CN110962124A - Method for compensating static error and correcting dynamic stiffness model of cutting machining robot - Google Patents
Method for compensating static error and correcting dynamic stiffness model of cutting machining robot Download PDFInfo
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Abstract
The invention discloses a method for correcting a static error compensation and dynamic stiffness model of a cutting machining robot, which relates to the technical field of robot machining, and adopts the following scheme: performing kinematic calibration on the robot according to the description file of the robot body parameters, identifying the robot structure parameters, performing static error compensation, and simultaneously recording measurement and calculation data in the calibration process; establishing a complete machine dynamic stiffness model of the robot, identifying modal parameters through a modal analysis experiment and recording modal experiment data; detecting whether the robot posture precision and the dynamic stiffness model meet the robot tail end positioning precision requirement: a) if the accuracy requirement is not met, performing kinematic calibration on the stress conditions of the robot at different poses, calculating an elastic deformation error caused by the self weight of the robot in a calibration process, and correcting a static error compensation and a whole machine dynamic stiffness model of the robot in the calibration process; b) and if the accuracy requirement is met, completing static error compensation and correction of the robot dynamic stiffness model.
Description
Technical Field
The invention relates to a cutting robot, in particular to a method for correcting a static error compensation and dynamic stiffness model of the cutting robot.
Background
The progress and application of the industrial robot technology are important means and key links for promoting the intelligent manufacturing development of China. The industrial robot has the advantages of high flexibility, low cost, large working space and flexible pose control, can meet the requirements of modern production modes of various, small-batch and field processing when being applied to cutting processing, obviously reduces the production cost, improves the utilization rate of equipment and processing space, and effectively improves the technical innovation speed and enterprise competitiveness. However, the industrial robot has the problems of low repeated positioning precision, poor rigidity, complicated error analysis and control and the like, so that the application of the robot in the field of cutting machining is greatly limited.
How to carry out effective analysis to the error of cutting process robot, improve the machining precision is the key problem who promotes the robot cutting process and use. The errors of the robot cutting process mainly comprise static errors and dynamic errors. For static errors, a static error model can be established by a kinematics calibration method and error compensation is carried out, but the elastic deformation error caused by the self weight of the robot is not separated from the measured data during the primary kinematics calibration, so that the identified structural parameters have errors, and meanwhile, the dynamic stiffness model error is also caused because the whole dynamic stiffness model of the robot is a function of the structural parameters. Therefore, a method for correcting a static error compensation and dynamic stiffness model of a cutting robot is needed to synthesize an analysis process of dynamic and static errors and correct the static error compensation and dynamic stiffness model of the robot, so as to solve the problem of poor machining precision of the robot.
Disclosure of Invention
The invention provides a method for compensating static errors and correcting a dynamic stiffness model of a cutting machining robot, aiming at the problems of low repeated positioning precision, poor stiffness, complicated error analysis control and the like of an industrial robot.
The invention discloses a method for correcting a static error compensation and dynamic stiffness model of a cutting machining robot, which adopts the following technical scheme for solving the technical problems:
a static error compensation and dynamic stiffness model correction method for a cutting machining robot is realized by the following steps:
firstly, performing kinematic calibration on a robot according to a description file of robot body parameters, identifying robot structure parameters, compensating static errors, and simultaneously recording measurement and calculation data in a calibration process;
establishing a dynamic stiffness model of the whole robot, identifying modal parameters through a modal analysis experiment and recording modal experiment data;
step three, detecting whether the pose precision and the dynamic stiffness model of the robot meet the positioning precision requirement of the tail end of the robot or not:
a) if the accuracy requirement is not met, performing kinematic calibration on the stress conditions of the robot at different poses, calculating an elastic deformation error caused by the self weight of the robot in a calibration process, correcting static error compensation in the calibration process, compensating based on the corrected static error, returning to the step two, and correcting the built complete machine dynamic stiffness model of the robot;
b) and if the accuracy requirement is met, completing static error compensation and correction of the robot dynamic stiffness model.
