun is maximum welding speed Vhm, wherein Hm=2×H2H0, H0 is preset standard welding strength, vhm =2×Vh0 and Vh0 is preset standard welding speed;
When the defect grade is determined to be a first concave grade, the first part to be repaired is repaired in real time by the first concave repair parameter; when the defect grade is determined to be a second concave grade, the first part to be repaired is repaired in real time by the second concave repair parameter;
when the defect grade is determined to be a first bulge grade, the first bulge maintenance parameter is used for carrying out real-time maintenance on the second part to be maintained; when the defect grade is determined to be a second bulge grade, the second bulge maintenance parameter is used for carrying out real-time maintenance on the second part to be maintained;
when the defect grade is determined to be a first welding grade, the first welding maintenance parameter is used for carrying out real-time maintenance on the third part to be maintained; and when the defect grade is determined to be a second welding grade, the third part to be repaired is repaired in real time by the second welding repair parameter.
Further, updating the real-time simulation model during maintenance includes: the three-dimensional space data are time sequence data, the three-dimensional space data at the i moment are recorded as (xi, yi, zi), the three-dimensional space data at the i-1 moment are recorded as (x (i-1), y (i-1), z (i-1)), the three-dimensional space data at the i moment are compared with the three-dimensional space data at the i-1 moment, and when (xi, yi, zi) is not equal to (x (i-1), y (i-1) and z (i-1)), the three-dimensional space data of the part to be maintained are judged to be changed, and the real-time simulation model is updated according to the three-dimensional space data at the i moment to obtain an updated real-time simulation model.
Further, adjusting the maintenance parameter based on a difference of the updated real-time simulation model and the standard simulation model includes:
when the difference between the updated real-time simulation model and the standard simulation model is the updated surface depression depth Dg epsilon [ D0, 2X D0], the maintenance parameter is adjusted to be a first depression maintenance parameter; when the difference between the updated real-time simulation model and the standard simulation model is the updated surface concave depth Dg epsilon (2X D0, ++ infinity), the maintenance parameter is adjusted to be a second concave maintenance parameter;
when the difference between the updated real-time simulation model and the standard simulation model is the updated surface protrusion height Hg epsilon [ H0, 2X H0], the maintenance parameter is adjusted to be a first protrusion maintenance parameter; when the difference between the updated real-time simulation model and the standard simulation model is the updated surface protrusion height Hg epsilon (2X H0, ++ infinity), the maintenance parameter is adjusted to be a second protrusion maintenance parameter;
when the difference between the updated real-time simulation model and the standard simulation model is updated crack width Wg epsilon [ W0, 2X W0], adjusting the maintenance parameter to be a first welding maintenance parameter; and when the difference between the updated real-time simulation model and the standard simulation model is the updated crack width Wg epsilon (2 XW 0, ++ infinity), adjusting the maintenance parameter to be a second welding maintenance parameter.
Further, detecting the defect and calculating a defect index, determining a maintenance result according to the defect index, and determining that the maintenance tool is finished to be maintained or is continued to be maintained according to the maintenance result, wherein the method comprises the following steps:
when the defect is detected to be a pit, a pit defect index γd=d/D0 is calculated; when the defect is detected to be a bulge, calculating a bulge defect index gamma h=H/H0; when the defect is detected to be cracking, calculating a cracking defect index gamma w=W/W0;
the conditions for determining that the maintenance result is qualified for maintenance are as follows: determining that the first part to be maintained is qualified in maintenance when the concave defect index gamma d epsilon [0, gamma d0 ]; when the convex defect indexes gamma h epsilon [0, gamma h0], determining that the second part to be maintained is qualified in maintenance; when the cracking defect index gamma w epsilon [0, gamma w0] is determined that the third part to be maintained is qualified; wherein γd0 is a preset standard concave defect index, γh0 is a preset standard convex defect index, and γw0 is a preset standard cracking defect index;
the conditions for determining that the maintenance result is unqualified are as follows: determining that the first part to be maintained is unqualified when the concave defect index gamma d epsilon (gamma d0, ++ infinity); when the convex defect index gamma h epsilon (gamma h0, ++ infinity), determining that the maintenance of the second part to be maintained is unqualified; determining that the third part to be maintained is unqualified when the cracking defect index gamma w epsilon (gamma w0, ++ infinity);
When the maintenance result is that the maintenance is qualified, determining that the maintenance tool finishes maintenance; and when the maintenance result is that the maintenance is not qualified, determining that the maintenance tool continues to maintain.
Further, the S022 includes: performing primary division and secondary division on the three-dimensional space data of the part to be maintained, wherein the primary division is used for dividing the three-dimensional space data of the part to be maintained into a plurality of first three-dimensional shape finite element grid data, the first three-dimensional shape finite element grid data comprises first standard three-dimensional shape finite element grid data and first non-standard three-dimensional shape finite element grid data,
the X-direction differential value delta X1 = Xi-X (i-1), the Y-direction differential value delta y1 = Yi-Y (i-1), the Z-direction differential value delta z1 = Zi-Z (i-1), wherein Xi is the ith point X direction value under the standard coordinate system, X (i-1) is the ith point X direction value under the standard coordinate system, yi is the ith point Y direction value under the standard coordinate system, Y (i-1) is the ith point Y direction value under the standard coordinate system, zi is the ith point Z direction value under the standard coordinate system, Z (i-1) is the ith point Z direction value under the standard coordinate system;
When Δx1=Δx0 and Δy1=Δy0 and Δz1=Δz0, the first three-dimensional shape finite element mesh data is first standard three-dimensional shape finite element mesh data, where Δx0 is a preset X-direction standard deviation value and Δy0 is a preset Y-direction standard deviation value; Δz0 is a preset Z-direction standard deviation value;
when Δx1 e [0, Δx0) or Δy1 e [0, Δy0) or Δz1 e [0, Δz0), the first three-dimensional shape finite element mesh data is first non-standard three-dimensional shape finite element mesh data;
the secondary division is used for dividing the first non-standard three-dimensional shape finite element mesh data into a plurality of second three-dimensional shape finite element mesh data,
the X-direction differential value Δx2=α1×Δx1, the Y-direction differential value Δy2=α2×Δy1, and the Z-direction differential value Δz2=α3×Δz1 of the second three-dimensional finite element mesh data, wherein α1 is a first correction coefficient for correcting the X-direction differential value, α2 is a second correction coefficient for correcting the Y-direction differential value, and α3 is a third correction coefficient for correcting the Y-direction differential value.
