CN114310907A - Multi-working-condition self-adaptive industrial robot tail end vibration suppression method - Google Patents
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Abstract
The invention discloses a multi-working-condition self-adaptive industrial robot tail end vibration suppression method, which comprises the following steps of: a data preparation stage: selecting a certain number of position points representing the whole robot motion space; acquiring a vibration signal corresponding to each position point by using an acceleration sensor; and (3) a data processing stage: analyzing the vibration signal to obtain vibration parameters corresponding to the position points; analyzing the acquired and calculated data to select independent variables and dependent variables; analyzing the scatter diagram and selecting a proper nonlinear regression equation for fitting; designing an input shaper by using vibration parameters; a working condition self-adaptive stage; the method aims to provide a multi-working-condition self-adaptive industrial robot tail end vibration suppression method, a small amount of data are collected, the mean square error is calculated by utilizing the collected natural frequency parameters calculated by a sum equation, the mean square error is used as an index to correct the regression equation coefficient, and the optimal shaper design parameters are guaranteed to be obtained.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a multi-working-condition self-adaptive method for suppressing the tail end vibration of an industrial robot.
Background
Industrial robots have increasingly been incorporated into manufacturing and are widely used in welding, painting and assembly operations. However, due to poor precision and low rigidity of the robot, great challenges exist on high-speed and high-precision roads. Because there is great flexibility in industrial robot joint department, when carrying out the operation, can inevitably take place the vibration, can divide into two parts with these vibrations: process vibration, residual vibration. In welding and freight operations, quick repositioning is needed, but the existence of residual vibration causes that the operation can be carried out after the vibration amplitude is reduced to a certain magnitude before each positioning, thereby greatly reducing the working efficiency. Therefore, suppression of the residual vibration at the end of the robot is a problem to be solved urgently.
To reduce the effects of residual vibration, researchers have proposed two main vibration suppression methods: on-line vibration suppression using closed-loop control and off-line vibration suppression using trajectory planning. Compared with an offline method, the online vibration suppression technology has better disturbance rejection capability at the cost of needing an additional sensor and higher cost; the off-line method can also effectively avoid residual vibrations if an accurate estimate of the natural frequency can be known in advance. Obviously, off-line vibration suppression is more consistent with industrial robots. Input Shaping Technology (IST), which is an off-line vibration suppression technology that avoids residual vibration by generating a trajectory having a self-canceling characteristic, has been applied to many fields including cranes, numerical control machines, etc.
The IST was originally proposed by Singer in 1988 for a linear time-invariant system, whose natural frequency parameters are fixed and invariant, so that there still exists a certain difficulty in applying it to a robot system or other nonlinear time-variant systems. For this purpose, researchers modify the structure of the designed shaper to adapt to the change of system parameters by introducing new constraint conditions to improve the robustness of the shaper, so that the shaper is gradually evolved from the original ZV shaper to ZVD, EI, SI, and the like. In addition, due to the principle problem of the IST, when designing the shaper, a delay is inevitably introduced, and with the introduction of constraint conditions, the delay problem becomes more serious, and in order to solve the problem, later researchers perform accelerated processing on the trajectory by various methods, including methods such as a negative pulse shaper, trajectory acceleration, phase offset, and the like.
The above proposed IST solves the problem of the variation of the natural frequency parameters of the nonlinear time varying system to some extent, but has a problem that they adopt a single parameter shaper for track processing. The existing Input Shaping Technology (IST) is designed by basically adopting a single system parameter when an industrial robot shaper is designed, and the actual working condition is not analyzed and processed, so that the selection of the design parameter of the shaper is extremely difficult, and the designed shaper has poor effect in actual application and is difficult to cope with some changed working conditions.
Disclosure of Invention
The invention aims to provide a multi-working-condition self-adaptive industrial robot tail end vibration suppression method, which is characterized in that a small amount of data is collected, the mean square error is calculated by utilizing the collected natural frequency parameters calculated by a sum equation, and the regression equation coefficient is corrected by taking the mean square error as an index, so that the optimal shaper design parameters are ensured to be obtained.
