CN115056218A - Method and system for identifying robot mode by using joint motor current signal - Google Patents
Method and system for identifying robot mode by using joint motor current signal Download PDFInfo
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Abstract
The invention discloses a method and a system for identifying robot modes by using joint motor current signals, belonging to the field of robot dynamics, wherein the method comprises the following steps: the robot structure is excited by using the inertia force in the acceleration and deceleration movement process of the mechanical arm of the robot, and the robot structure can generate corresponding vibration response under the action of the excitation force. Meanwhile, collecting current signals of the joint motor, processing the current signals based on an OMA theory and identifying the robot mode. Compared with the existing method for identifying the robot mode by using the vibration signal, the method for identifying the robot mode by using the joint motor current signal is firstly provided, so that the robot mode in the machining process can be analyzed in real time, the robot mode parameters under different poses can be identified, and the operation process is simple.
Description
Technical Field
The invention belongs to the field of robot dynamics, and particularly relates to a method and a system for identifying a robot mode by using a joint motor current signal.
Background
The large curved surface component is widely applied to the industries of aviation, aerospace, navigation and the like, and compared with machine tool machining, the robot machining has the characteristics of flexible structure, large operation space and quick reconstruction, can reach inaccessible areas of complex parts, and is expected to become an important machining means in the field of large complex component machining. Although the robot large arm unfolding processing characteristics are very suitable for the in-place processing of the large curved surface components, certain development and effect are achieved in the aspects of processing efficiency and processing flexibility. But robotic milling is still now considered an open problem. One of the major problems is the inherently weak stiffness of the robot tandem. The robot has relatively low pose-associated structure dynamic stiffness, and the processing precision and the surface integrity of the robot are often reduced.
Currently, robot research is mainly focused on the fields of robot processes and kinematics. The method of estimating tip properties for a combination of a milling force model and a robot spring model is limited to account for static deformation. However, the static stiffness criteria for optimum attitude selection generally do not guarantee an optimum vibration level and thus surface roughness. In the traditional method, the dynamic parameters of the robot are mainly obtained by a vibration sensor of an external pasting or embedding structure and a mixed Finite Element Method (FEM), the operation process of the experiment method based on the vibration sensor is complex, and the precision of the finite element analysis method is limited by the accuracy of a model. Therefore, the method and the device can conveniently and quickly identify the robot modal parameters, and have very important significance for improving the robot processing quality and enriching the large-scale component robotized processing stability theoretical system.
Disclosure of Invention
In view of the above disadvantages and the improved needs of the prior art, the present invention provides a method and a system for identifying a robot mode by using a joint motor current signal, which are based on an OMA theory and obtain a joint motor current signal to identify a mode parameter of a robot under the action of a random inertial force generated by a robot joint random idle operation excitation.
In order to achieve the above object, the present invention provides a method for identifying a robot mode by using a joint motor current signal, comprising:
controlling each joint motor to accelerate or decelerate, and exciting the modal parameters of the robot;
and acquiring a current signal of the joint motor, processing the current signal based on a working mode analysis method OMA and identifying the robot mode.
Further, the robot is a multi-joint robot;
respectively acquiring current signals of each joint motor and performing modal identification;
and if all joints recognize the same mode, taking the same mode as the overall mode of the robot, otherwise, taking the mode recognized by each joint as the respective local mode.
Further, the acquiring a current signal of the joint motor comprises:
obtaining three-phase current signals of the joint motor and calculating the average value I of the three-phase current signals rms Thereby obtaining the current signal of the joint motor
Further, after current signals of the joint motor are obtained, the complex modal damping natural frequency omega of the r-order mode of the robot is calculated through a random decrement method and a complex exponential method r And complex modal damping ratio ζ r ；
And calculating a frequency response function G (omega) according to the following formula:
wherein n represents the modal total order; { phi r Represents a mode shape factor; { L r Denotes a modality engagement factor; the superscript T represents matrix transposition, the superscript H represents conjugate transposition, and the superscript indicates conjugation; i represents an imaginary unit; lambda [ alpha ] r Representing the complex frequency.
In another aspect of the present invention, a system for identifying a robot mode using a joint motor current signal is provided, including: the device comprises a current sensor, a control unit, an acquisition unit and a processing unit;
the current sensor is arranged in a control cabinet of the robot and used for measuring the current of the joint motor;
the control unit is used for controlling each joint motor to accelerate or decelerate and exciting the modal parameters of the robot;
the acquisition unit is used for acquiring current signals of the joint motor;
the processing unit processes the current signal and identifies a robot mode based on a working mode analysis method OMA.
