WO2020062232A1 - Procédé, dispositif et système de traitement de données, support d'informations et processeur - Google Patents

Procédé, dispositif et système de traitement de données, support d'informations et processeur Download PDF

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WO2020062232A1
WO2020062232A1 PCT/CN2018/109071 CN2018109071W WO2020062232A1 WO 2020062232 A1 WO2020062232 A1 WO 2020062232A1 CN 2018109071 W CN2018109071 W CN 2018109071W WO 2020062232 A1 WO2020062232 A1 WO 2020062232A1
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source object
modeled
data
source
geometric
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PCT/CN2018/109071
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English (en)
Chinese (zh)
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沈轶轩
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西门子股份公司
沈轶轩
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Priority to CN201880096104.3A priority Critical patent/CN112513860A/zh
Priority to PCT/CN2018/109071 priority patent/WO2020062232A1/fr
Publication of WO2020062232A1 publication Critical patent/WO2020062232A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects

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  • This application relates to the field of industrial production simulation. Specifically, the present application relates to a data processing method, device, system, storage medium, processor, and computer program product for rapid modeling of mathematical models in plant simulation.
  • kinematics and mathematical simulations can be performed on equipment and / or workpieces in a plant to obtain kinematics models and mathematical models that are independent of each other.
  • the derivation of the kinematics model is based on the kinematics constraints.
  • the kinematics constraints are added to the production line model to detect the movement speed of the workpiece, the cooperation and interference between the workstations, and the time series or event triggering as the derivation mechanism.
  • the parameters are inputs.
  • the mathematical model uses mathematical formulas as the basis for derivation, output, energy consumption, etc. as outputs.
  • the mathematical model also uses time series or event triggers as the derivation mechanism, and the parameters of the production line as inputs.
  • a data processing method including: obtaining geometric data and statistical data of a source object from a kinematics model of the source object according to a relationship between the object to be modeled and the source object; The relationship between the modeling object and the source object is to convert the obtained geometric data and statistical data of the source object into geometric data and statistical data for mathematical modeling of the object to be modeled.
  • the method further includes: inputting a relationship between the object to be modeled and the source object.
  • the user can flexibly manage the relationship between the object to be modeled and the source object according to the actual needs.
  • the data processing method further includes at least one of the following steps: using the transformed geometric data to perform three-dimensional mathematical modeling of the object to be modeled to obtain a three-dimensional mathematical model of the object to be modeled, and using the converted statistical data
  • the two-dimensional mathematical modeling of the object to be modeled is performed to obtain the two-dimensional mathematical model of the object to be modeled.
  • the source object includes at least one of one or more devices in a factory and one or more workpieces processed by the one or more devices in the factory.
  • the relationship between the object to be modeled and the source object includes: the object to be modeled and the source object are the same object; the object to be modeled is a combination of source objects; the object to be modeled and the source object are related to each other in the production process; The location of the modeled object in the plant is correlated with the location of the source object in the plant.
  • the geometric data of the source object includes at least one of the following: Geometric model; orientation information of the source object in the factory; location information of the source object in the factory, and the statistics of the source object include at least one of the following: the name of the source object; the type of the source object; Translation speed; rotation speed of the source object; length of the source object; processing duration of the workpiece currently being processed by the source object; waiting duration of the source object waiting for processing of the workpiece.
  • the geometric data of the source object includes the following items At least one of: the geometric model of the source object; the orientation information of the source object in the factory; the location information of the source object in the factory, and the statistics of the source object include at least one of the following: the name of the source object The type of the source object; the translation speed of the source object; the duration of the movement of the source object; the speed of rotation of the source object; the length of the source object; the duration of the source object currently being processed; the source object's waiting to be processed Wait for processing duration.
  • the data of the kinematics model of the source object can be automatically converted, thereby achieving rapid modeling of the mathematical model.
  • the step of converting the acquired geometric data and statistical data of the source object into the geometric data and statistical data of the object to be modeled includes:
  • the step of converting data and statistical data into geometric data and statistical data for mathematical modeling of the object to be modeled includes: when the object to be modeled and the source object are the same object, the acquired geometric data and statistical data of the source object As geometric data and statistical data for mathematical modeling of the object to be modeled; when the object to be modeled is a combination of source objects, the obtained geometric data and statistical data of all the source objects are used as the object to be modeled
  • the geometric data and statistical data for mathematical modeling when the object to be modeled and the source object are related to each other in the production process, according to the production process-based conversion relationship between the geometric data of the object to be modeled and the geometric data of the source object, The obtained geometric data of the source object is converted into geometric data for mathematical modeling of the object to be modeled, and The conversion relationship between the statistical data of the model object and the statistical
  • the obtained statistical data of the source object is converted into statistical data for mathematical modeling of the object to be modeled.