In another aspect, the present invention also provides a system for controlling movement and monitoring state of a robot based on digital twinning, the system comprising:
The data acquisition module is used for acquiring three-dimensional space data of the part to be maintained through a three-dimensional vision sensor arranged on the face of the robot;
the digital twin module is connected with the data acquisition module and comprises a simulation unit and a comparison unit, wherein the simulation unit is used for constructing a real-time simulation model of the part to be maintained, and the comparison unit is used for determining defects of the part to be maintained according to the difference between a preset standard simulation model and the real-time simulation model, determining a maintenance mode according to the defects and selecting a maintenance tool of the robot;
the maintenance module is connected with the digital twin module and comprises a maintenance unit, an updating unit and an adjusting unit, wherein the maintenance unit is used for determining a defect grade and maintaining the defect in real time according to maintenance parameters determined by the defect grade, the updating unit is used for updating the real-time simulation model in the maintenance process, and the adjusting unit is used for adjusting the maintenance parameters based on the difference between the updated real-time simulation model and the standard simulation model;
the detection module is connected with the maintenance module and comprises a detection unit and a determination unit, wherein the detection unit is used for detecting the defects and calculating to obtain defect indexes, and the determination unit is used for determining maintenance results according to the defect indexes and determining that the maintenance tool is finished to be maintained or to continue to be maintained according to the maintenance results;
The evaluation module is connected with the detection module and comprises a calculation unit and an evaluation unit, wherein the calculation unit is used for calculating and obtaining a maintenance evaluation value, and the evaluation unit is used for comparing the evaluation value with a preset standard evaluation value to obtain a comparison result and determining an evaluation grade according to the comparison result.
Compared with the prior art, the method has the beneficial effects that the real-time simulation model is generated by modeling the part to be maintained by utilizing the three-dimensional space data, so that the simulation imaging of the part to be maintained based on the real-time three-dimensional space data is realized; by comparing the real-time simulation model with a preset standard simulation model and determining the defects of the parts to be maintained, real-time analysis based on the three-dimensional simulation model is realized; the maintenance mode is determined according to the defects of the parts to be maintained, and the maintenance tool of the robot is selected according to the maintenance mode, so that the analysis result is obtained based on the real-time analysis of the three-dimensional simulation model, and the timeliness and reliability of the analysis are improved; the defect grade is determined, and the defects are maintained in real time by the maintenance parameters determined by the defect grade, so that the analysis process and the analysis result based on the real-time simulation model are carried out with the motion control system of the robot, and the reliability and the accuracy of the motion control of the robot are improved; the real-time simulation model is updated in the maintenance process, and the maintenance parameters are adjusted based on the difference between the updated real-time simulation model and the standard simulation model, so that the working state of the maintenance tool is adjusted in real time in the analysis process based on the three-dimensional simulation model, and the maintenance accuracy is improved; the closed-loop control of the robot maintenance motion is realized by detecting the defect of the part to be maintained, determining a maintenance result according to the defect index and determining the maintenance tool to continue maintenance or finish maintenance according to the maintenance result; and the maintenance evaluation value is obtained through calculation, the evaluation value is compared with a preset standard evaluation value to obtain a comparison result, and the evaluation grade is determined according to the comparison result, so that the maintenance quality of the part to be maintained of the robot is improved.
In particular, the real-time analysis based on the three-dimensional simulation model is realized by determining the defects of the part to be maintained according to the difference between the preset standard simulation model and the real-time simulation model; by determining the maintenance mode according to the defects of the part to be maintained and selecting the maintenance tool of the robot according to the defects, the real-time analysis based on the three-dimensional simulation model is realized to obtain an analysis result, and the timeliness and reliability of the analysis are improved; the defects of the part to be maintained are determined to be concave according to the concave depth of the surface of the part to be maintained, the maintenance mode is determined to be reverse knocking, and the maintenance tool of the robot is selected as a hammer, so that analysis, identification and maintenance of the concave defects are realized; the defects of the parts to be maintained are determined to be bulges according to the bulge heights of the surfaces of the parts to be maintained, the maintenance mode is determined to be cutting, and the maintenance tool of the robot is selected as a cutting knife, so that the analysis, identification and maintenance of the bulge defects are realized; the analysis, identification and maintenance of the cracking defects are realized by determining the defects of the to-be-maintained parts as cracking according to the crack width of the to-be-maintained parts, determining the maintenance mode as welding and selecting the maintenance tool of the robot as a welding gun.
Particularly, the knocking acting force and knocking speed of the hammer are determined specifically by determining the depression grade according to the depression depth and further determining the maintenance parameters, so that the maintenance accuracy of the hammer on the depression part is improved; the method has the advantages that the projection grade is determined according to the height of the projection, the maintenance parameters are further determined, the cutting acting force and the cutting speed of the cutting knife are particularly determined, and the maintenance accuracy of the cutting knife on the projection part is improved; the welding strength and the welding speed of the welding gun are specifically determined by determining the cracking grade and further determining the maintenance parameters according to the width of the crack, so that the maintenance accuracy of the welding gun on the crack part is improved.
In particular, by updating the real-time simulation model in the maintenance process, the data update of constructing the real-time simulation model based on the real-time three-dimensional space data is realized, and the instantaneity of analysis of the simulation model is ensured.
In particular, the maintenance parameters are adjusted based on the difference between the updated real-time simulation model and the standard simulation model, so that the working state of the maintenance tool is adjusted in real time according to the analysis result, and the maintenance accuracy is improved.
In particular, by detecting the defects and calculating to obtain a defect index, determining a maintenance result according to the defect index, and determining that the maintenance tool is finished to be maintained or is continued to be maintained according to the maintenance result, closed-loop control of robot maintenance movement is realized, and the accuracy and the integrity of robot maintenance are improved.
Particularly, the maintenance evaluation value is obtained through calculation, the evaluation value is compared with a preset standard evaluation value to obtain a comparison result, and the evaluation grade is determined according to the comparison result, so that the maintenance quality of the robot to-be-maintained parts is improved; by setting different maintenance weights, the importance degree of local maintenance in overall maintenance can be flexibly adjusted.