Specifically, the description file of the robot body parameter can completely describe the normative file of the robot body parameter, and the generation process of the description file includes:
1) according to the structural parameters of the robot, the sensitivity of the dynamic characteristics of the robot is analyzed, the structural parameters comprise three types of functional components, joint connection modes and structural components, wherein the functional components comprise a driving unit, a connecting rod unit and a speed reducer unit, the joint connection modes comprise integrated connection and coupling connection, and the structural components comprise serial connection, parallel connection and serial-parallel connection combination;
2) establishing a precision criterion and a specification of parameter description according to an analysis result;
3) adopting a standardized XML file format as a carrier, and respectively generating a description file of the parameters of the functional component, a description file of the parameters of the joint connection mode and a description file of the parameters of the structure composition after performing sensitivity analysis on the three parameters of the functional component, the joint connection mode and the structure composition;
4) and integrating the description file of the parameters of the functional components, the description file of the parameters of the joint connection mode and the description file of the parameters of the structure composition by the open-source xml file generator to generate the description file of the parameters of the robot body.
More specifically, in the process of generating the description file, according to the structural parameters of the robot, the sensitivity analysis of the dynamic characteristics of the robot includes the following specific operations:
establishing a robot simulation model according to the robot structure parameters;
establishing a simulation dynamic stiffness model according to the robot simulation model;
taking the simulation dynamic stiffness model as a target function, and carrying out sensitivity analysis on the structural parameters of the robot;
determining the sensitivity of the influence of the change of the robot structural parameters on the dynamic characteristics of the robot control system, weighing the sensitivity of the structural parameters through calculation, programming and analysis by a mechanical engineer, and then manually establishing the precision criterion and the specification of the parameter description.
Specifically, in the first step, the kinematic calibration of the robot is a process of identifying accurate parameters of a complete machine dynamic stiffness model of the robot by using an advanced measurement means and a proper parameter identification method, so as to improve the precision of the robot, and the process includes:
1) modeling: establishing a robot model which has a correct functional relation and is related to the robot kinematics by using simulation software, wherein the robot model represents the relation between the structural parameters and the angles of all joints of the robot and the position of the tail end of the robot in a Cartesian space;
2) measurement: commanding the robot to execute a plurality of groups of actions, recording joint angle values and space coordinate values acquired by the laser tracker in real time when the robot executes each group of actions, simultaneously commanding the robot model to synchronously execute the actions of the robot, further calculating a theoretical Cartesian space position at the tail end of the robot model, and finally obtaining the actual position of the robot and the theoretical position of the robot model;
3) parameter identification: selecting the mean square sum of the space position deviation of the measuring position points as an objective function, taking the robot structure parameters as optimization variables, carrying out optimization solution, and determining the error coefficient of the established robot model;
4) and (3) error correction: and inputting the error coefficient into simulation software to correct the robot model.
Specifically, in the second step, the specific operation of establishing the complete machine dynamic stiffness model includes:
acquiring a description file of robot body parameters, and calling a model class library through the description file;
firstly, carrying out theoretical analysis on components influencing error analysis and component contact characteristics in the robot, establishing a dynamic stiffness theoretical submodel of the contact characteristics of the components and the components by adopting a computational modal analysis method,
then, performing modal experiments on components influencing error analysis in the robot and component contact characteristics, establishing a dynamic stiffness experiment submodel and a modal submodel of the components and the component contact characteristics by acquiring and processing excitation and response data, identifying modal parameters and performing verification of the dynamic stiffness experiment submodel;
then, removing minimal factors influencing error analysis according to theoretical analysis results, simplifying variables of the dynamic stiffness theoretical submodel, and correcting the dynamic stiffness theoretical submodel of the corresponding component and the contact characteristic of the component through the dynamic stiffness experimental submodel to obtain the dynamic stiffness submodel meeting the precision requirement;
finally, synthesizing the dynamic stiffness submodels meeting the precision requirement into a complete machine dynamic stiffness theoretical model of the robot through a modal synthesis theory;
performing modal experiment on the whole robot, establishing a whole machine dynamic stiffness experiment model and a modal model of the robot by acquiring and processing excitation and response data, identifying modal parameters and verifying the whole machine dynamic stiffness experiment model;
and (IV) correcting the whole dynamic stiffness theoretical model through the whole dynamic stiffness experimental model to obtain a whole dynamic stiffness model meeting the precision requirement.