  • the obtained geometric data of the source object is converted into the geometric data of the object to be modeled and the geometric data of the source object based on the position in the factory.
  • Geometric data used for mathematical modeling of the object to be modeled, and according to the conversion relationship between the statistical data of the object to be modeled and the statistical data of the source object based on the location in the factory the obtained statistical data of the source object is converted into Statistics for mathematical modeling of the object being modeled.
  • the data of the kinematics model of the source object can be automatically converted, thereby achieving rapid modeling of the mathematical model.
  • a data processing device including: an obtaining unit, configured to obtain geometric data of a source object from a kinematics model of the source object according to a relationship between the object to be modeled and the source object; And statistical data; a conversion unit for converting the geometric data and statistical data of the source object obtained by the obtaining unit into a geometry for mathematical modeling of the object to be modeled according to the relationship between the object to be modeled and the source object Data and statistics.
  • the data processing device further includes: an input unit for inputting a relationship between the object to be modeled and the source object.
  • the modeling device further includes at least one of the following units: a three-dimensional modeling unit, configured to obtain the three-dimensional mathematics of the object to be modeled by using the acquired geometric data to obtain the three-dimensional mathematical model of the object to be modeled Model; a two-dimensional modeling unit, configured to obtain the two-dimensional mathematical model of the object to be modeled by using the converted statistical data to obtain and perform two-dimensional mathematical modeling of the object to be modeled.
  • a three-dimensional modeling unit configured to obtain the three-dimensional mathematics of the object to be modeled by using the acquired geometric data to obtain the three-dimensional mathematical model of the object to be modeled Model
  • a two-dimensional modeling unit configured to obtain the two-dimensional mathematical model of the object to be modeled by using the converted statistical data to obtain and perform two-dimensional mathematical modeling of the object to be modeled.
  • the source object includes at least one of one or more devices in the factory and one or more workpieces processed by the one or more devices in the factory.
  • the relationship between the object to be modeled and the source object is the same object; the object to be modeled is a combination of source objects; the object to be modeled and the source object are related to each other in the production process; the location of the object to be modeled in the factory Associated with the location of the source object in the plant.
  • the geometric data of the source object includes at least one of the following: a geometric model of the source object; a source object in the factory Orientation information; location information of the source object in the factory, and the statistics of the source object include at least one of the following: the name of the source object; the type of the source object; the translation speed of the source object; the rotation speed of the source object; The length of the source object; the processing duration of the workpiece currently being processed by the source object; the waiting duration of the source object waiting to process the workpiece.
  • the geometric data of the source object includes at least one of the following: Geometric model; orientation information of the source object in the factory; location information of the source object in the factory, and the statistics of the source object include at least one of the following: the name of the source object; the type of the source object; Translation speed; movement duration of the source object; rotation speed of the source object; length of the source object; processing duration of the source object currently being processed; duration of the source object waiting to be processed and waiting to be processed.
  • the conversion unit is configured to: when the object to be modeled and the source object are the same object, use the acquired geometric data and statistical data of the source object as the geometry for mathematically modeling the object to be modeled Data and statistical data; when the object to be modeled is a combination of source objects, all the acquired geometric data and statistical data of the source object are used as geometric data and statistical data for mathematical modeling of the object to be modeled; When the modeling object and the source object are related to each other in the production process, the obtained geometric data of the source object is converted to be used for construction according to the production process-based conversion relationship between the geometric data of the object to be modeled and the geometric data of the source object.
  • a data processing system including: a kinematics model simulator for obtaining a kinematics model of a source object; and an obtaining unit for obtaining the data between the object to be modeled and the source object.
  • Relationship to obtain the geometric data and statistical data of the source object from the kinematics model of the source object of the kinematic model simulator; the conversion unit is used to obtain the data obtained by the acquisition unit according to the relationship between the object to be modeled and the source object The geometric data and statistical data of the source object are converted into geometric data and statistical data used for mathematical modeling of the object to be modeled; a mathematical model simulator is used to use the geometric data transformed by the transformation unit to perform three-dimensional mathematics of the object to be modeled Modeling to obtain a three-dimensional mathematical model of the object to be modeled, and using statistical data transformed by the conversion unit to perform two-dimensional mathematical modeling of the object to be modeled to obtain a two-dimensional mathematical model of the object to be modeled.
  • a storage medium stores a program, and the method according to any one of the foregoing is executed when the program is run.
  • a processor which is coupled to the memory, and is characterized in that the memory stores a program, and the processor executes the method according to any one of the above when the program runs the program.
