CN111975784A - Joint robot fault diagnosis method based on current and vibration signals - Google Patents
Joint robot fault diagnosis method based on current and vibration signals Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
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- B—PERFORMING OPERATIONS; TRANSPORTING
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Abstract
The invention discloses a joint robot fault diagnosis method based on current and vibration signals, which comprises the steps of firstly picking up a motor current signal and a joint vibration signal of a joint to be researched of a robot; filtering the motor current signal to extract the instantaneous frequency of the joint motor current signal; calculating a real-time rotation angle of a joint motor shaft by using the instantaneous frequency extracted from the joint motor current signal; carrying out low-pass filtering processing on the vibration signal; determining the maximum order ratio range and equally dividing the rotation angle to obtain an equal-angle sampling time sequence and carrying out equal-angle sampling on the filtered vibration signal; finally, Fourier transformation is carried out on the equal-angle sampling sequence of the vibration signals to obtain a robot joint vibration signal order spectrum and the robot joint vibration signal order spectrum is analyzed to realize robot joint fault diagnosis; the first-order frequency required by vibration order ratio analysis is extracted very conveniently and quickly, and vibration signal stabilization processing can be completed only by ensuring synchronous acquisition of vibration and current, so that robot joint fault diagnosis and state detection are completed.
Description
Technical Field
The invention relates to a joint robot fault diagnosis method based on current and vibration signals, and belongs to the technical field of state monitoring and fault diagnosis of industrial robots.
Background
The six-degree-of-freedom serial industrial robot has very wide application in industrial automation production, and parts abrasion caused by long-time operation and the occurrence of some emergencies can cause the robot to stop operating suddenly, so that the operation of a production line is damaged, and loss is caused to enterprises. The main devices of the robot joint are a servo motor and a reducer, and the monitoring of the robot and the traditional motor and reducer state monitoring method can be used for reference. The traditional motor state monitoring adopts the vibration signal spectrum analysis; for a six-degree-of-freedom series robot, a vibration signal is a typical non-stationary signal, and is generally firstly subjected to stationary processing, and the stationary processing mode generally adopts order ratio tracking. However, for the robot, the key phase pulse is difficult to obtain, the joint reducer has a complex structure, and the time-frequency instantaneous frequency extraction difficulty is high, so that the order ratio analysis from the two aspects has a plurality of problems, and the instantaneous frequency extracted by the current signals acquired synchronously replaces the time-frequency analysis to obtain the instantaneous conversion frequency relatively easily.
When the robot operates, the rotating speed of the robot is always in a changing state, and joint vibration signals of the robot are typical non-stationary signals; the robot joint structure is complex, so it is not practical to realize order tracking through hardware. Meanwhile, the joint servo motor encoder feedback pulse acquisition difficulty is high, and the cost is high. In addition, because the robot joint comprises a motor, a speed reducer and other parts, and each joint is in a connection state, the frequency conversion of the motor shaft in a frequency spectrum is not obvious when the robot joint vibrates a signal, the extraction difficulty is high, an equiangular sampling sequence is difficult to obtain, and the order ratio analysis of the vibration signal is difficult. The robot joint motor current signal acquisition cost is low, the acquisition is convenient, and the order analysis by using the current signal to extract the instantaneous frequency has great significance.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a joint robot fault diagnosis method based on current and vibration signals, which does not need key phase signals and extraction of instantaneous frequency of the vibration signals, and can complete the order analysis of the vibration signals only by synchronously acquiring the current and the vibration signals and extracting the instantaneous frequency of the current signals.