More specifically, the related model class library is designed by applying an object-oriented method, and the design process comprises the following steps:
1) establishing a robot component error analysis base class by using a tool SQLserver, wherein the base class comprises an ID, an error analysis method and other attributes and is used for analyzing the reasons for generating component errors;
2) functional component classes and joint connection mode classes are derived from the robot component error analysis base class, wherein,
the functional component class is used for analyzing the influence of the rigidity of the component on the error, and derives a rod piece class and a reducer class from the functional component class;
the joint connection mode is used for analyzing the influence of the contact rigidity of the component, and the joint connection mode derives two sub-types of integral connection and coupling connection;
3) and (4) packaging the base class and the derived subclasses, and calling the packaging information of the model class library by the description file of the robot body parameters when the theoretical model of the whole dynamic stiffness of the robot is established.
In the step (two), the dynamic stiffness submodels are integrated into a complete machine dynamic stiffness theoretical model of the robot through a modal synthesis theory, and the process comprises the following steps:
carrying out modal experiment on components influencing error analysis in the robot and component contact characteristics, establishing a dynamic stiffness experiment submodel and a modal submodel of the component and component contact characteristics by collecting and processing excitation and response data, identifying modal parameters and carrying out verification on the dynamic stiffness experiment submodel;
removing minimum factors influencing error analysis according to theoretical analysis results, and simplifying variables of the dynamic stiffness theoretical submodel;
modifying the dynamic stiffness theoretical submodel of the corresponding component and the contact characteristic of the component through the dynamic stiffness experimental submodel to obtain a dynamic stiffness submodel meeting the precision requirement;
and synthesizing the dynamic stiffness submodels meeting the precision requirement into a complete machine dynamic stiffness theoretical model of the robot through a modal synthesis theory.
Preferably, in the step (four), the specific process of correcting the theoretical model of the whole dynamic stiffness through the experimental model of the whole dynamic stiffness is as follows:
step 1: inputting the technological parameters into a controller, executing the processing track by the controller, and acquiring experimental data through a dynamometer and an acceleration sensor;
step 2: carrying out Fourier transform on the collected acceleration data to obtain vibration amplitude spectrum data, carrying out logarithm operation on the amplitude spectrum data, and then obtaining amplitude spectrum cepstrum data through inverse Fourier transform;
and step 3: performing exponential window filtering operation on the amplitude spectrum cepstrum data obtained in the step (2), and performing inverse cepstrum operation on the filtered cepstrum data to obtain vibration amplitude spectrum data under random excitation;
and 4, step 4: carrying out Fourier transform on the collected acceleration data to obtain vibration phase spectrum data;
and 5: combining the amplitude spectrum and the phase spectrum data obtained in the steps 3 and 4, performing inverse Fourier transform to obtain an acceleration time domain signal under random excitation in the processing process;
step 6: and (5) identifying modal parameters by using the time domain signal obtained in the step (5) through a least square complex frequency domain method, obtaining a functional relation between the deformation of the tail end of the cutting robot and the change of the cutting force, and further constructing a complete machine dynamic stiffness model of the cutting robot meeting the precision requirement.
Specifically, in the first step, an elastic deformation error caused by the self weight of the robot in the calibration process is calculated, and the process comprises the following steps:
1) calculating elastic deformation coefficient E, measuring the deformation data sigma of terminal Cartesian space coordinate at several positions with laser tracker, establishing a mapping relation table of deformation sigma and gravity epsilon according to the gravity epsilon of robot, and calculating the elastic deformation coefficient E according to formula (1)
Calculating the average elastic deformation coefficients of different pose conditions;
2) calculating and compensating elastic deformation error according to elastic deformation coefficient and gravity at corresponding pose via formula (1)
And (3) calculating a deformation error, compensating the deformation error into the robot model, and repeating the processes of measuring, calculating a deformation coefficient and compensating the deformation error in the step 1) until the precision condition is met.