In order to achieve the purpose, the invention adopts the following technical scheme: a multi-working condition self-adaptive industrial robot tail end vibration suppression method comprises the following steps:
a data preparation stage: selecting a certain number of position points representing the whole robot motion space; acquiring a vibration signal corresponding to each position point by using an acceleration sensor;
and (3) a data processing stage: analyzing the vibration signal to obtain vibration parameters corresponding to the position points; analyzing the acquired and calculated data to select independent variables and dependent variables; analyzing the scatter diagram and selecting a proper nonlinear regression equation for fitting; designing an input shaper by using vibration parameters;
and (3) a working condition self-adaptive stage: selecting a small number of position points according to actual working conditions to acquire vibration signals; and analyzing to obtain vibration parameters, and correcting the coefficient of the regression equation by using the obtained data.
Preferably, in the data preparation phase, the method specifically includes: the robot working space analysis method comprises the steps that an acceleration sensor is installed at the tail end of a robot, the robot working space is analyzed, a certain number of position points representing the whole robot movement space are selected, common loads in actual operation are selected for experiment, joint angles corresponding to the selected position points are issued to a controller, the robot moves to a specified position, vibration signals under the position are obtained through the acceleration sensor, and meanwhile corresponding joint angles and load parameters are stored.
Preferably, in the data processing stage, the method specifically includes:
the method comprises the following steps: processing the vibration signal obtained in the data preparation stage to obtain the vibration parameter of the system, and obtaining the natural frequency parameter of the system and the damping ratio parameter of the system at the corresponding position through processing and analysis;
step two: analyzing the data acquired and calculated in the data preparation stage and the first step, and determining independent variables and dependent variables of a nonlinear regression equation; selecting the natural frequency parameter as a dependent variable according to robustness analysis, analyzing joint angles and load parameters obtained in a data preparation stage as preselected parameters to select independent variables, drawing scatter diagrams of each preselected parameter and the natural frequency parameter, performing comparative analysis on all the point diagrams, and selecting the parameter with the largest influence on the natural frequency as the independent variable;
step three: designing a multiple nonlinear regression equation for the independent variables and the dependent variables obtained in the step two, analyzing a scatter diagram of each independent variable and each dependent variable by using a controlled variable method to obtain an order relation of each independent variable and each dependent variable so as to obtain a required regression model, and analyzing by using a least square method to obtain coefficients of the equation;
step four: and C, calculating the natural frequency parameter of the corresponding position by using the regression equation obtained in the step three, designing a proper input shaper, accelerating the preset track according to the time delay of the shaper to obtain a new position instruction, and applying the shaper to the accelerated position instruction to obtain a corrected position instruction.
Preferably, in the step one, the vibration signal obtained in the data preparation stage is processed to obtain system vibration parameters, the processing process includes fast fourier transform, the fast fourier transform mainly uses a computer to rapidly implement discrete fourier transformation, and x (n) is a robot end vibration signal collected in the data preparation stage, the signal is a finite-length sequence with a length M, and the discrete fourier transform formula is as follows:
in the formula (I), the compound is shown in the specification,
n is the interval length of discrete Fourier transform, N is more than or equal to M, and X (k) is a group of complex results obtained by the discrete Fourier transform.
Preferably, in the step one, the vibration signal obtained in the data preparation stage is processed to obtain a system vibration parameter, the processing process includes calculation by an attenuation method, and the damping ratio coefficient is obtained by analyzing according to an energy attenuation curve of the system under the condition of free vibration, and the formula is as follows:
in the formula, An+m、AnTwo peaks on the curve that are m peaks apart.