Further, the robot is a multi-joint robot;
the acquisition unit is also used for respectively acquiring current signals of the joint motors;
the processing unit is further used for identifying the mode of each joint, if all joints identify the same mode, the same mode is used as the whole mode of the robot, and otherwise, the mode identified by each joint is used as the local mode of the robot.
Furthermore, the acquisition unit is also used for acquiring three-phase current signals of the joint motor so as to calculate the average value I of the three-phase current signals rms Thereby obtaining the current signal of the joint motor
Further, after acquiring a current signal of the joint motor, the processing unit calculates a complex modal damping natural frequency omega of an r-order modal of the robot through a random decrement method and a complex exponential method r And complex modal damping ratio ζ r ；
And calculating a frequency response function G (omega) by the following formula:
wherein n represents the modal total order; { phi r Represents a mode shape factor; { L r Denotes a modality engagement factor; the superscript T represents matrix transposition, the superscript H represents conjugate transposition, and the superscript indicates conjugation; i represents an imaginary unit; lambda r Representing the complex frequency.
Generally, by the above technical solution conceived by the present invention, the following beneficial effects can be obtained:
(1) according to the invention, theoretical analysis and experimental verification are carried out, the robot mode is identified by utilizing the joint motor current signal (a current sensor can be arranged in a control cabinet of the robot and does not need to be arranged on a robot body) for the first time, and compared with the existing method of identifying the robot mode by utilizing a vibration signal (a displacement sensor needs to be arranged on the robot body, additional mass is introduced, the accuracy of mode identification is influenced, and the accuracy of mode identification is also influenced due to the reasons that the sensor is not arranged properly, the sensor is not firmly attached to the robot body and the like), the method can avoid adverse effects caused by the installation position of the sensor, so that the accuracy of mode identification is improved; meanwhile, the robot modal in the machining process can be analyzed in real time, the robot modal parameter identification under different poses can be realized, and the operation process is simple.
(2) The current signals of each shaft can be processed respectively and then analyzed integrally to obtain the local mode of each shaft and the overall mode of the robot, and the weak link of the robot can be analyzed by analyzing the local mode and the overall mode. And the local mode and the overall mode under different poses can be analyzed to select a proper pose in the actual processing process. The method can also be used for analyzing the wear state of the robot, estimating the processing quality and the like.
Drawings
FIG. 1 is a schematic diagram of measuring a joint motor current signal;
FIG. 2 is a schematic diagram of a robot joint motor control principle;
fig. 3 is a flowchart illustrating a method for identifying a robot mode by using a joint motor current signal according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
In the invention, the working mode analysis method (OMA) is a method capable of identifying the dynamic characteristics of the structure under the actual operating condition, and the method can identify the mode parameters according to the power spectrum of the output response only based on the output response data. The OMA method can identify the natural frequency and the damping ratio only by the output signal.
The following is a theoretical analysis and derivation process for using joint motor current signals to be able to identify robot modes.
FIG. 1 is a schematic diagram of measuring a joint motor current signal, and FIG. 1 is a robot; 2 is a joint motor; 3 is a current sensor and a signal wire, wherein the current sensor can be connected to a control cabinet of the robot; 4 is a data acquisition instrument; and 5 is used for analyzing the current signal by a computer.
In the present embodiment, a 6-joint robot is taken as an example. And (3) exciting the robot structure by utilizing the idle running of the mechanical arm: firstly, the numerical control G code is used for controlling the acceleration or deceleration motion of each joint motor, and the mechanical arm can generate corresponding inertia force in the process. The various components of the robot structure will produce a vibratory response under the effect of this inertial force. When the joint motor is limited to carry out acceleration and deceleration movement within a relatively small angle, the dynamic characteristics of the robot structure are basically not influenced by the small change of the position of the mechanical arm, meanwhile, the factors such as centrifugal force, Coriolis acceleration and the like in the movement process of the mechanical arm can be ignored, and the robot structure can be regarded as linear and unchangeable. Based on the OMA theory, under the excitation of random inertial force, the kinetic equation can be expressed as:
in the equation [ I]、[C]、[K]The matrixes respectively represent rotational inertia, damping and rigidity matrixes; { theta }, a,
Respectively are angular displacement, angular velocity and angular acceleration column vectors; { T } is the drive torque acting on the robot that is generated when the robot arm is driven in motion. Performing fourier transform on equation (r) to obtain:
{θ(ω)}＝{G(ω)}{T(ω)} ②
according to the principle of mechanical vibration:
wherein:
the modal model in equation (c) is a linear combination of n resonant modes and represents the dynamic characteristics of the robot. Equation (iv) represents the complex frequency. Omega r Representing a complex modal damping natural frequency; zeta r Represents a complex modal damping ratio; { phi r Represents a mode shape factor; { L r Denotes a modality engagement factor; the superscript letter T denotes the matrix transpose, H denotes the conjugate transpose, and the superscript x denotes the conjugate. i represents an imaginary unit.