Compared with the prior art, the method for compensating the static error and correcting the dynamic stiffness model of the cutting machining robot has the beneficial effects that:
1) the method comprises the steps of calculating the self gravity of the robot and the elastic deformation caused by the self gravity in the calibration process by analyzing the stress of the robot in different poses and combining the parameters of the robot body and a dynamic stiffness model, realizing static error compensation in the calibration process, then iteratively optimizing the analysis process, and correcting the structural parameters of the robot and the dynamic stiffness model of the whole robot obtained by kinematics calibration, so that the accuracy of the static error compensation and the dynamic stiffness model is improved, and the problem of poor machining accuracy of the robot is solved;
2) in the iterative optimization analysis process, the experimental result data of the kinematics calibration and modal analysis experiment is used, multiple times of kinematics calibration measurement and modal experiments are not needed, and the implementation difficulty of the method is reduced.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a flow chart of generating a robot ontology parameter description file in the present invention;
FIG. 3 is a flow chart of establishing a complete machine dynamic stiffness model in the invention;
FIG. 4 is a flow chart of establishing a theoretical model of the dynamic stiffness of the whole machine in the invention.
Detailed Description
In order to make the technical scheme, the technical problems to be solved and the technical effects of the present invention more clearly apparent, the following technical scheme of the present invention is clearly and completely described with reference to the specific embodiments.
The first embodiment is as follows:
with reference to fig. 1, the present embodiment provides a method for correcting a static error compensation and dynamic stiffness model of a cutting robot, where the method is implemented by:
and S100, performing kinematic calibration on the robot according to the description file of the robot body parameters, identifying the robot structure parameters, compensating static errors, and simultaneously recording measurement and calculation data in the calibration process.
With reference to fig. 2, in step S100, the description file of the robot ontology parameters involved, that is, the normative file capable of completely describing the robot ontology parameters, is generated in the process of generating the description file, where:
s101, analyzing the sensitivity of the dynamic characteristics of the robot according to the structural parameters of the robot, wherein the structural parameters comprise three types of functional components, joint connection modes and structural components, the functional components comprise driving units, connecting rod units and speed reducer units, the joint connection modes comprise integrated connection and coupling connection, and the structural components comprise serial connection, parallel connection and serial-parallel connection combination;
s102, establishing precision criteria and specifications of parameter description according to the analysis result;
s103, adopting a standardized XML file format as a carrier, carrying out sensitivity analysis on three parameters of the functional component, the joint connection mode and the structure composition, and respectively generating a description file of the parameters of the functional component, a description file of the parameters of the joint connection mode and a description file of the parameters of the structure composition;
and S104, integrating the description file of the functional component parameters, the description file of the joint connection mode parameters and the description file of the structure composition parameters by an open source xml file generator to generate a description file of the robot body parameters.
In the generation process of the description file, according to the structural parameters of the robot, the sensitivity analysis of the dynamic characteristics of the robot is carried out, and the specific operations comprise:
establishing a robot simulation model according to the robot structure parameters;
establishing a simulation dynamic stiffness model according to the robot simulation model;
taking the simulation dynamic stiffness model as a target function, and carrying out sensitivity analysis on the structural parameters of the robot;
determining the sensitivity of the influence of the change of the robot structural parameters on the dynamic characteristics of the robot control system, weighing the sensitivity of the structural parameters through calculation, programming and analysis by a mechanical engineer, and then manually establishing the precision criterion and the specification of the parameter description.
In step S100, the kinematics calibration of the robot is a process of identifying accurate parameters of a complete machine dynamic stiffness model of the robot by using an advanced measurement means and a proper parameter identification method, so as to improve the precision of the robot, and the process includes:
s111, modeling: establishing a robot model which has a correct functional relation and is related to the robot kinematics by using simulation software, wherein the robot model represents the relation between the structural parameters and the angles of all joints of the robot and the position of the tail end of the robot in a Cartesian space;
s112, measurement: commanding the robot to execute a plurality of groups of actions, recording joint angle values and space coordinate values acquired by the laser tracker in real time when the robot executes each group of actions, simultaneously commanding the robot model to synchronously execute the actions of the robot, further calculating a theoretical Cartesian space position at the tail end of the robot model, and finally obtaining the actual position of the robot and the theoretical position of the robot model;
s113, parameter identification: selecting the mean square sum of the space position deviation of the measuring position points as an objective function, taking the robot structure parameters as optimization variables, carrying out optimization solution, and determining the error coefficient of the established robot model;
s114, error correction: and inputting the error coefficient into simulation software to correct the robot model.