In particular, the standardization of the space coordinate system and the data pattern is realized by establishing a three-dimensional space standard coordinate system and determining the three-dimensional space data as international unit system data under the standard coordinate system; the accuracy of simulation data is improved by carrying out data processing on the three-dimensional space data and obtaining a plurality of finite element grid data of the part to be maintained; by generating the three-dimensional simulation model of the part to be maintained under the three-dimensional space standard coordinate system according to the finite element grid data, the full-angle three-dimensional simulation of the part to be maintained is realized.
In particular, by carrying out primary division and secondary division on the three-dimensional space data of the part to be maintained, the accuracy of simulation data is improved, and the non-standard three-dimensional shape finite element grid data is more refined and higher in accuracy.
Drawings
FIG. 1 is a flowchart of a method for controlling the motion and monitoring the state of a robot based on digital twinning according to an embodiment of the present invention;
FIG. 2 is a flow chart of a process of constructing a real-time simulation model of the component to be maintained in S02 in the digital twin-based robot motion control and status monitoring method according to the embodiment of the present invention;
fig. 3 is a schematic structural diagram of the digital twin-based robot motion control and status monitoring system according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a digital twin module structure of the digital twin-based robot motion control and status monitoring system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a maintenance module of the digital twin-based robot motion control and status monitoring system according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a detection module of the digital twin-based robot motion control and status monitoring system according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an evaluation module of the digital twin-based robot motion control and status monitoring system according to an embodiment of the present invention;
reference numerals: 1. a data acquisition module; 2. a digital twinning module; 3. a maintenance module; 4. a detection module; 5. an evaluation module; 201. a simulation unit; 202. a comparison unit; 301. a maintenance unit; 302. an updating unit; 303. an adjusting unit; 401. a detection unit; 402. a determination unit; 501. a calculation unit; 502. and an evaluation unit.
Detailed Description
In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.
It should be noted that, in the description of the present invention, terms such as "upper," "lower," "left," "right," "inner," "outer," and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, which are merely for convenience of description, and do not indicate or imply that the apparatus or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention.
Furthermore, it should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.
The digital twin-based robot motion control and state monitoring method and system, as shown in fig. 1-7, can be implemented as follows:
as shown in fig. 1, the method for controlling the movement and monitoring the state of the robot based on digital twin comprises the following steps:
s01, collecting three-dimensional space data of a part to be maintained;
s02, constructing a real-time simulation model of the part to be maintained, determining defects of the part to be maintained according to the difference between a preset standard simulation model and the real-time simulation model, determining a maintenance mode according to the defects, and selecting a maintenance tool of the robot;
s03, determining the defect grade and repairing the defect in real time according to the repairing parameters determined by the defect grade,
updating the real-time simulation model during maintenance,
and adjusting maintenance parameters based on the difference between the updated real-time simulation model and the standard simulation model;
s04, detecting defects and calculating to obtain defect indexes, determining maintenance results according to the defect indexes, and determining that the maintenance tool is finished to be maintained or to continue to be maintained according to the maintenance results;
s05, calculating to obtain a maintenance evaluation value, comparing the evaluation value with a preset standard evaluation value to obtain a comparison result, and determining an evaluation grade according to the comparison result;
Specifically, as shown in fig. 2, the step S02 of constructing a real-time simulation model of the component to be repaired includes:
s021, establishing a three-dimensional space standard coordinate system and determining the three-dimensional space data as international unit system data under the standard coordinate system;
s022, carrying out data processing on the three-dimensional space data and obtaining a plurality of finite element grid data of the part to be maintained;
s023, generating a real-time simulation model of the part to be maintained under the three-dimensional space standard coordinate system according to the finite element grid data.
Modeling the part to be maintained by utilizing the three-dimensional space data to generate a real-time simulation model, so that simulation imaging of the part to be maintained based on the real-time three-dimensional space data is realized; by comparing the real-time simulation model with a preset standard simulation model and determining the defects of the parts to be maintained, real-time analysis based on the three-dimensional simulation model is realized; the maintenance mode is determined according to the defects of the parts to be maintained, and the maintenance tool of the robot is selected according to the maintenance mode, so that the analysis result is obtained based on the real-time analysis of the three-dimensional simulation model, and the timeliness and reliability of the analysis are improved; the defect grade is determined, and the defects are maintained in real time by the maintenance parameters determined by the defect grade, so that the analysis process and the analysis result based on the real-time simulation model are carried out with the motion control system of the robot, and the reliability and the accuracy of the motion control of the robot are improved; the real-time simulation model is updated in the maintenance process, and the maintenance parameters are adjusted based on the difference between the updated real-time simulation model and the standard simulation model, so that the working state of the maintenance tool is adjusted in real time in the analysis process based on the three-dimensional simulation model, and the maintenance accuracy is improved; the closed-loop control of the robot maintenance motion is realized by detecting the defects of the part to be maintained, determining the maintenance result according to the defect index and determining the maintenance tool to continue maintenance or finish maintenance according to the maintenance result; and the maintenance evaluation value is obtained through calculation, the evaluation value is compared with a preset standard evaluation value to obtain a comparison result, and the evaluation grade is determined according to the comparison result, so that the maintenance quality of the part to be maintained of the robot is improved.
The standardization of the space coordinate system and the data pattern is realized by establishing a three-dimensional space standard coordinate system and determining the three-dimensional space data as international unit system data under the standard coordinate system; the accuracy of simulation data is improved by carrying out data processing on the three-dimensional space data and obtaining a plurality of finite element grid data of the part to be maintained; by generating the three-dimensional simulation model of the part to be maintained under the three-dimensional space standard coordinate system according to the finite element grid data, the full-angle three-dimensional simulation of the part to be maintained is realized.
Specifically, S02 determines a defect of a part to be repaired according to a difference between a preset standard simulation model and a real-time simulation model, determines a repair mode according to the defect, and selects a repair tool of the robot, including:
when the surface depression depth D of the part to be maintained is larger than the standard depression depth D0, determining the part to be maintained of the part to be maintained as a first part to be maintained and determining the defect of the first part to be maintained as depression, determining the maintenance mode as reverse knocking and selecting the maintenance tool of the robot as a hammer;
when the surface protrusion height H of the part to be maintained is larger than the standard protrusion height H0, determining the part to be maintained of the part to be maintained as a second part to be maintained and determining the defect of the second part to be maintained as protrusion, determining the maintenance mode as cutting and selecting the maintenance tool of the robot as a cutting knife;
When the crack width W of the part to be maintained is larger than the standard crack width W0, determining the part to be maintained of the part to be maintained as a third part to be maintained and determining the defect of the third part to be maintained as cracking, determining the maintenance mode as welding and selecting a maintenance tool of the robot as a welding gun.