Preferably, in step four, the input shaper is:
in the formula (f)ISFor a designed pulse sequence of length n, AiIs the pulse amplitude, t, of the ith pulse in the pulse trainiIs the instant of action of the pulse. According to the time delay t introduced in the input shaper formulad＝t-tnAccelerating the predetermined track, and taking coefficients
Let s (t) be the position command of the predetermined track, and the specific formula for performing the acceleration processing is as follows: sacc(τ)＝sacc(kt)＝s(t)，t∈[0,T]In the formula, sacc(τ) is the position command after acceleration, after which the corrected position command can be obtained using the input shaper.
Preferably, in the working condition adaptive stage, the method specifically includes: and performing coefficient correction on the obtained regression equation according to the actual working condition, comparing the natural frequency parameters corresponding to the calculated and collected data with the natural frequency parameters obtained by actual collection by using the regression equation obtained in the data processing stage, and performing equation coefficient correction by using the mean square error of the natural frequency parameters as an index.
Preferably, the coefficient correction process in the adaptive stage of the operating condition specifically includes: adopting a small amount of data to correct the coefficient of a regression equation in a data processing stage, and correcting the equation coefficient by taking the mean square error of the inherent frequency as an index, wherein the specific index is as follows:
in the formula, yiIs the value of the inherent frequency that is acquired,
is the average of the natural frequencies calculated using the regression equation.
The technical scheme of the invention has the beneficial effects that: by analyzing the motion space of the robot and adopting multivariate nonlinear regression analysis to obtain the relationship between parameters such as joint angles, loads and the like and the design parameters of the shaper, the most appropriate design parameters are ensured to be obtained in the operation process of the robot; meanwhile, considering that external disturbance exists in actual operation, the optimal shaper is guaranteed to be designed by adopting a small amount of data to correct the coefficient of the fitting equation.
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FIG. 1 is a schematic flow diagram of one embodiment of the present invention.
Detailed Description
The technical scheme of the invention is further explained by the specific implementation mode in combination with the attached drawings.
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Referring to fig. 1, the method for suppressing the end vibration of the industrial robot with the adaptive multi-working condition comprises the following steps:
a data preparation stage: selecting a certain number of position points representing the whole robot motion space; acquiring a vibration signal corresponding to each position point by using an acceleration sensor;
and (3) a data processing stage: analyzing the vibration signal to obtain vibration parameters corresponding to the position points; analyzing the acquired and calculated data to select independent variables and dependent variables; analyzing the scatter diagram and selecting a proper nonlinear regression equation for fitting; designing an input shaper by using vibration parameters;
and (3) a working condition self-adaptive stage: selecting a small number of position points according to actual working conditions to acquire vibration signals; and analyzing to obtain vibration parameters, and correcting the coefficient of the regression equation by using the obtained data.
The existing shaper is basically designed by adopting a single system vibration parameter, and the design of the shaper with multiple system vibration parameters is realized by designing a multiple nonlinear regression equation; in order to better adapt to the practical application of the industrial robot, a small amount of data is collected, the mean square error is calculated by utilizing the collected natural frequency parameters calculated by the sum equation, and the regression equation coefficient is corrected by taking the mean square error as an index, so that the optimal shaper design parameters are ensured to be obtained.
The method and the device analyze the motion space of the robot, and obtain the relationship between parameters such as joint angles and loads and design parameters of a shaper by adopting multivariate nonlinear regression analysis, so that the most appropriate design parameters can be obtained in the operation process of the robot; meanwhile, considering that external disturbance exists in actual operation, the optimal shaper is guaranteed to be designed by adopting a small amount of data to correct the coefficient of the fitting equation.
In the present application, the terms appearing are to be interpreted:
input Shaping Technique (IST): the shaper is designed using the natural frequency and damping ratio parameters of the system to avoid residual vibrations by generating a trajectory with self-canceling characteristics.
Multivariate nonlinear regression analysis: the method is characterized in that a nonlinear regression model containing more than two variables is processed by drawing a scatter diagram, linearizing the nonlinear regression model, segmenting and the like, and fitting is carried out by using a least square method.
FFT (fast fourier transform): the conversion from the time domain to the frequency domain of the signal is realized by using the general name of an efficient and quick method of computer-computed Discrete Fourier Transform (DFT).