  • a computer program product is also provided.
  • the computer program product is stored on a computer-readable medium and includes computer-executable instructions.
  • the at least one processor executes the instructions according to the foregoing. Either method.
  • the method according to the embodiment of the present application may be implemented by a program in a storage medium and a processor, thereby determining an accurate required production equipment path.
  • a mathematical model can be easily constructed using information obtained from a kinematic model. This greatly reduces the time required to model in a mathematical model. Therefore, it is very easy and meaningful to build a "bridge" between a kinematics simulator (machining simulation) and a mathematical simulator (factory simulation). This means that, if the operator already has a machining simulation model, he can easily build a plant simulation model.
  • FIG. 1 is a schematic diagram showing a relationship between a kinematics model of an object and data related to its mathematical model according to an embodiment of the present application;
  • FIG. 2 is a schematic diagram showing a relationship between a kinematics model and a mathematical model of a robot according to an embodiment of the present application;
  • FIG. 3 is a flowchart of a data processing method according to an embodiment of the present application.
  • FIG. 4 is a flowchart of a conversion step in a data processing method according to an embodiment of the present application.
  • FIG. 5 is a block diagram of a data processing apparatus according to an embodiment of the present application.
  • FIG. 6 is a schematic diagram of a file structure of an information acquisition module of a data processing device according to an embodiment of the present application
  • FIG. 7 is a block diagram of a data processing system according to an embodiment of the present application.
  • FIG. 8 is a block diagram of a three-dimensional mathematical model and a two-dimensional mathematical model of a kinematic model, a mathematical model, and a mathematical model according to an embodiment of the present application;
  • FIG. 9 is a block diagram of a plant-level simulation according to an embodiment of the present application.
  • Geometric model processing time, waiting time in the mathematical model of the 204-2 robot
  • the acquired geometric data and statistical data of the source object are converted into geometric data and statistical data of the object to be modeled.
  • S308 uses the transformed geometric data to perform 3D mathematical modeling of the object to be modeled to obtain a 3D mathematical model of the object to be modeled.
  • S310 uses the converted statistical data to perform two-dimensional mathematical modeling of the object to be modeled to obtain a two-dimensional mathematical model of the object to be modeled.
  • S402 determines the relationship between the object to be modeled and the source object input in step S302 of FIG. 3
  • S408 convert the acquired geometric data and statistical data of the source object into geometric data and statistical data of the object to be modeled
  • S410 Convert the obtained geometric data of the source object into the geometric data of the object to be modeled according to the conversion relationship based on the position in the factory of the geometric data of the object to be modeled and the geometric data of the source object, and according to the object to be modeled, and The conversion relationship between the statistical data of the source object and the statistical data of the source object based on the location in the factory, and the obtained statistical data of the source object is converted into the statistical data of the object to be modeled
  • FIG. 1 is a schematic diagram showing a relationship between a kinematics model of an object and data related to its mathematical model according to an embodiment of the present application.
  • the object may be equipment in a factory (for example, a robotic arm, a conveyor belt) or a workpiece in a factory (for example, a workpiece being processed on a conveyor belt).
  • a factory for example, a robotic arm, a conveyor belt
  • a workpiece in a factory for example, a workpiece being processed on a conveyor belt.
  • a region 104 represents the same type of data related to the kinematics model and mathematical model of the object, for example, a geometric model representing a robotic arm (for example, a model of a robotic arm in a three-dimensional space represented in CAD format), a representation Equipment parameters of the conveyor belt (for example, the length and speed of the conveyor belt), the processing duration of the workpiece currently being processed, and the like.
  • Region 102 represents data that is involved in the kinematics model but not in the mathematical model, such as the movement trajectory of the object. Specifically, it can be a kinematic constraint, a motion pair, a motion speed, and a degree of freedom of the robotic arm.
  • Region 106 represents data related to the mathematical model but not to the kinematics model, for example, the number of workpieces processed by the robot arm in a unit time, the energy consumption of the robot arm, and the like.
  • the information from the kinematic model (which is in a process simulation) is usually redundant for the mathematical model (which is in a plant simulation).
  • the following content uses a robot arm as an example to explain machining simulation and factory simulation.
  • the kinematics model of the manipulator in machining simulation is generated by kinematics modeling of the manipulator that produces displacement.
  • the kinematics model of a mechanical arm in machining simulation refers to the same geometric structure and physics as the real robot arm created in a virtual space that simulates the real robot arm based on data related to the geometry and physical motion characteristics of the real robot arm.
  • Virtual model of a kinematic arm with kinematics The virtual model can run in the virtual space with the same physical and operational laws as the real robotic arm in the real space, and can simulate the structure, operating conditions and physical state of the real robotic arm in the real space in the virtual space.