Specifically, the standard concave depth D0 set by the standard simulation model preset in this embodiment is 5mm, the standard convex height H0 is 5mm, and the standard slit width W0 is 2 mm.
The defects of the parts to be maintained are determined according to the difference between the preset standard simulation model and the real-time simulation model, so that real-time analysis based on the three-dimensional simulation model is realized; the real-time analysis based on the three-dimensional simulation model is realized to obtain an analysis result by determining a maintenance mode according to the defects of the part to be maintained and selecting a maintenance tool of the robot according to the defects, so that the timeliness and the reliability of the analysis are improved; the defects of the part to be maintained are determined to be concave according to the concave depth of the surface of the part to be maintained, the maintenance mode is determined to be reverse knocking, and the maintenance tool of the robot is selected as a hammer, so that analysis, identification and maintenance of the concave defects are realized; the defects of the parts to be maintained are determined to be bulges according to the bulge heights of the surfaces of the parts to be maintained, the maintenance mode is determined to be cutting, and the maintenance tool of the robot is selected as a cutting knife, so that the analysis, identification and maintenance of the bulge defects are realized; the analysis, identification and maintenance of the cracking defects are realized by determining the defects of the to-be-maintained parts as cracking according to the crack width of the to-be-maintained parts, determining the maintenance mode as welding and selecting the maintenance tool of the robot as a welding gun.
Specifically, determining a defect level and repairing the defect in real time with a repair parameter determined by the defect level includes:
the conditions for determining the dent level are:
the surface pit depth D epsilon [ D0, 2X D0] is a first pit level, and the surface pit depth D epsilon (2X D0, ++ infinity) is a second pit level;
the first depression maintenance parameter determined by the first depression level is that the knocking force of the hammer is standard knocking force F0 and the knocking speed of the hammer is standard knocking speed Vf0, and the second depression maintenance parameter determined by the second depression level is that the knocking force of the hammer is maximum knocking force Fm and the knocking speed of the hammer is maximum knocking speed Vfm, wherein Fm=2×F0, F0 is preset standard knocking force, vfm=2×Vf0, and Vf0 is preset standard knocking speed;
specifically, the standard tap force F0 set in advance in the present embodiment is 2.5N, and the standard tap speed Vf0 set in advance is 2 times/s.
The conditions for determining the bump level are:
the surface protrusion height H epsilon [ H0, 2X H0] is a first protrusion level, and the surface protrusion height H epsilon (2X H0, ++ infinity) is a second protrusion level;
the first bulge maintenance parameter determined by the first bulge grade is that the cutting force of the cutting knife is standard cutting force Q0 and the cutting speed of the cutting knife is standard cutting speed Vq0, the second bulge maintenance parameter determined by the second bulge grade is that the cutting force of the cutting knife is maximum cutting force Qm and the cutting speed of the cutting knife is maximum cutting speed Vqm, wherein qm=2×Q0, Q0 is preset standard cutting force, vqm =2×Vq0 and Vq0 is preset standard cutting speed;
Specifically, the standard cutting force Q0 set in advance in the present embodiment is 10N, and the standard cutting speed Vq0 set in advance is 0.1m/s.
The conditions for determining the welding grade are:
the crack width W epsilon [ W0,2 XW 0] is a first welding grade, and the crack width W epsilon (2 XW 0, ++ infinity) is a second welding grade;
the first welding maintenance parameter determined by the first welding grade is that the welding strength of the welding gun is standard welding strength H0 and the welding speed of the welding gun is standard welding speed Vh0, the second welding maintenance parameter determined by the second welding grade is that the welding strength of the welding gun is maximum welding strength Hm and the welding speed of the welding gun is maximum welding speed Vhm, wherein Hm=2×H2 0, H0 is preset standard welding strength, vhm =2×Vh0 and Vh0 is preset standard welding speed;
specifically, the standard welding strength H0 preset in the present embodiment is 5N/mm 2 The preset standard welding speed Vh0 is 4mm 2 /s。
When the defect grade is determined to be a first concave grade, the first part to be repaired is repaired in real time by the first concave repair parameter; when the defect grade is determined to be the second concave grade, the first part to be repaired is repaired in real time by the second concave repair parameter;
When the defect level is determined to be the first bulge level, the first bulge maintenance parameter is used for carrying out real-time maintenance on the second part to be maintained; when the defect grade is determined to be the second bulge grade, the second bulge maintenance parameter is used for carrying out real-time maintenance on the second part to be maintained;
when the defect grade is determined to be the first welding grade, the third part to be repaired is repaired in real time by the first welding repair parameter; and when the defect grade is determined to be the second welding grade, performing real-time maintenance on the third part to be maintained by the second welding maintenance parameter.
The knocking acting force and the knocking speed of the hammer are specifically determined by determining the depression grade according to the depression depth and further determining the maintenance parameters, so that the maintenance accuracy of the hammer on the depression part is improved; the method has the advantages that the projection grade is determined according to the height of the projection, the maintenance parameters are further determined, the cutting acting force and the cutting speed of the cutting knife are particularly determined, and the maintenance accuracy of the cutting knife on the projection part is improved; the welding strength and the welding speed of the welding gun are specifically determined by determining the cracking grade and further determining the maintenance parameters according to the width of the crack, so that the maintenance accuracy of the welding gun on the crack part is improved.
Specifically, updating the real-time simulation model during the repair process includes: the three-dimensional space data is time sequence data, the three-dimensional space data at the i moment is recorded as (xi, yi, zi), the three-dimensional space data at the i-1 moment is recorded as (x (i-1), y (i-1), z (i-1)), the three-dimensional space data at the i moment is compared with the three-dimensional space data at the i-1 moment, and when (xi, yi, zi) is not equal to (x (i-1), y (i-1), z (i-1)), the three-dimensional space data of the part to be maintained is judged to be changed, and the real-time simulation model is updated according to the three-dimensional space data at the i moment to obtain the updated real-time simulation model.