Attenuation method: and (4) drawing an amplitude reduction vibration curve of the free vibration of the system, and analyzing the curve to obtain a damping ratio coefficient of the system.
Specifically, in the data preparation phase, the method specifically includes: the robot working space analysis method comprises the steps that an acceleration sensor is installed at the tail end of a robot, the robot working space is analyzed, a certain number of position points representing the whole robot movement space are selected, common loads in actual operation are selected for experiment, joint angles corresponding to the selected position points are issued to a controller, the robot moves to a specified position, vibration signals under the position are obtained through the acceleration sensor, and meanwhile corresponding joint angles and load parameters are stored.
In the present application, the specific definition of selecting a certain number of position points is to collect a limited number of position points according to the difference of the actual robot, and generally select a point at the end and a point at the joint. According to the vibration direction that needs restrain, at the terminal reasonable installation acceleration sensor of industrial robot, guarantee that it can correctly gather the vibration signal of corresponding direction, pass through band-pass filter with the vibration signal who obtains and filter low frequency and high frequency signal, obtain the vibration signal that can use.
Preferably, in the data processing stage, the method specifically includes:
the method comprises the following steps: processing the vibration signal obtained in the data preparation stage to obtain the vibration parameter of the system, and obtaining the natural frequency parameter of the system and the damping ratio parameter of the system at the corresponding position through processing and analysis;
step two: analyzing the data acquired and calculated in the data preparation stage and the first step, and determining independent variables and dependent variables of a nonlinear regression equation; selecting the natural frequency parameter as a dependent variable according to robustness analysis, analyzing joint angles and load parameters obtained in a data preparation stage as preselected parameters to select independent variables, drawing scatter diagrams of each preselected parameter and the natural frequency parameter, performing comparative analysis on all the point diagrams, and selecting the parameter with the largest influence on the natural frequency as the independent variable;
step three: designing a multiple nonlinear regression equation for the independent variables and the dependent variables obtained in the step two, analyzing a scatter diagram of each independent variable and each dependent variable by using a controlled variable method to obtain an order relation of each independent variable and each dependent variable so as to obtain a required regression model, and analyzing by using a least square method to obtain coefficients of the equation;
step four: and C, calculating the natural frequency parameter of the corresponding position by using the regression equation obtained in the step three, designing a proper input shaper, accelerating the preset track according to the time delay of the shaper to obtain a new position instruction, and applying the shaper to the accelerated position instruction to obtain a corrected position instruction.
In the application, in the first step, the vibration signal obtained in the data preparation stage is processed to obtain the system vibration parameter, the processing process includes fast fourier transform, the fast fourier transform mainly utilizes a computer to rapidly realize discrete fourier transformation, x (n) is set as a robot terminal vibration signal collected in the data preparation stage, the signal is a finite length sequence with the length of M, and the discrete fourier transform formula is as follows:
in the formula (I), the compound is shown in the specification,
n is the interval length of discrete Fourier transform, N is more than or equal to M, and X (k) is a group of complex results obtained by the discrete Fourier transform.
Furthermore, in the first step, the vibration signal obtained in the data preparation stage is processed to obtain the system vibration parameters, the processing process includes calculation by an attenuation method, and the damping ratio coefficient is obtained by analyzing according to the energy attenuation curve of the system under the condition of free vibration, and the formula is as follows:
in the formula, An+m、AnTwo peaks on the curve that are m peaks apart.
Further, in step four, the input shaper is:
in the formula (f)ISFor designed pulse sequences, it is longDegree n, AiIs the pulse amplitude, t, of the ith pulse in the pulse trainiIs the instant of action of the pulse. According to the time delay t introduced in the input shaper formulad＝t-tnAccelerating the predetermined track, and taking coefficients
Let s (t) be the position command of the predetermined track, and the specific formula for performing the acceleration processing is as follows: sacc(τ)＝sacc(kt)＝s(t)，t∈[0,T]In the formula, sacc(τ) is the position command after acceleration, after which the corrected position command can be obtained using the input shaper.