  • the simulation may include generating a kinematic model of a plurality of robotic arms involved in the processing process to create a virtual environment in a virtual space consistent with a device spatial relationship in a real space.
  • collisions between the various kinematics models may occur (for example, the kinematics model of the first robotic arm is in the process of The kinematics model of the second robotic arm at the position collides), coordination (for example, the kinematics model of the first robotic arm at the first processing step and the kinematics model of the second robotic arm at the second processing step will be coordinated Work) and other events.
  • the modeling involved in this kinematics model in machining simulation is mainly used to examine the detailed design of the production line of interest.
  • the mathematical model of the robotic arm is a model obtained by mathematically modeling the robotic arm, and is a mathematical representation of the information related to the robotic arm through mathematical expressions.
  • the mathematical model may include a three-dimensional mathematical model in which a three-dimensional mathematical expression is expressed by a mathematical expression and a two-dimensional mathematical model in which a two-dimensional mathematical expression is expressed by a mathematical expression.
  • the mechanical arm is defined as a working unit, and the mathematical model also includes data such as input, derivation mechanism, and output.
  • the input is a mathematically expressed parameter of the robotic arm (for example, the device initialization time of the robotic arm), the derivation mechanism is a time series or trigger event expressed by a mathematical formula, and the output is the unit working time and energy consumption of the robotic arm Wait.
  • the mathematical model of the robot arm is not used for the specific motion analysis of the robot arm.
  • the mathematical model of a robotic arm does not provide information such as the trajectory of the robotic arm. Therefore, it can also be understood that the mathematical model of the robotic arm (involving factory simulation) is located at the upper level of the kinematics model (involving machining simulation), and the kinematics model at the lower level reflects more detailed information than the mathematical model at the upper level.
  • a kinematic model involves geometric information (i.e., the geometric model of the object in three dimensions), kinematic information (e.g., kinematic constraints, kinematic pairs, motion speed, kinematic freedom), device parameters (e.g., length, speed ) And processing time (for example, unit working time).
  • the mathematical model can involve geometric information, kinematic information, equipment parameters, processing time, throughput, energy consumption information, and so on. Both of these involve geometric information, kinematic information, equipment parameters, processing time, etc. (as shown in section 104 of Figure 1). Table 1 lists the information and data involved in some kinematic models and data models:
  • FIG. 2 is a schematic diagram showing a relationship between a kinematic model and a mathematical model of a robot according to an embodiment of the present application.
  • the data involved in the robot's kinematics model and data model are shown in Table 2:
  • 202-2 in the kinematics model 202 of the robot represents the geometric model, processing time, and waiting time in the kinematics model of the robot.
  • 204-2 in the mathematical model of the robot 204 represents the geometric model, processing time, and waiting time in the mathematical model of the robot.
  • 202-4 in the robot's kinematics model 202 represents collisions, movement trajectories (e.g., the robot's degree of freedom of movement) in the robot's kinematics model.
  • the 204-4 part in the mathematical model of the robot 204 represents the energy consumption and throughput in the mathematical model of the robot.
  • data of 202-2 in the kinematics model of the robot may be converted into data of 204-2 in the mathematical model of the robot, as shown by arrow 1.
  • data of 204-4 in the mathematical model of the robot may be obtained from outside (for example, input) as shown by arrow 2.
  • kinematics models are used in kinematics simulations and have more comprehensive geometric information.
  • the kinematic model also has more comprehensive data such as equipment parameters and processing efficiency. Therefore, although data from kinematics such as kinematics may not be needed to build a mathematical model, some manufacturing parameters (e.g., equipment parameters such as length and width, processing time such as unit working time) from the kinematic model may be helpful For building mathematical models.
  • data may be acquired from a kinematic model and mapped to a mathematical model (factory simulation).
  • mathematical models can be easily and quickly established.
  • FIG. 3 is a flowchart of a data processing method according to an embodiment of the present application. As shown in Figure 3, the method includes:
  • Step S302 the user inputs the relationship between the object to be modeled and the source object via a user interface.
  • the user can input the relationship through an I / O interface.
  • One or more of the I / O devices can communicate between a person and a computer system.
  • I / O devices may include keyboards, keys, microphones, displays, mice, printers, scanners, speakers, still cameras, styluses, tablets, touch screens, trackballs, cameras, and the like.
  • the data processing method may be used for plant modeling, and the source objects include at least one of one or more equipment in the plant and one or more workpieces processed by the plant equipment.
  • the object to be modeled and the source object may be a workpiece to be processed, a robot arm, a conveyor belt.