By updating the real-time simulation model in the maintenance process, the data update of constructing the real-time simulation model based on the real-time three-dimensional space data is realized, and the instantaneity of analysis of the simulation model is ensured.
Specifically, adjusting maintenance parameters based on differences between the updated real-time simulation model and the standard simulation model includes:
when the difference between the updated real-time simulation model and the standard simulation model is the updated surface concave depth Dg epsilon [ D0,2 xD 0], the maintenance parameter is adjusted to be a first concave maintenance parameter; when the difference between the updated real-time simulation model and the standard simulation model is the updated surface concave depth Dg epsilon (2X D0, ++ infinity), the maintenance parameter is adjusted to be a second concave maintenance parameter;
When the difference between the updated real-time simulation model and the standard simulation model is the updated surface protrusion height Hg epsilon [ H0, 2X H0], the maintenance parameter is adjusted to be a first protrusion maintenance parameter; when the difference between the updated real-time simulation model and the standard simulation model is the updated surface protrusion height Hg (2X H0, ++ infinity), the maintenance parameters are adjusted to be second protrusion maintenance parameters;
when the difference between the updated real-time simulation model and the standard simulation model is the updated crack width Wg epsilon [ W0,2 XW 0], the maintenance parameter is adjusted to be a first welding maintenance parameter; and when the difference between the updated real-time simulation model and the standard simulation model is the updated crack width Wg epsilon (2 XW 0, ++ infinity), adjusting the maintenance parameter to be a second welding maintenance parameter.
By adjusting the maintenance parameters based on the difference between the updated real-time simulation model and the standard simulation model, the working state of the maintenance tool is adjusted in real time according to the analysis result, and the maintenance accuracy is improved.
Specifically, detecting the defect and calculating to obtain a defect index, determining a maintenance result according to the defect index, and determining that the maintenance tool is finished to be maintained or is continued to be maintained according to the maintenance result, wherein the method comprises the following steps:
When the defect is detected as a dent, a dent defect index γd=d/D0 is calculated; when the detected defect is a bulge, calculating a bulge defect index gamma h=H/H0; when the detected defect is cracking, calculating a cracking defect index gamma w=w/W0;
the conditions for determining that the maintenance result is qualified for maintenance are as follows: determining that the first part to be maintained is qualified when the concave defect index gamma d epsilon [0, gamma d0 ]; when the bulge defect index gamma h epsilon [0, gamma h0], determining that the second part to be maintained is qualified; when the cracking defect index gamma w epsilon [0, gamma w0], determining that the third part to be maintained is qualified in maintenance; wherein γd0 is a preset standard concave defect index, γh0 is a preset standard convex defect index, and γw0 is a preset standard cracking defect index;
the conditions for determining that the maintenance result is unqualified are as follows: determining that the first part to be maintained is unqualified when the concave defect index gamma d epsilon (gamma d0, ++ infinity); when the convex defect index gamma h epsilon (gamma h0, ++ infinity), determining that the maintenance of the second part to be maintained is unqualified; determining that the third part to be maintained is unqualified when the cracking defect index gamma w epsilon (gamma w0, ++ infinity);
when the maintenance result is that the maintenance is qualified, determining that the maintenance tool finishes maintenance; and when the maintenance result is that the maintenance is unqualified, determining that the maintenance tool continues to maintain.
Specifically, in this embodiment, when the maintenance result is that the maintenance is qualified, the maintenance result is fed back and the collected data is determined to be finished; and when the maintenance result is that the maintenance is unqualified, feeding back the maintenance result and determining to continuously collect data.
Specifically, the smaller the first to-be-repaired portion concave defect index γd, the second to-be-repaired portion convex defect index γh and the third to-be-repaired portion crack defect index γw are, the more perfect the repair is indicated, when the defect index is 0, the state of the repaired to-be-repaired component is not different from the standard simulation model, and in the embodiment, γd0, γh0 and γw0 respectively take values of 0.1.
The defect is detected, the defect index is obtained through calculation, the maintenance result is determined according to the defect index, the maintenance tool is determined to continue to maintain according to the maintenance result, and the three-dimensional space data is determined to continue to be collected, so that the closed-loop control of the maintenance motion of the robot is realized, and the accuracy and the integrity of the maintenance of the robot are improved.
Specifically, the method includes the steps of calculating a maintenance evaluation value according to a preset maintenance result evaluation model, comparing the evaluation value with a preset standard evaluation value to obtain a comparison result, and determining an evaluation grade according to the comparison result, wherein the method comprises the following steps:
Calculating to obtain a maintenance evaluation value P= (γd multiplied by β1+γh multiplied by β2+γw multiplied by β3) multiplied by 100/(β1+β2+β3) according to a preset maintenance result evaluation model, wherein P is the evaluation value of maintenance of the part to be maintained by the robot, β1 is the maintenance weight of the first part to be maintained, β2 is the maintenance weight of the second part to be maintained, and β3 is the maintenance weight of the third part to be maintained;
specifically, the repair weights determined by different parts to be repaired for different defects are different, in this embodiment, the repair weight β1 of the first part to be repaired is 30%, the repair weight β2 of the second part to be repaired is 30%, and the repair weight β3 of the third part to be repaired is 40%.
The conditions for determining the evaluation level are: p epsilon [0, P0] is first-level maintenance, P epsilon (P0, 2 x P0) is second-level maintenance, P epsilon (2 x P0, ++ infinity) is third-level maintenance, wherein P0 is a preset standard evaluation value.
Specifically, the standard evaluation value P0 preset in the present embodiment takes a value of 4.
The maintenance evaluation value is obtained through calculation, the evaluation value is compared with a preset standard evaluation value to obtain a comparison result, and an evaluation grade is determined according to the comparison result, so that the maintenance quality of the part to be maintained of the robot is improved; by setting different maintenance weights, the importance degree of local maintenance in overall maintenance can be flexibly adjusted.