Specifically, in the working condition adaptive phase, the method specifically includes: and performing coefficient correction on the obtained regression equation according to the actual working condition, comparing the natural frequency parameters corresponding to the calculated and collected data with the natural frequency parameters obtained by actual collection by using the regression equation obtained in the data processing stage, and performing equation coefficient correction by using the mean square error of the natural frequency parameters as an index.
Because a regression equation is already obtained, only a small amount of data needs to be acquired to perform correction when the regression equation obtained in the data processing stage is used.
Preferably, the coefficient correction process in the adaptive stage of the operating condition specifically includes: adopting a small amount of data to correct the coefficient of a regression equation in a data processing stage, and correcting the equation coefficient by taking the mean square error of the inherent frequency as an index, wherein the specific index is as follows:
in the formula, yiIs the value of the inherent frequency that is acquired,
is the average of the natural frequencies calculated using the regression equation.
The method comprises the steps of carrying out relational mapping on joint angles, loads and natural frequency parameters by using a multivariate nonlinear regression equation, analyzing the corresponding relations of the joint angles, the loads and the natural frequency, and selecting several groups of parameters with larger influences as independent variables of the regression equation. The working condition self-adaption realization of shaping design is provided, the coefficient of the regression equation is adjusted to realize the working condition self-adaption, and the coefficient of the regression equation is corrected by collecting a small amount of data and taking the mean square error of the inherent frequency as an index.
In the description herein, references to the description of the terms "embodiment," "example," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The technical principle of the present invention is described above in connection with specific embodiments. The description is made for the purpose of illustrating the principles of the invention and should not be construed in any way as limiting the scope of the invention. Based on the explanations herein, those skilled in the art will be able to conceive of other embodiments of the present invention without inventive effort, which would fall within the scope of the present invention.
Claims (8)
1. A multi-working condition self-adaptive industrial robot tail end vibration suppression method is characterized by comprising the following steps:
a data preparation stage: selecting a certain number of position points representing the whole robot motion space; acquiring a vibration signal corresponding to each position point by using an acceleration sensor;
and (3) a data processing stage: analyzing the vibration signal to obtain vibration parameters corresponding to the position points; analyzing the acquired and calculated data to select independent variables and dependent variables; analyzing the scatter diagram and selecting a proper nonlinear regression equation for fitting; designing an input shaper by using vibration parameters;
and (3) a working condition self-adaptive stage: selecting a small number of position points according to actual working conditions to acquire vibration signals; and analyzing to obtain vibration parameters, and correcting the coefficient of the regression equation by using the obtained data.
2. The method for suppressing the end vibration of the industrial robot with the adaptive multi-working condition according to claim 1 is characterized by specifically comprising the following steps in the data preparation phase: the robot working space analysis method comprises the steps that an acceleration sensor is installed at the tail end of a robot, the robot working space is analyzed, a certain number of position points representing the whole robot movement space are selected, common loads in actual operation are selected for experiment, joint angles corresponding to the selected position points are issued to a controller, the robot moves to a specified position, vibration signals under the position are obtained through the acceleration sensor, and meanwhile corresponding joint angles and load parameters are stored.
3. The method for suppressing the vibration of the tail end of the industrial robot with the adaptive multi-working condition according to claim 1 is characterized by specifically comprising the following steps in the data processing stage:
the method comprises the following steps: processing the vibration signal obtained in the data preparation stage to obtain the vibration parameter of the system, and obtaining the natural frequency parameter of the system and the damping ratio parameter of the system at the corresponding position through processing and analysis;
step two: analyzing the data acquired and calculated in the data preparation stage and the first step, and determining independent variables and dependent variables of a nonlinear regression equation; selecting the natural frequency parameter as a dependent variable according to robustness analysis, analyzing joint angles and load parameters obtained in a data preparation stage as preselected parameters to select independent variables, drawing scatter diagrams of each preselected parameter and the natural frequency parameter, performing comparative analysis on all the point diagrams, and selecting the parameter with the largest influence on the natural frequency as the independent variable;
step three: designing a multiple nonlinear regression equation for the independent variables and the dependent variables obtained in the step two, analyzing a scatter diagram of each independent variable and each dependent variable by using a controlled variable method to obtain an order relation of each independent variable and each dependent variable so as to obtain a required regression model, and analyzing by using a least square method to obtain coefficients of the equation;
step four: and C, calculating the natural frequency parameter of the corresponding position by using the regression equation obtained in the step three, designing a proper input shaper, accelerating the preset track according to the time delay of the shaper to obtain a new position instruction, and applying the shaper to the accelerated position instruction to obtain a corrected position instruction.