Through numerical control program control, the joint motor can drive the mechanical arm to move, the moment generated by the motor is used for overcoming friction moment, inertia moment and the like, and under the idle running condition, a moment equation generated by the motor is as follows:
T m (t)＝K t I qm ⑤
T m for useful motor torque, K t Is a torque constant, I qm Is the current signal of the motor, where the subscript m is the column vector component.
Under the condition of full closed loop, vibration displacement information of the mechanical arm is introduced into a current loop of a servo system through a grating ruler, in the method, a current signal is recorded as two parts, one part is a driving torque I q1 Mainly used for overcoming friction moment, inertia moment and the like, and part of the vibration displacement response signals are marked as I q2 . Wherein I q1 Is a low-frequency component in the current signal, I q2 Is a high frequency component in the current signal. According to the frequency bandwidth characteristics of the current loop, the speed loop and the position loop control system, the low-frequency component in the current signal can cause the system to generate response, so that the motor generates torque; the high frequency components do not cause the system to respond, i.e. the motor does not generate torque, but are only detected by the current loop. Equation (v) is improved:
T m (t)＝K t I q1m ⑥
since the swing angle of the robot arm is small, it can be considered that the driving force of the joint motor is proportional to the current. Combining equations (r) and (v) can yield:
fourier transforming the equation to obtain:
{θ(ω)}＝K t {G(ω)}{I q1 (ω)} ⑧
according to OMA, a pseudo-random excitation instruction is designed to control the robot to execute random idle running action, under the action of the random excitation instruction, a joint motor drives a mechanical arm to move back and forth, and modal parameters of the robot are excited by acceleration and deceleration. The essence of the robot is that under the driving action of a joint motor, when the inherent characteristics of the robot are excited, the actual position of the mechanical arm fluctuates (the structure vibrates); such fluctuations will introduce a position loop, a velocity loop, and a current loop to adjust. The vibration information of the robot is responded in the current signal. The control schematic diagram can be simplified to fig. 2.
The transfer relationship between the vibration signal and the current signal can be obtained by fig. 2 as follows:
{I q2 (ω)}＝{H(ω)}{θ(ω)} ⑨
simultaneous equations (II), (III) and (III) are obtained:
by analysis of the transfer function r and before, { I } when the robot is in motion in the randomly excited state q1 (ω) } is the current that produces the driving torque, and can be obtained by measuring the current signal and analyzing the low frequency component. Therefore, the frequency response function is mainly composed of { I } q2 (ω) } and { H (ω) }. { H (ω) } can be obtained by analyzing the velocity loop, the position loop, and the current loop. By analysing the current signal I q2 (ω), a frequency response function { G (ω) } of the robot can be obtained.
Thus, it is explained that the robot mode can be identified using the joint motor current signal.
Based on the above analysis, the present invention provides a method for identifying a robot mode by using a joint motor current signal, as shown in fig. 3, including:
s1, controlling each joint motor to accelerate or decelerate, and exciting the modal parameters of the robot;
s2, acquiring a current signal of the joint motor, processing the current signal based on a working mode analysis method OMA and identifying the robot mode.
Due to the control characteristics of the robot, when only one axis moves, the change of the gravity center of the axis can form a changed load to act on other axes, so that the other axes also have current passing through. Therefore, when the robot carries out random idle running excitation, the current signals of the six axes are correlated. The current signals of each axis can be processed and then analyzed integrally to obtain the local mode of each axis and the overall mode of the robot. It should be noted that, if the same mode is identified in all six axes, the same mode is used as the overall mode of the robot; otherwise, the mode recognized by each axis is used as the respective local mode.