Specifically, S022 includes: performing primary division and secondary division on three-dimensional space data of a part to be maintained, wherein the primary division is used for dividing the three-dimensional space data of the part to be maintained into a plurality of first three-dimensional shape finite element grid data, the first three-dimensional shape finite element grid data comprises first standard three-dimensional shape finite element grid data and first non-standard three-dimensional shape finite element grid data,
the X-direction differential value delta X1 = Xi-X (i-1), the Y-direction differential value delta y1 = Yi-Y (i-1), the Z-direction differential value delta z1 = Zi-Z (i-1), wherein Xi is the X-direction value of the ith point in a standard coordinate system, X (i-1) is the X-direction value of the ith point in the standard coordinate system, yi is the Y-direction value of the ith point in the standard coordinate system, Y (i-1) is the Y-direction value of the ith point in the standard coordinate system, zi is the Z-direction value of the ith point in the standard coordinate system, and Z (i-1) is the Z-direction value of the ith point in the standard coordinate system;
when Δx1=Δx0 and Δy1=Δy0 and Δz1=Δz0, the first three-dimensional shape finite element mesh data is first standard three-dimensional shape finite element mesh data, wherein Δx0 is a preset X-direction standard deviation value and Δy0 is a preset Y-direction standard deviation value; Δz0 is a preset Z-direction standard deviation value;
When Δx1 e [0, Δx0) or Δy1 e [0, Δy0) or Δz1 e [0, Δz0), the first three-dimensional shape finite element mesh data is first non-standard three-dimensional shape finite element mesh data;
specifically, Δx0, Δy0, and Δz0 in this embodiment each take a value of 3mm.
A second division for dividing the first non-standard three-dimensional shape finite element mesh data into a plurality of second three-dimensional shape finite element mesh data,
the X-direction differential value Δx2=α1×Δx1, the Y-direction differential value Δy2=α2×Δy1, and the Z-direction differential value Δz2=α3×Δz1 of the second three-dimensional shape finite element mesh data, wherein α1 is a first correction coefficient for correcting the X-direction differential value, α2 is a second correction coefficient for correcting the Y-direction differential value, and α3 is a third correction coefficient for correcting the Y-direction differential value.
Specifically, in the data dividing process, the smaller the differential values in the X direction, the Y direction and the Z direction are, the higher the accuracy of generating the three-dimensional simulation model is, and the longer the time of generating the three-dimensional simulation model through calculation is, but considering that the time of constructing the three-dimensional simulation model needs to meet the requirement of robot maintenance, the time of constructing the three-dimensional simulation model is not suitable to exceed the movement time of a part to be maintained by robot control maintenance, and the differential values of the data dividing are respectively in the optimal state in the standard differential value range. In this embodiment, α1, α2, and α3 each take a value of 0.33.
By carrying out primary division and secondary division on the three-dimensional space data of the part to be maintained, the accuracy of simulation data is improved, and the non-standard three-dimensional shape finite element grid data is more refined and higher in accuracy.
In another aspect, as shown in fig. 3, the present invention further provides a digital twin-based robot motion control and status monitoring system, which includes:
the data acquisition module 1 is used for acquiring three-dimensional space data of a part to be maintained through a three-dimensional vision sensor arranged on the face of the robot;
as shown in fig. 4, the digital twin module 2 is connected with the data acquisition module and comprises a simulation unit 201 and a comparison unit 202, wherein the simulation unit is used for constructing a real-time simulation model of a part to be maintained, and the comparison unit is used for determining defects of the part to be maintained according to the difference between a preset standard simulation model and the real-time simulation model, determining a maintenance mode according to the defects and selecting a maintenance tool of the robot;
as shown in fig. 5, the maintenance module 3 is connected with the digital twin module and comprises a maintenance unit 301, an updating unit 302 and an adjusting unit 303, wherein the maintenance unit is used for determining a defect grade and carrying out real-time maintenance on the defect with maintenance parameters determined by the defect grade, the updating unit is used for updating the real-time simulation model in the maintenance process, and the adjusting unit is used for adjusting the maintenance parameters based on the difference between the updated real-time simulation model and the standard simulation model;
As shown in fig. 6, the detection module 4 is connected with the maintenance module and comprises a detection unit 401 and a determination unit 402, wherein the detection unit is used for detecting defects and calculating to obtain defect indexes, and the determination unit is used for determining maintenance results according to the defect indexes and determining that the maintenance tool is finished or continues maintenance according to the maintenance results;
as shown in fig. 7, the evaluation module 5 is connected to the detection module and includes a calculation unit 501 and an evaluation unit 502, where the calculation unit is configured to calculate and obtain an evaluation value for maintenance, and the evaluation unit is configured to compare the evaluation value with a preset standard evaluation value to obtain a comparison result, and determine an evaluation level according to the comparison result.
Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.
The foregoing description is only of the preferred embodiments of the invention and is not intended to limit the invention; various modifications and variations of the present invention will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. The method for controlling the movement and monitoring the state of the robot based on digital twinning is characterized by comprising the following steps:
s01, collecting three-dimensional space data of a part to be maintained;
s02, constructing a real-time simulation model of the part to be maintained, determining defects of the part to be maintained according to the difference between a preset standard simulation model and the real-time simulation model, determining a maintenance mode according to the defects, and selecting a maintenance tool of the robot;
s03, determining a defect grade and repairing the defect in real time according to the repairing parameters determined by the defect grade,
updating the real-time simulation model during maintenance,
and adjusting the maintenance parameters based on differences between the updated real-time simulation model and the standard simulation model;
s04, detecting the defects and calculating to obtain defect indexes, determining maintenance results according to the defect indexes, and determining that the maintenance tool is finished to be maintained or to continue to be maintained according to the maintenance results;
s05, calculating to obtain a maintenance evaluation value, comparing the evaluation value with a preset standard evaluation value to obtain a comparison result, and determining an evaluation grade according to the comparison result;
Calculating according to a preset maintenance result evaluation model to obtain a maintenance evaluation value P= (γd multiplied by β1+γh multiplied by β2+γw multiplied by β3) multiplied by 100/(β1+β2+β3), wherein P is the evaluation value of the robot for maintaining the part to be maintained, β1 is the maintenance weight of a first part to be maintained, β2 is the maintenance weight of a second part to be maintained, β3 is the maintenance weight of a third part to be maintained, γd is a concave defect index, γh is a convex defect index, and γw is a cracking defect index; wherein, the dent defect index γd=d/d0, D is the surface dent depth of the part to be maintained, D0 is the standard dent depth, the protrusion defect index γh=h/H0, H is the surface protrusion height of the part to be maintained, H0 is the standard protrusion height, the cracking defect index γw=w/W0, W is the crack width of the part to be maintained, and W0 is the standard crack width;
the conditions for determining the evaluation level are: p epsilon [0, P0] is first-level maintenance, P epsilon (P0, 2 x P0) is second-level maintenance, P epsilon (2 x P0, ++ infinity) is third-level maintenance, wherein P0 is a preset standard evaluation value;
wherein, the step S02 of constructing a real-time simulation model of the component to be maintained comprises the following steps:
S021, establishing a three-dimensional space standard coordinate system and determining the three-dimensional space data as international unit system data under the standard coordinate system;
s022, carrying out data processing on the three-dimensional space data and obtaining a plurality of finite element grid data of the part to be maintained;
s023, generating a real-time simulation model of the part to be maintained under the three-dimensional space standard coordinate system according to the finite element grid data.