4. The method for suppressing the end vibration of the industrial robot under the adaptive multi-working condition according to claim 3, wherein in the step one, the vibration signal obtained in the data preparation stage is processed to obtain the system vibration parameters, the processing process includes fast fourier transform, the fast fourier transform mainly uses a computer to rapidly implement discrete fourier transform, and x (n) is set as the robot end vibration signal collected in the data preparation stage, and the signal is a finite-length sequence with the length of M, and the discrete fourier transform formula is as follows:
in the formula (I), the compound is shown in the specification,
n is the interval length of discrete Fourier transform, N is more than or equal to M, and X (k) is a group of complex results obtained by the discrete Fourier transform.
5. The method for suppressing the end vibration of the industrial robot under the adaptive multi-working condition according to claim 3, wherein in the first step, the vibration signal obtained in the data preparation stage is processed to obtain the system vibration parameters, the processing process comprises the calculation of an attenuation method, and the damping ratio coefficient is obtained by analyzing according to the energy attenuation curve of the system under the condition of free vibration, and the formula is as follows:
in the formula, An+m、AnTwo peaks on the curve that are m peaks apart.
6. The method for suppressing the end vibration of the industrial robot with the adaptive multi-working condition according to claim 3, wherein in the fourth step, the input shaper is:
in the formula (f)ISFor a designed pulse sequence of length n, AiIs the pulse amplitude, t, of the ith pulse in the pulse trainiThe acting time of the pulse; according to the time delay t introduced in the input shaper formulad＝t-tnAccelerating the predetermined track, and taking coefficients
Let s (t) be the position command of the predetermined track, and the specific formula for performing the acceleration processing is as follows: sacc(τ)＝sacc(kt)＝s(t)，t∈[0,T]In the formula, sacc(τ) is the position command after acceleration, after which the corrected position command can be obtained using the input shaper.
7. The method for suppressing the vibration of the tail end of the industrial robot with the adaptive multi-working condition according to claim 1 is characterized by specifically comprising the following steps in the working condition adaptive stage: and performing coefficient correction on the obtained regression equation according to the actual working condition, comparing the natural frequency parameters corresponding to the calculated and collected data with the natural frequency parameters obtained by actual collection by using the regression equation obtained in the data processing stage, and performing equation coefficient correction by using the mean square error of the natural frequency parameters as an index.
8. The method for suppressing the vibration of the tail end of the industrial robot with the adaptive multi-working condition as claimed in claim 7, wherein the coefficient correction process in the working condition adaptive stage is specifically as follows: taking a small amount of data to correct the coefficient of regression equation in data processing stageThe frequency mean square error is used as an index to correct the equation coefficient, and the specific index is as follows:
in the formula, yiIs the value of the inherent frequency that is acquired,
is the average of the natural frequencies calculated using the regression equation.
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| 周星,黄石峰,朱志红.: "六关节工业机器人TCP标定模型研究与算法改进", 《机械工程学报》, vol. 55, no. 11 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114700988A (en) * | 2022-05-09 | 2022-07-05 | 西安交通大学 | Joint action division method for health monitoring of mechanical transmission part of industrial robot |
| CN114700988B (en) * | 2022-05-09 | 2023-10-24 | 西安交通大学 | Joint motion dividing method for health monitoring of industrial robot transmission part |
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