  • the relationship between the object to be modeled and the source object may include at least one of the following: the object to be modeled and the source object are the same object; the object to be modeled is a combination of source objects (for example, the source object is in a factory For each robot arm of a production line, the object to be modeled is a combination of all robot arms on a production line in the factory); the object to be modeled and the source object are related to each other in the production process (for example, the source object is on the production line)
  • Step S304 Obtain geometric data and statistical data of the source object from the kinematics model of the source object according to the relationship between the object to be modeled and the source object input in step S302.
  • the geometric data of the source object includes at least one of the following: the orientation information of the source object in the factory; the location information of the source object in the factory, and
  • the statistics of the source object include at least one of the following: the name of the source object; the type of the source object; the translation speed of the source object; the rotation speed of the source object; the length of the source object; the currently processed workpiece of the source object The processing duration of the source object; the waiting duration of the source object waiting to process the workpiece.
  • the geometric data of the source object includes at least one of the following: the geometric model of the source object; the source object is in the factory
  • the orientation information of the source object; the location information of the source object in the factory, and the statistics of the source object include at least one of the following: the name of the source object; the type of the source object; the translation speed of the source object; the rotation speed of the source object ; The length of the source object; the processing duration of the source object currently being processed; the waiting duration of the source object waiting to be processed.
  • geometric data is used for 3D modeling in mathematical models.
  • the purpose of obtaining geometric data is to input the obtained model and its relative position for 3D display.
  • the obtained statistics are used for 2D modeling in mathematical models.
  • the purpose of obtaining statistical data is to input statistical data information into a 2D model for simulation.
  • step S306 the acquired geometric data and statistical data of the source object are converted into geometric data and statistical data of the object to be modeled according to the relationship between the object to be modeled and the source object input in step S302.
  • the specific method for converting the geometric data and statistical data of the source object into the geometric data and statistical data of the object to be modeled will be described in detail in FIG. 4.
  • Step S308 Use the transformed geometric data to perform three-dimensional mathematical modeling of the object to be modeled to obtain a three-dimensional mathematical model of the object to be modeled.
  • a three-dimensional mathematical model of the object to be modeled is shown in, for example, part 804 in FIG. 8.
  • Step S310 Use the converted statistical data to perform two-dimensional mathematical modeling of the object to be modeled to obtain a two-dimensional mathematical model of the object to be modeled.
  • a two-dimensional mathematical model of the object to be modeled is shown as 806 in FIG. 8.
  • step S302 may be omitted.
  • step S306 in the case where it is only necessary to convert the acquired geometric data and statistical data of the source object into geometric data and statistical data of the object to be modeled, the process may be ended at step S306 without performing step S308 and step S310.
  • this disclosure describes and illustrates specific components, devices, or systems that perform specific steps of the method of FIG. 3, this disclosure contemplates any suitable component, device, or system that performs any suitable steps of the method of FIG. Any suitable combination.
  • step S302 may be omitted.
  • user input may not be required.
  • the execution order of steps S308 and S310 is adjusted.
  • steps S308 and S310 may be performed in parallel, or may be performed in any serial order.
  • modeling of a mathematical model using a kinematic model is realized. That is, the conversion from machining simulation to factory simulation is realized.
  • FIG. 4 is a flowchart of the conversion steps in the data processing method according to the embodiment of the present application, and the specific details of the conversion steps in the data processing method according to the embodiment of the present application are further described with reference to FIG. 4.
  • This conversion step includes:
  • Step S402. it is determined whether the relationship between the object to be modeled and the source object input in step S302 in FIG. 3 is one of the following cases: the object to be modeled and the source object are the same object; The object to be modeled is a combination of source objects; the position of the object to be modeled and the source object in the production process or in the factory are related to each other.
  • step S404 when it is determined in step S402 that the object to be modeled and the source object are the same object, the acquired geometric data and statistical data of the source object are used as the geometric data and statistical data of the object to be modeled.
  • the obtained geometric data and statistical data of the kinematics model of the first robotic arm are used as the geometrical data and statistics of the mathematical model of the first robotic arm, respectively data.
  • step S406 when it is determined in step S402 that the object to be modeled is a combination of source objects, the acquired geometric data and statistical data of the source objects are used as the geometric data and statistical data of the object to be modeled.
  • the object to be modeled is a single robotic arm, and the source object is a combination of robotic arms, the first robotic arm, the second robotic arm, and the third robotic arm on each pipeline will be obtained.
  • Nth The geometric data and statistical data of the kinematic model of each robot arm (N is an integer greater than 3) are used as the geometric data and statistical data of the mathematical model of the combination of all the robot arms on each pipeline.