2. The method for controlling and monitoring the motion of a robot based on digital twinning according to claim 1, wherein the step S02 of determining the defect of the part to be repaired according to the difference between the preset standard simulation model and the real-time simulation model, determining the repair mode according to the defect, and selecting the repair tool of the robot comprises:
when the surface depression depth D of the part to be maintained is larger than the standard depression depth D0, determining a part to be maintained of the part to be maintained as a first part to be maintained, determining a defect of the first part to be maintained as a depression, determining a maintenance mode as reverse knocking, and selecting a maintenance tool of a robot as a hammer;
when the surface protrusion height H of the part to be maintained is larger than the standard protrusion height H0, determining the part to be maintained of the part to be maintained as a second part to be maintained and determining the defect of the second part to be maintained as a protrusion, determining the maintenance mode as cutting and selecting a maintenance tool of a robot as a cutting knife;
When the crack width W of the part to be maintained is larger than the standard crack width W0, determining the part to be maintained of the part to be maintained as a third part to be maintained and determining the defect of the third part to be maintained as cracking, determining the maintenance mode as welding and selecting a maintenance tool of a robot as a welding gun.
3. The digital twinning-based robot motion control and status monitoring method of claim 2, wherein determining a defect level and repairing the defect in real time with a repair parameter determined by the defect level comprises:
the conditions for determining the dent level are:
the surface pit depth D epsilon [ D0, 2X D0] is a first pit level, and the surface pit depth D epsilon (2X D0, ++ infinity) is a second pit level;
the first concave maintenance parameter determined by the first concave grade is that the knocking acting force of the hammer is standard knocking acting force F0 and the knocking speed of the hammer is standard knocking speed Vf0, the second concave maintenance parameter determined by the second concave grade is that the knocking acting force of the hammer is maximum knocking acting force Fm and the knocking speed of the hammer is maximum knocking speed Vfm, wherein Fm=2×F0, F0 is preset standard knocking acting force, vfm=2×vf0, and Vf0 is preset standard knocking speed;
The conditions for determining the bump level are:
the surface protrusion height H epsilon [ H0, 2X H0] is a first protrusion level, and the surface protrusion height H epsilon (2X H0, ++ infinity) is a second protrusion level;
the first bulge maintenance parameter determined by the first bulge level is that the cutting acting force of the cutting knife is standard cutting acting force Q0 and the cutting speed of the cutting knife is standard cutting speed Vq0, the second bulge maintenance parameter determined by the second bulge level is that the cutting acting force of the cutting knife is maximum cutting acting force Qm and the cutting speed of the cutting knife is maximum cutting speed Vqm, wherein qm=2×Q0, Q0 is preset standard cutting acting force, vqm =2×Vq0 and Vq0 is preset standard cutting speed;
the conditions for determining the welding grade are:
the crack width W epsilon [ W0,2 XW 0] is a first welding grade, and the crack width W epsilon (2 XW 0, ++ infinity) is a second welding grade;
the first welding maintenance parameter determined by the first welding grade is that the welding strength of the welding gun is standard welding strength H0 and the welding speed of the welding gun is standard welding speed Vh0, the second welding maintenance parameter determined by the second welding grade is that the welding strength of the welding gun is maximum welding strength Hm and the welding speed of the welding gun is maximum welding speed Vhm, wherein Hm=2×H2H0, H0 is preset standard welding strength, vhm =2×Vh0 and Vh0 is preset standard welding speed;
When the defect grade is determined to be a first concave grade, the first part to be repaired is repaired in real time by the first concave repair parameter; when the defect grade is determined to be a second concave grade, the first part to be repaired is repaired in real time by the second concave repair parameter;
when the defect grade is determined to be a first bulge grade, the first bulge maintenance parameter is used for carrying out real-time maintenance on the second part to be maintained; when the defect grade is determined to be a second bulge grade, the second bulge maintenance parameter is used for carrying out real-time maintenance on the second part to be maintained;
when the defect grade is determined to be a first welding grade, the first welding maintenance parameter is used for carrying out real-time maintenance on the third part to be maintained; and when the defect grade is determined to be a second welding grade, the third part to be repaired is repaired in real time by the second welding repair parameter.
4. A method of digital twinning-based robotic motion control and status monitoring according to claim 3, wherein updating the real-time simulation model during maintenance comprises: the three-dimensional space data are time sequence data, the three-dimensional space data at the i moment are recorded as (xi, yi, zi), the three-dimensional space data at the i-1 moment are recorded as (x (i-1), y (i-1), z (i-1)), the three-dimensional space data at the i moment are compared with the three-dimensional space data at the i-1 moment, and when (xi, yi, zi) is not equal to (x (i-1), y (i-1) and z (i-1)), the three-dimensional space data of the part to be maintained are judged to be changed, and the real-time simulation model is updated according to the three-dimensional space data at the i moment to obtain an updated real-time simulation model.
5. The method of claim 4, wherein adjusting the maintenance parameters based on differences between the updated real-time simulation model and the standard simulation model comprises:
when the difference between the updated real-time simulation model and the standard simulation model is the updated surface depression depth Dg epsilon [ D0, 2X D0], the maintenance parameter is adjusted to be a first depression maintenance parameter; when the difference between the updated real-time simulation model and the standard simulation model is the updated surface concave depth Dg epsilon (2X D0, ++ infinity), the maintenance parameter is adjusted to be a second concave maintenance parameter;
when the difference between the updated real-time simulation model and the standard simulation model is the updated surface protrusion height Hg epsilon [ H0, 2X H0], the maintenance parameter is adjusted to be a first protrusion maintenance parameter; when the difference between the updated real-time simulation model and the standard simulation model is the updated surface protrusion height Hg epsilon (2X H0, ++ infinity), the maintenance parameter is adjusted to be a second protrusion maintenance parameter;
when the difference between the updated real-time simulation model and the standard simulation model is updated crack width Wg epsilon [ W0, 2X W0], adjusting the maintenance parameter to be a first welding maintenance parameter; and when the difference between the updated real-time simulation model and the standard simulation model is the updated crack width Wg epsilon (2 XW 0, ++ infinity), adjusting the maintenance parameter to be a second welding maintenance parameter.