Specifically, the measured current signal is processed as follows. The motor current signals for the six axes can be analyzed separately. The three-phase current signals of the motor can be obtained through the Hall current sensor, and therefore the average value I of the current signals can be calculated rms ，I rms And I q There is the following relationship between:
the collected current signals can be processed by methods such as a random decrement method, an NExT method, an ITD method, an STD method, a complex exponential method and the like, and the natural frequency and the damping ratio of the robot are calculated. The random subtraction method and the NExT method correspond to preprocessing of data, and then processing is performed by a method such as the ITD method, the STD method, or the complex exponential method. The invention is explained by taking a random decrement method and a complex exponential method as examples, wherein the random decrement method is characterized in that a property that the average value of a stable random vibration signal is zero is utilized, an actually measured vibration response signal containing two components of a deterministic vibration signal and a random signal is distinguished, the deterministic signal is separated from the random signal to obtain a free attenuation vibration response signal, and then a time domain identification method can be utilized to identify modal parameters. The complex exponential method is a form in which a free vibration response or an impulse response function according to a structure can be expressed as a sum of complex exponential functions, and then an unknown parameter is determined in a linear method. The method is based on the principle of vibration mode superposition of vibration differential equations, a relational expression between dynamic response and modal parameters is established, and complete modal parameters can be obtained by fitting an impulse response function.
In the present invention, I q1 Is a current generating a driving torque, I q2 Is vibratingA response signal to the displacement. I.C. A q1 Is a deterministic vibration signal, I q2 Including deterministic vibration signals and stochastic signals. Thus, the current signal can be processed by a random decrement method, i.e. I q1 And I q2 The deterministic signal is separated to obtain a free damped vibration response signal.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A method for identifying a robot mode using joint motor current signals, comprising:
controlling each joint motor to accelerate or decelerate, and exciting modal parameters of the robot;
and acquiring a current signal of the joint motor, processing the current signal based on a working mode analysis method OMA and identifying the robot mode.
2. The method of identifying a robot modality using joint motor current signals according to claim 1, wherein the robot is a multi-joint robot;
respectively acquiring current signals of each joint motor and performing modal identification;
and if all joints recognize the same mode, taking the same mode as the overall mode of the robot, otherwise, taking the mode recognized by each joint as the respective local mode.
3. The method for identifying a robot modality using joint motor current signals according to claim 1, wherein the acquiring of the joint motor current signals comprises:
obtaining three-phase current signals of the joint motor and calculating the average value I of the three-phase current signals rms Thereby obtaining the current signal of the joint motor
4. The method for identifying the robot mode according to claim 1, wherein the complex mode damping natural frequency ω of the r-th mode of the robot is calculated by a random subtraction method and a complex exponential method after the current signal of the joint motor is obtained r And complex modal damping ratio ζ r ；
And calculating a frequency response function G (omega) according to the following formula:
wherein n represents the modal total order; { phi r Represents a mode shape factor; { L r Denotes a modality engagement factor; the superscript T represents matrix transposition, the superscript H represents conjugate transposition, and the superscript indicates conjugation; i represents an imaginary unit; lambda [ alpha ] r Representing the complex frequency.
5. A system for identifying a robot mode using a joint motor current signal, comprising: the device comprises a current sensor, a control unit, an acquisition unit and a processing unit;
the current sensor is arranged in a control cabinet of the robot and used for measuring the current of the joint motor;
the control unit is used for controlling each joint motor to accelerate or decelerate and exciting the modal parameters of the robot;
the acquisition unit is used for acquiring current signals of the joint motor;
the processing unit processes the current signal and identifies a robot mode based on a working mode analysis method OMA.
6. The system for recognizing robot modalities using joint motor current signals according to claim 5, wherein the robot is a multi-joint robot;
the acquisition unit is also used for respectively acquiring current signals of the joint motors;
the processing unit is further used for identifying the mode of each joint, if all joints identify the same mode, the same mode is used as the whole mode of the robot, and otherwise, the mode identified by each joint is used as the local mode of the robot.
7. The system for identifying robot modalities according to claim 5, wherein the collection unit is further configured to collect three-phase current signals of the joint motor to calculate a mean I of the three-phase current signals rms Thereby obtaining the current signal of the joint motor
8. The system for identifying robot modes according to claim 5, wherein after the current signals of the joint motors are obtained, the processing unit calculates the complex mode damping natural frequency ω of the r-th mode of the robot by a random decrement method and a complex exponential method r And complex modal damping ratio ζ r ；
And calculating a frequency response function G (omega) according to the following formula:
wherein n represents the modal total order; { phi r Denotes the mode shapeA factor; { L r Denotes a modality engagement factor; the superscript T represents matrix transposition, the superscript H represents conjugate transposition, and the superscript x represents conjugation; i represents an imaginary unit; lambda [ alpha ] r Representing the complex frequency.
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