  • Step S408 When it is determined in step S402 that the position of the object to be modeled and the position of the source object in the production process or in the factory are related to each other, the acquired geometric data and statistical data of the source object are converted into the geometric data of the object to be modeled and Statistical data. When it is determined that the positions of the object to be modeled and the source object are related to each other in the factory, step S410 is performed.
  • the data obtained from the kinematic model is about the moving time of the workpiece, while the corresponding object in the mathematical model is the conveyor belt. Therefore, in order to realize modeling in a mathematical model using data of a kinematic model, it is necessary to convert the moving time of a workpiece into the speed of a conveyor belt.
  • step S412 is performed.
  • step S412 according to the production process-based conversion relationship between the geometric data of the object to be modeled and the geometric data of the source object, The obtained geometric data of the source object is converted into the geometric data of the object to be modeled, and the obtained statistical data of the source object is converted into based on the production process conversion relationship between the statistical data of the object to be modeled and the statistical data of the source object.
  • the data obtained from the kinematics model is about the processing duration of the first workpiece that is currently being processed, while the corresponding object in the mathematical model is the first in the next processing stage after being processed as the first workpiece.
  • Two artifacts Therefore, in order to realize modeling in a mathematical model using data of a kinematic model, it is necessary to convert the processing duration of the first workpiece to the processing duration of the second workpiece waiting to be processed.
  • the relationship between the object of the kinematic model and the object of the mathematical model has been stored in advance. Therefore, according to the predetermined relationship, the data obtained from the kinematic model can be processed to calculate the mathematical model. Desired value.
  • a user interface UI can be provided, allowing the user to manually define the relationship between the object to be modeled and the source object, and giving the geometric data and statistical data of the object to be modeled and the source object Conversion relationship between geometric data and statistical data.
  • the kinematic model of the slider as the workpiece to be processed and the kinematic model of the conveyor belt as equipment in the factory can be known or obtained, and the interrelationship between the slider and the conveyor belt in the production process can be determined or entered.
  • the blocks are placed on the conveyor and the slider moves in translation as the conveyor moves. Therefore, the movement time of the slider can be obtained from the kinematics model of the slider, and the length of the conveyor can be obtained from the kinematics model of the conveyor.
  • S represents the speed of the conveyor belt in the mathematical model of the conveyor belt as the object to be modeled
  • L represents the length of the conveyor belt obtained from the kinematic model of the conveyor belt as the source object
  • T represents the length from The movement time of the slider obtained from the kinematics model of the slider of the object.
  • the speed of the conveyor belt for mathematically modeling the conveyor belt as an object to be modeled can be obtained.
  • the object to be modeled is a conveyor belt and the source object is an artifact.
  • the user inputs a conveyor belt and a workpiece on a graphical interface via an input device such as a keyboard or a touch screen.
  • a workpiece is a workpiece being transported on a conveyor. Therefore, the position of the conveyor belt and the workpiece in the factory are interrelated.
  • geometric data for example, the orientation information of the workpiece in the factory, position information in the factory
  • statistical data for example, the duration of the movement of the workpiece
  • the obtained geometric data and statistical data of the workpiece are converted into geometric data and statistical data of the object to be modeled (for example, the speed of a conveyor belt).
  • the user can also manually define the conversion relationship between the statistical data of the conveyor belt and the statistical data of the workpiece according to the position in the factory through the graphical user interface, and then convert the obtained statistical data of the workpiece (for example, the moving time of the workpiece) into the Statistics (for example, the speed of a conveyor belt).
  • the length of the conveyor belt is divided by the movement duration of the workpiece to obtain the speed of the conveyor belt.
  • the transformed geometric data and statistical data are used to perform 3D mathematical modeling and 2D mathematical modeling, so as to obtain a 3D mathematical model and a 2D mathematical model of the conveyor belt.
  • a three-dimensional mathematical model and a two-dimensional mathematical model of the conveyor belt can be performed using a mathematical modeling method (NX MOTION, NX MCD) known in the art.
  • FIG. 5 is a block diagram of a data processing apparatus according to an embodiment of the present application.
  • the data processing apparatus includes: an input unit 502 for inputting a relationship between an object to be modeled and a source object by a user; and an acquisition unit 504 for receiving the relationship output by the input unit,
  • the geometric data and statistical data of the source object are obtained from the kinematics model of the source object;
  • the conversion unit 506 is configured to convert the geometric data and statistical data of the source object obtained by the acquisition unit into Geometric data and statistical data of the modeled object;
  • a modeling unit 508, configured to use the geometric data obtained by the acquisition unit to perform three-dimensional mathematical modeling of the object to be modeled to obtain a three-dimensional mathematical model of the object to be modeled, and construct
  • the model unit is configured to perform two-dimensional mathematical modeling of the object to be modeled by using the statistical data obtained by the obtaining unit to obtain a two-dimensional mathematical model of the object to be modeled.