And step S200, establishing a complete machine dynamic stiffness model of the robot by combining the attached figures 3 and 4, identifying modal parameters through a modal analysis experiment and recording modal experiment data.
In step S200, with reference to fig. 3, the specific operation of establishing the stiffness model of the whole machine includes:
s210, obtaining a description file of the robot body parameters, and calling a model class library through the description file;
s220, with reference to the attached figure 4, firstly, theoretical analysis is carried out on components and component contact characteristics influencing error analysis in the robot, a dynamic stiffness theoretical submodel of the contact characteristics of each component and component is established by adopting a computational modal analysis method,
then, performing modal experiments on components influencing error analysis in the robot and component contact characteristics, establishing a dynamic stiffness experiment submodel and a modal submodel of the components and the component contact characteristics by acquiring and processing excitation and response data, identifying modal parameters and performing verification of the dynamic stiffness experiment submodel;
then, removing minimal factors influencing error analysis according to theoretical analysis results, simplifying variables of the dynamic stiffness theoretical submodel, and correcting the dynamic stiffness theoretical submodel of the corresponding component and the contact characteristic of the component through the dynamic stiffness experimental submodel to obtain the dynamic stiffness submodel meeting the precision requirement;
finally, synthesizing the dynamic stiffness submodels meeting the precision requirement into a complete machine dynamic stiffness theoretical model of the robot through a modal synthesis theory;
s230, performing modal experiments on the whole robot, establishing a whole machine dynamic stiffness experimental model and a modal model of the robot through collecting and processing excitation and response data, identifying modal parameters and verifying the whole machine dynamic stiffness experimental model;
s240, correcting the whole dynamic stiffness theoretical model through the whole dynamic stiffness experimental model to obtain a whole dynamic stiffness model meeting the precision requirement.
In step S210, the model class library is designed by applying an object-oriented method, and the design process includes:
s211, establishing a robot assembly error analysis base class by means of the SQLserver, wherein the base class comprises an ID, an error analysis method and other attributes and is used for analyzing the reason of assembly error generation;
s212, deriving a functional component class and a joint connection mode class by the robot component error analysis base class, wherein,
the functional component class is used for analyzing the influence of the rigidity of the component on the error, and derives a rod piece class and a reducer class from the functional component class;
the joint connection mode is used for analyzing the influence of the contact rigidity of the component, and the joint connection mode derives two sub-types of integral connection and coupling connection;
s213, the encapsulation base class and the derived subclass, and when the robot complete machine dynamic stiffness theoretical model is established, the encapsulation information of the model class library is called by the description file of the robot body parameters.
In step S220, the dynamic stiffness sub-model is integrated into a complete dynamic stiffness theoretical model of the robot through a modal synthesis theory, and the process includes:
carrying out modal experiment on components influencing error analysis in the robot and component contact characteristics, establishing a dynamic stiffness experiment submodel and a modal submodel of the component and component contact characteristics by collecting and processing excitation and response data, identifying modal parameters and carrying out verification on the dynamic stiffness experiment submodel;
removing minimum factors influencing error analysis according to theoretical analysis results, and simplifying variables of the dynamic stiffness theoretical submodel;
modifying the dynamic stiffness theoretical submodel of the corresponding component and the contact characteristic of the component through the dynamic stiffness experimental submodel to obtain a dynamic stiffness submodel meeting the precision requirement;
and synthesizing the dynamic stiffness submodels meeting the precision requirement into a complete machine dynamic stiffness theoretical model of the robot through a modal synthesis theory.