6. The method of claim 5, wherein detecting the defect and calculating a defect index, determining a repair result based on the defect index, and determining that the repair tool is finished or continues to repair based on the repair result comprises:
when the defect is detected to be a pit, a pit defect index γd=d/D0 is calculated; when the defect is detected to be a bulge, calculating a bulge defect index gamma h=H/H0; when the defect is detected to be cracking, calculating a cracking defect index gamma w=W/W0;
the conditions for determining that the maintenance result is qualified for maintenance are as follows: determining that the first part to be maintained is qualified in maintenance when the concave defect index gamma d epsilon [0, gamma d0 ]; when the convex defect indexes gamma h epsilon [0, gamma h0], determining that the second part to be maintained is qualified in maintenance; when the cracking defect index gamma w epsilon [0, gamma w0] is determined that the third part to be maintained is qualified; wherein γd0 is a preset standard concave defect index, γh0 is a preset standard convex defect index, and γw0 is a preset standard cracking defect index;
the conditions for determining that the maintenance result is unqualified are as follows: determining that the first part to be maintained is unqualified when the concave defect index gamma d epsilon (gamma d0, ++ infinity); when the convex defect index gamma h epsilon (gamma h0, ++ infinity), determining that the maintenance of the second part to be maintained is unqualified; determining that the third part to be maintained is unqualified when the cracking defect index gamma w epsilon (gamma w0, ++ infinity);
When the maintenance result is that the maintenance is qualified, determining that the maintenance tool finishes maintenance; and when the maintenance result is that the maintenance is not qualified, determining that the maintenance tool continues to maintain.
7. The method for controlling and monitoring the motion of a robot based on digital twinning according to claim 1, wherein S022 comprises: performing primary division and secondary division on the three-dimensional space data of the part to be maintained, wherein the primary division is used for dividing the three-dimensional space data of the part to be maintained into a plurality of first three-dimensional shape finite element grid data, the first three-dimensional shape finite element grid data comprises first standard three-dimensional shape finite element grid data and first non-standard three-dimensional shape finite element grid data,
the X-direction differential value delta X1 = Xi-X (i-1), the Y-direction differential value delta y1 = Yi-Y (i-1), the Z-direction differential value delta z1 = Zi-Z (i-1), wherein Xi is the ith point X direction value under the standard coordinate system, X (i-1) is the ith point X direction value under the standard coordinate system, yi is the ith point Y direction value under the standard coordinate system, Y (i-1) is the ith point Y direction value under the standard coordinate system, zi is the ith point Z direction value under the standard coordinate system, Z (i-1) is the ith point Z direction value under the standard coordinate system;
When Δx1=Δx0 and Δy1=Δy0 and Δz1=Δz0, the first three-dimensional shape finite element mesh data is first standard three-dimensional shape finite element mesh data, where Δx0 is a preset X-direction standard deviation value and Δy0 is a preset Y-direction standard deviation value; Δz0 is a preset Z-direction standard deviation value;
when Δx1 e [0, Δx0) or Δy1 e [0, Δy0) or Δz1 e [0, Δz0), the first three-dimensional shape finite element mesh data is first non-standard three-dimensional shape finite element mesh data;
the secondary division is used for dividing the first non-standard three-dimensional shape finite element mesh data into a plurality of second three-dimensional shape finite element mesh data,
the X-direction differential value Δx2=α1×Δx1, the Y-direction differential value Δy2=α2×Δy1, and the Z-direction differential value Δz2=α3×Δz1 of the second three-dimensional finite element mesh data, wherein α1 is a first correction coefficient for correcting the X-direction differential value, α2 is a second correction coefficient for correcting the Y-direction differential value, and α3 is a third correction coefficient for correcting the Y-direction differential value.
8. A system for use in a digital twinning-based robot motion control and condition monitoring method according to claim 1, comprising:
The data acquisition module is used for acquiring three-dimensional space data of the part to be maintained through a three-dimensional vision sensor arranged on the face of the robot;
the digital twin module is connected with the data acquisition module and comprises a simulation unit and a comparison unit, wherein the simulation unit is used for constructing a real-time simulation model of the part to be maintained, and the comparison unit is used for determining defects of the part to be maintained according to the difference between a preset standard simulation model and the real-time simulation model, determining a maintenance mode according to the defects and selecting a maintenance tool of the robot;
the maintenance module is connected with the digital twin module and comprises a maintenance unit, an updating unit and an adjusting unit, wherein the maintenance unit is used for determining a defect grade and maintaining the defect in real time according to maintenance parameters determined by the defect grade, the updating unit is used for updating the real-time simulation model in the maintenance process, and the adjusting unit is used for adjusting the maintenance parameters based on the difference between the updated real-time simulation model and the standard simulation model;
the detection module is connected with the maintenance module and comprises a detection unit and a determination unit, wherein the detection unit is used for detecting the defects and calculating to obtain defect indexes, and the determination unit is used for determining maintenance results according to the defect indexes and determining that the maintenance tool is finished to be maintained or to continue to be maintained according to the maintenance results;
The evaluation module is connected with the detection module and comprises a calculation unit and an evaluation unit, wherein the calculation unit is used for calculating and obtaining a maintenance evaluation value, and the evaluation unit is used for comparing the evaluation value with a preset standard evaluation value to obtain a comparison result and determining an evaluation grade according to the comparison result.
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CN116805311A (en) * | 2023-08-18 | 2023-09-26 | 长春师范大学 | Automobile part surface defect monitoring method based on robot vision |
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CN112765768A (en) * | 2020-12-22 | 2021-05-07 | 天津博诺智创机器人技术有限公司 | Discrete workshop digital traceability method based on Internet of things |
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