  • the obtaining unit 504 includes: a geometric data obtaining unit 504-2, configured to obtain geometric data of the source object from a kinematic model of the source object according to the relationship determined by the determining unit; a statistical data obtaining unit 504-4, It is used to obtain the statistical data of the source object from the kinematics model of the source object according to the relationship determined by the determination unit.
  • the conversion unit 506 includes a geometric data conversion unit 506-2, configured to convert the geometric data of the source object obtained by the geometric data acquisition unit 504-2 into the object to be modeled according to the relationship determined by the determination unit.
  • Statistical data conversion unit 506-4 configured to convert the statistical data of the source object obtained by the statistical data acquisition unit 504-4 into the statistical data of the object to be modeled according to the relationship determined by the determination unit.
  • the geometric data acquisition unit acquires geometric information and relative position and orientation information.
  • the statistical data acquisition section acquires statistical data information (for example, object name, object type, speed, length, processing time, waiting time).
  • the geometric data acquisition section acquires geometric data of all objects from the kinematic model.
  • the geometric data acquisition unit can acquire geometric information of all objects in the kinematics simulator.
  • the acquired geometric information can be saved as a file in a format supported by the mathematical simulator.
  • geometric information can be saved in the path of the saved file.
  • the statistical data acquisition unit acquires statistical data of a part of the objects from the kinematics model.
  • the statistical data acquisition section can acquire all required statistical data information.
  • the obtaining unit uses an object-oriented method. Establish categories to store information for all objects. This category has several attributes. It includes object name, object type, object geometry model. And, for different object types, its inherent different properties.
  • the obtained data can be stored in an object-oriented manner.
  • categories are established and all source objects are stored by category. For each source object, the corresponding information is stored.
  • FIG. 6 is a schematic diagram of a file structure of an information acquisition module of a data processing apparatus according to an embodiment of the present application.
  • the category "conveyor belt” (denoted as A in Fig. 6) as an example, it can have speed (denoted as B in Fig. 6), width (denoted as C in Fig. 6), length (denoted as in Fig. 6 as D), the location in the factory (indicated as E in FIG. 6), the orientation in the factory (indicated as F in FIG. 6), and other attributes and the storage path of geometric information (indicated as G in FIG. 6). That is, in the acquisition unit 504, the attributes for the category "conveyor belt” are stored in an object-oriented manner as shown in Table 3 below.
  • the acquired data is stored in a folder in a format supported by the mathematical model for subsequent use. Since the obtained information is object-oriented, automatic mapping in the conversion unit 506 can be realized. For example, according to the needs for modeling in a mathematical model, or according to the relationship between the object to be modeled and the source object, only a part of the statistical data in the kinematics model of the source object or a part of the statistical data of the object may be obtained. In addition, in some cases, some statistical data can be generated based on geometric data. For example, statistical data such as the length of the object can be generated based on the geometric data of the source object.
  • geometric data is a geometric model of an object in three-dimensional space
  • the data does not have such information as length, width, and height, but statistical methods can be obtained in specific ways.
  • the geometric model is a straight belt
  • the above data processing apparatus and its internal unit perform the data processing method shown in FIG. 3, which will not be repeated here. In this manner, a device for modeling in a mathematical model is provided.
  • FIG. 7 is a block diagram of a data processing system according to an embodiment of the present application.
  • the system includes: a kinematics model simulator 702 for obtaining a kinematics model of a source object; an input unit 704 for inputting a relationship between the object to be modeled and the source object; an obtaining unit 706 for Obtaining the geometric data and statistical data of the source object from the kinematics model of the source object according to the relationship output by the input unit; a conversion unit 708, configured to according to the relationship output by the input unit To convert the geometric data and statistical data of the source object obtained by the obtaining unit into geometric data and statistical data of the object to be modeled; a mathematical model simulator 710 is configured to utilize the converted unit The converted geometric data is used to perform three-dimensional mathematical modeling of the object to be modeled to obtain the three-dimensional mathematical model of the object to be modeled, and the statistical data transformed by the conversion unit is used to perform two
  • FIG. 8 it is a block diagram of a kinematics model, a three-dimensional mathematical model of a mathematical model, and a two-dimensional mathematical model according to an embodiment of the present application.
  • reference numeral 802 in FIG. 8 represents a kinematic model of the source object
  • reference numeral 804 represents a 3D model of a mathematical model of the object to be modeled
  • reference numeral 806 represents a 2D model of the mathematical model of the object to be modeled.