In step S240, the specific process of correcting the theoretical model of the whole dynamic stiffness through the experimental model of the whole dynamic stiffness is as follows:
s241, inputting the technological parameters into a controller, executing the processing track by the controller, and acquiring experimental data through a dynamometer and an acceleration sensor;
s242, carrying out Fourier transform on the collected acceleration data to obtain vibration amplitude spectrum data, carrying out logarithm operation on the amplitude spectrum data, and then obtaining amplitude spectrum cepstrum data through inverse Fourier transform;
s243, performing exponential window filtering operation on the amplitude spectrum cepstrum data obtained in the step S242, and performing inverse cepstrum operation on the filtered cepstrum data to obtain vibration amplitude spectrum data under random excitation;
s244, carrying out Fourier transform on the collected acceleration data to obtain vibration phase spectrum data;
s245, combining the amplitude spectrum and the phase spectrum data obtained in the step S243 and the step S244, performing inverse Fourier transform to obtain an acceleration time domain signal under random excitation in the machining process;
and S246, identifying modal parameters by using the time domain signal obtained in the step S245 through a least square complex frequency domain method, obtaining a functional relation between the deformation of the tail end of the cutting robot and the change of the cutting force, and further constructing a complete machine dynamic stiffness model of the cutting robot meeting the precision requirement.
Step S300, detecting whether the robot pose precision and the dynamic stiffness model meet the robot tail end positioning precision requirement:
a) if the accuracy requirement is not met, performing kinematic calibration on the stress conditions of the robot at different poses, calculating an elastic deformation error caused by the self weight of the robot in a calibration process, correcting static error compensation in the calibration process, returning to the step S200 based on the corrected static error compensation, and correcting the established whole machine dynamic stiffness model of the robot;
b) and if the accuracy requirement is met, completing static error compensation and correction of the robot dynamic stiffness model.
In step S300, an elastic deformation error caused by the self weight of the robot in the calibration process is calculated, and the process includes:
1) calculating elastic deformation coefficient E, measuring the deformation data sigma of terminal Cartesian space coordinate at several positions with laser tracker, establishing a mapping relation table of deformation sigma and gravity epsilon according to the gravity epsilon of robot, and calculating the elastic deformation coefficient E according to formula (1)
Calculating the average elastic deformation coefficients of different pose conditions;
2) calculating and compensating elastic deformation error according to elastic deformation coefficient and gravity at corresponding pose via formula (1)
And (3) calculating a deformation error, compensating the deformation error into the robot model, and repeating the processes of measuring, calculating a deformation coefficient and compensating the deformation error in the step 1) until the precision condition is met.
In summary, the method for correcting the static error compensation and the dynamic stiffness model of the cutting machining robot can be used for correcting the obtained structural parameters of the robot and the dynamic stiffness model of the whole machine by using kinematics calibration and modal analysis, so that the accuracy of the static error compensation and the dynamic stiffness model is improved, and the problem of poor machining accuracy of the robot is solved.
The principles and embodiments of the present invention have been described in detail using specific examples, which are provided only to aid in understanding the core technical content of the present invention. Based on the above embodiments of the present invention, those skilled in the art should make any improvements and modifications to the present invention without departing from the principle of the present invention, and therefore, the present invention should fall into the protection scope of the present invention.
Claims (9)
1. A method for compensating static error and correcting a dynamic stiffness model of a cutting machining robot is characterized by comprising the following implementation processes:
firstly, performing kinematic calibration on a robot according to a description file of robot body parameters, identifying robot structure parameters, compensating static errors, and simultaneously recording measurement and calculation data in a calibration process;
establishing a dynamic stiffness model of the whole robot, identifying modal parameters through a modal analysis experiment and recording modal experiment data;
step three, detecting whether the pose precision and the dynamic stiffness model of the robot meet the positioning precision requirement of the tail end of the robot or not:
a) if the accuracy requirement is not met, performing kinematic calibration on the stress conditions of the robot at different poses, calculating an elastic deformation error caused by the self weight of the robot in a calibration process, correcting static error compensation in the calibration process, compensating based on the corrected static error, returning to the step two, and correcting the built complete machine dynamic stiffness model of the robot;
b) and if the accuracy requirement is met, completing static error compensation and correction of the robot dynamic stiffness model.
2. The method for correcting the static error compensation and dynamic stiffness model of the cutting machining robot according to claim 1, wherein the description file of the robot body parameters is a normative file capable of completely describing the robot body parameters, and the generation process of the description file comprises:
1) according to the structural parameters of the robot, the sensitivity of the dynamic characteristics of the robot is analyzed, the structural parameters comprise three types of functional components, joint connection modes and structural components, wherein the functional components comprise a driving unit, a connecting rod unit and a speed reducer unit, the joint connection modes comprise integrated connection and coupling connection, and the structural components comprise serial connection, parallel connection and serial-parallel connection combination;
2) establishing a precision criterion and a specification of parameter description according to an analysis result;
3) adopting a standardized XML file format as a carrier, and respectively generating a description file of the parameters of the functional component, a description file of the parameters of the joint connection mode and a description file of the parameters of the structure composition after performing sensitivity analysis on the three parameters of the functional component, the joint connection mode and the structure composition;
4) and integrating the description file of the parameters of the functional components, the description file of the parameters of the joint connection mode and the description file of the parameters of the structure composition by the open-source xml file generator to generate the description file of the parameters of the robot body.
3. The method for correcting the static error compensation and dynamic stiffness model of the cutting machining robot according to claim 2, wherein the sensitivity analysis of the dynamic characteristics of the robot according to the structural parameters of the robot comprises the following specific operations:
establishing a robot simulation model according to the robot structure parameters;
establishing a simulation dynamic stiffness model according to the robot simulation model;
taking the simulation dynamic stiffness model as a target function, and carrying out sensitivity analysis on the structural parameters of the robot;
determining the sensitivity of the influence of the change of the robot structural parameters on the dynamic characteristics of the robot control system, weighing the sensitivity of the structural parameters through calculation, programming and analysis by a mechanical engineer, and then manually establishing the precision criterion and the specification of the parameter description.
4. The method for compensating static error and modifying dynamic stiffness model of cutting robot as claimed in claim 1, wherein the kinematics calibration of the robot is a process of identifying accurate parameters of the dynamic stiffness model of the whole robot by using advanced measurement means and a proper parameter identification method, thereby improving the accuracy of the robot, the process comprising:
1) modeling: establishing a robot model which has a correct functional relation and is related to the robot kinematics by using simulation software, wherein the robot model represents the relation between the structural parameters and the angles of all joints of the robot and the position of the tail end of the robot in a Cartesian space;
2) measurement: commanding the robot to execute a plurality of groups of actions, recording joint angle values and space coordinate values acquired by the laser tracker in real time when the robot executes each group of actions, simultaneously commanding the robot model to synchronously execute the actions of the robot, further calculating a theoretical Cartesian space position at the tail end of the robot model, and finally obtaining the actual position of the robot and the theoretical position of the robot model;
3) parameter identification: selecting the mean square sum of the space position deviation of the measuring position points as an objective function, taking the robot structure parameters as optimization variables, carrying out optimization solution, and determining the error coefficient of the established robot model;
4) and (3) error correction: and inputting the error coefficient into simulation software to correct the robot model.
5. The method for correcting the static error compensation and dynamic stiffness model of the cutting machining robot according to any one of claims 1 to 4, wherein the specific operation of establishing the whole dynamic stiffness model comprises the following steps:
acquiring a description file of robot body parameters, and calling a model class library through the description file;
firstly, carrying out theoretical analysis on components influencing error analysis and component contact characteristics in the robot, establishing a dynamic stiffness theoretical submodel of the contact characteristics of the components and the components by adopting a computational modal analysis method,
then, performing modal experiments on components influencing error analysis in the robot and component contact characteristics, establishing a dynamic stiffness experiment submodel and a modal submodel of the components and the component contact characteristics by acquiring and processing excitation and response data, identifying modal parameters and performing verification of the dynamic stiffness experiment submodel;
then, removing minimal factors influencing error analysis according to theoretical analysis results, simplifying variables of the dynamic stiffness theoretical submodel, and correcting the dynamic stiffness theoretical submodel of the corresponding component and the contact characteristic of the component through the dynamic stiffness experimental submodel to obtain the dynamic stiffness submodel meeting the precision requirement;
finally, synthesizing the dynamic stiffness submodels meeting the precision requirement into a complete machine dynamic stiffness theoretical model of the robot through a modal synthesis theory;
performing modal experiment on the whole robot, establishing a whole machine dynamic stiffness experiment model and a modal model of the robot by acquiring and processing excitation and response data, identifying modal parameters and verifying the whole machine dynamic stiffness experiment model;
and (IV) correcting the whole dynamic stiffness theoretical model through the whole dynamic stiffness experimental model to obtain a whole dynamic stiffness model meeting the precision requirement.