  • the system may be an electronic device that includes hardware, software, or embedded logic elements or a combination of two or more such elements and is capable of performing suitable functions implemented or supported by the system.
  • the system may include a computer system, such as a desktop computer, notebook or laptop computer, notebook, tablet, e-reader, GPS device, camera, personal digital assistant (PDA), handheld Electronic devices, cellular phones, smartphones, augmented / virtual reality devices, other suitable electronic devices, or any suitable combination thereof.
  • PDA personal digital assistant
  • This disclosure contemplates any suitable system.
  • the system enables network users on the client system to access the network.
  • the system enables its users to communicate with other users on other client systems.
  • a storage medium includes a stored program, wherein, when the program runs, the device where the storage medium is located is controlled to execute the foregoing data processing method.
  • a processor is provided, and the processor is configured to run a program, and the program executes the foregoing data processing method when the program is run.
  • a computer program product that is tangibly stored on a computer-readable medium and includes computer-executable instructions that, when executed, cause at least A processor executes the data processing method described above.
  • the method according to the embodiment of the present application can be implemented by a program in a storage medium, a processor, and a terminal, thereby implementing fast and convenient modeling in a mathematical model.
  • the description of each embodiment has its own emphasis. For a part that is not described in detail in an embodiment, reference may be made to the related description of other embodiments.
  • FIG. 9 is a block diagram of a plant-level simulation according to an embodiment of the present application.
  • reference numeral 902 represents a simulation of a plurality of individual robotic arms as equipment in a factory, which is usually a physical-level simulation (NX MOTION, NX MCD, which has not only kinematic information, but also physical information (for example, Mass, force).
  • Numeral 904 in FIG. 9 represents the use of kinematic models for simulation of multiple product line levels including multiple robotic arms, respectively.
  • Numeral 906 in FIG. 9 represents the use of simulation for the plant level including all product lines. Mathematical model.
  • the information obtained from the kinematic model can be used to quickly and easily build a mathematical model. It saves a lot of time required for modeling.
  • Kinematic simulator processing simulation
  • mathematical simulator Vectory simulation
  • a mathematical model can be easily constructed using information obtained from a kinematic model. This greatly reduces the time required to model in a mathematical model. Therefore, it is very easy and meaningful to build a "bridge" between a kinematics simulator (machining simulation) and a mathematical simulator (factory simulation). This means that, if the operator already has a machining simulation model, he can easily build a plant simulation model.
  • kinematic models which are in process simulation
  • mathematical models which are in factory simulation
  • the model can be automatically created in the mathematical simulator, and can be connected The entire product line for factory simulation. The product relationship will be closer.
  • the disclosed technical content can be implemented in other ways.
  • the device embodiments described above are only schematic.
  • the division of the unit or module is only a logical function division.
  • there may be another division manner such as multiple units or modules or components. It can be combined or integrated into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, modules or units, and may be electrical or other forms.
  • the units or modules described as separate components may or may not be physically separated, and the components displayed as units or modules may or may not be physical units or modules, which may be located in one place, or may be distributed to On multiple network elements or modules. Some or all of the units or modules may be selected according to actual needs to achieve the objective of the solution of this embodiment.
  • each functional unit or module in each embodiment of the present application may be integrated into one processing unit or module, or each unit or module may exist separately physically, or two or more units or modules may be integrated into one Unit or module.
  • the above-mentioned integrated unit or module can be implemented in the form of hardware or in the form of software functional unit or module.
  • the integrated unit When the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it may be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially a part that contributes to the existing technology or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium. , Including a number of instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present application.
  • the foregoing storage medium includes: U disk, Read-Only Memory (ROM, Read-Only Memory), Random Access Memory (RAM, Random Access Memory), mobile hard disk, magnetic disk, or optical disk and other media that can store program codes.

Abstract

L'invention concerne un procédé, un dispositif et un système de traitement de données, un support d'informations et un processeur. Le procédé consiste : à obtenir, en fonction de la relation entre un objet à modéliser et un objet source, les données géométriques et les données statistiques de l'objet source à partir du modèle cinématique de l'objet source ; et à convertir, en fonction de la relation entre l'objet à modéliser et l'objet source, les données géométriques obtenues et les données statistiques de l'objet source en données géométriques et en données statistiques permettant d'effectuer une modélisation mathématique sur l'objet à modéliser. Grâce à l'utilisation d'informations provenant d'un modèle cinématique, un modèle mathématique peut être établi facilement et rapidement.
PCT/CN2018/109071 2018-09-30 2018-09-30 Procédé, dispositif et système de traitement de données, support d'informations et processeur WO2020062232A1 (fr)

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