6. The method for modifying a static error compensation and dynamic stiffness model of a machining robot according to claim 5, wherein the model class library is designed by applying an object-oriented method, and the design process comprises:
1) establishing a robot component error analysis base class by using a tool SQLserver, wherein the base class comprises an ID, an error analysis method and other attributes and is used for analyzing the reasons for generating component errors;
2) functional component classes and joint connection mode classes are derived from the robot component error analysis base class, wherein,
the functional component class is used for analyzing the influence of the rigidity of the component on the error, and derives a rod piece class and a reducer class from the functional component class;
the joint connection mode is used for analyzing the influence of the contact rigidity of the component, and the joint connection mode derives two sub-types of integral connection and coupling connection;
3) and (4) packaging the base class and the derived subclasses, and calling the packaging information of the model class library by the description file of the robot body parameters when the theoretical model of the whole dynamic stiffness of the robot is established.
7. The method for compensating static error and modifying dynamic stiffness model of cutting robot as claimed in claim 5, wherein the dynamic stiffness sub-model is integrated into the whole dynamic stiffness theoretical model of robot by modal synthesis theory, the process includes:
carrying out modal experiment on components influencing error analysis in the robot and component contact characteristics, establishing a dynamic stiffness experiment submodel and a modal submodel of the component and component contact characteristics by collecting and processing excitation and response data, identifying modal parameters and carrying out verification on the dynamic stiffness experiment submodel;
removing minimum factors influencing error analysis according to theoretical analysis results, and simplifying variables of the dynamic stiffness theoretical submodel;
modifying the dynamic stiffness theoretical submodel of the corresponding component and the contact characteristic of the component through the dynamic stiffness experimental submodel to obtain a dynamic stiffness submodel meeting the precision requirement;
and synthesizing the dynamic stiffness submodels meeting the precision requirement into a complete machine dynamic stiffness theoretical model of the robot through a modal synthesis theory.
8. The method for compensating the static error and correcting the dynamic stiffness model of the cutting machining robot according to claim 7, wherein the specific process of correcting the whole dynamic stiffness theoretical model through the whole dynamic stiffness experimental model comprises the following steps:
step 1: inputting the technological parameters into a controller, executing the processing track by the controller, and acquiring experimental data through a dynamometer and an acceleration sensor;
step 2: carrying out Fourier transform on the collected acceleration data to obtain vibration amplitude spectrum data, carrying out logarithm operation on the amplitude spectrum data, and then obtaining amplitude spectrum cepstrum data through inverse Fourier transform;
and step 3: performing exponential window filtering operation on the amplitude spectrum cepstrum data obtained in the step (2), and performing inverse cepstrum operation on the filtered cepstrum data to obtain vibration amplitude spectrum data under random excitation;
and 4, step 4: carrying out Fourier transform on the collected acceleration data to obtain vibration phase spectrum data;
and 5: combining the amplitude spectrum and the phase spectrum data obtained in the steps 3 and 4, performing inverse Fourier transform to obtain an acceleration time domain signal under random excitation in the processing process;
step 6: and (5) identifying modal parameters by using the time domain signal obtained in the step (5) through a least square complex frequency domain method, obtaining a functional relation between the deformation of the tail end of the cutting robot and the change of the cutting force, and further constructing a complete machine dynamic stiffness model of the cutting robot meeting the precision requirement.
9. The method for compensating static error and modifying dynamic stiffness model of cutting processing robot according to any one of claims 1-4 or 6-8, wherein the elastic deformation error caused by the self weight of the robot in the calibration process is calculated, and the process comprises:
1) calculating elastic deformation coefficient E, measuring the deformation data sigma of terminal Cartesian space coordinate at several positions with laser tracker, establishing a mapping relation table of deformation sigma and gravity epsilon according to the gravity epsilon of robot, and calculating the elastic deformation coefficient E according to formula (1)
Calculating the average elastic deformation coefficients of different pose conditions;
2) calculating and compensating elastic deformation error according to elastic deformation coefficient and gravity at corresponding pose via formula (1)
And (3) calculating a deformation error, compensating the deformation error into the robot model, and repeating the processes of measuring, calculating a deformation coefficient and compensating the deformation error in the step 1) until the precision condition is met.
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