The vibration signal order ratio analysis method based on the current comprises the following specific steps:
(1) synchronously acquiring a motor current signal I (t) and a vibration signal S (t) of an ith joint of the robot in the process of rotating any angle, wherein t is sampling time;
acquiring a motor current signal I (t) of an ith joint of the robot through a current sensor, and acquiring a vibration signal S (t) of the ith joint of the robot through an acceleration sensor;
the arbitrary angle refers to an arbitrary value within an angle range allowed by a joint, and the angle range is described on a robot specification or a robot demonstrator;
(2) filtering and deburring the current signal I (t) by adopting a method of combining zero-phase filtering with singular value denoising to obtain a filtered current signal I1(t)；
(3) By the formula
Calculating the current signal I1(t) phase phi (t) by the formula
Calculating the current signal I1(t) instantaneous frequency f (t);
(4) by the formula
Wherein p is the number of pole pairs of the motor, the instantaneous rotating speed n (t) of the motor shaft is obtained through calculation, and the instantaneous rotating speed n (t) is obtained through a formula
Calculating to obtain an instantaneous rotation angle theta (t) of the motor shaft;
(5) by the formula
Calculating an equal-angle sampling interval delta theta; maximum order ratio vmaxIs an integer greater than or equal to 1;
(6) sampling the instantaneous rotation angle theta (t) according to the equal-angle sampling interval delta theta obtained by calculation in the step (5) to obtain an equal-angle instantaneous rotation angle sequence theta1(t)；
(7) Cubic spline interpolation is carried out on the instantaneous corner theta (t) to obtain an equal-angle instantaneous corner sequence theta1(T) time series T;
(8) carrying out low-pass filtering on the vibration signal S (t) acquired in the step (1) to obtain a filtered signal S1(t) for S1(T) carrying out cubic spline interpolation to obtain a vibration sequence S of the time sequence T2(t)；
(9) By the formula
Maximum order ratio vmaxIs an integer greater than or equal to 1; calculating a sequence of order ratios L, where n is the vibration sequence S2(t) length;
(10) for vibration sequence S2(t) performing Fast Fourier Transform (FFT) to obtain a ratio spectrum sequence S3(t)；
Taking the order ratio sequence L as an abscissa, and taking the order ratio spectrum sequence S3(t) drawing a scale spectrum with the first m values as vertical coordinates, wherein the m value is half of the length of the scale sequence L, and if L is an odd number, rounding the half of the length of the scale sequence L downwards;
and observing whether fault characteristic order ratios of all parts of the robot joint exist in order ratio components in the order ratio spectrum, if so, indicating that the parts have faults, and if not, indicating that the joints have no faults, thereby completing vibration signal order ratio analysis and realizing robot joint fault diagnosis and state detection.
The invention has the beneficial effects that:
1. the current signal instantaneous frequency extraction approach is superior to that of key phase pulse calculation and extraction from vibration signal time frequency spectrum;
2. the method can conveniently and quickly realize the order ratio analysis of the vibration signals;
3. the first-order frequency required by vibration order ratio analysis is extracted very conveniently and quickly, and vibration signal stabilization processing can be completed only by ensuring synchronous acquisition of vibration and current, so that joint state detection and fault diagnosis of the robot are realized.
Drawings
FIG. 1 is a schematic view of a robot configuration;
FIG. 2 is a schematic diagram of the original waveform of the current signal I (t) in the state of 60 degrees of articulation 2;
fig. 3 is a schematic diagram of an original waveform of a vibration signal s (t) in a state of 60 ° of joint movement of fig. 2;
FIG. 4 is a current signal I (t) after filtering for the current signal I (t) at 60 degrees of articulation 21(t) a waveform diagram;
FIG. 5 is a current signal I (t) after filtering for a current signal I (t) at 60 degrees of articulation 21(t) a waveform of the instantaneous frequency f (t);
fig. 6 is a waveform diagram of an instantaneous rotation angle θ (t) calculated by an instantaneous frequency f (t);
FIG. 7 is a sequence S after resampling of the vibration signal2(t) a waveform diagram;
FIG. 8 is a schematic diagram of a vibration signal scale spectrum;
in fig. 1: the system comprises a 1-1 st joint, a 2-2 nd joint, a 3-connecting arm I, a 4-3 rd joint, a 5-4 th joint, a 6-connecting arm II, a 7-5 th joint, an 8-6 th joint, a 9-electric cabinet, a 10-current sensor and an 11-acceleration sensor.
Detailed Description
The present invention is further illustrated by the following examples, but the scope of the invention is not limited to the above-described examples.
Example 1: the vibration signal order ratio analysis method based on the current comprises the following steps:
the Qianjiang QJR6-1 welding robot is adopted, and fig. 1 is a schematic structural diagram of the robot, which comprises a joint I1, a joint II 2, a connecting arm I3, a joint III 4, a joint IV 5, a connecting arm II 6, a joint V7, a joint VI 8, an electric cabinet 9, a current sensor 10 and an acceleration sensor 11; the implementation object is a joint II, the motion angle is 60 degrees, and the specific operation flow is as follows:
1. in the state that a single joint of a second joint moves by 60 degrees, a current sensor is adopted to obtain a motor current signal I (t) of the second joint of the robot, as shown in figure 2, an acceleration sensor 11 is adopted to obtain a vibration signal S (t) of the second joint, as shown in figure 3, t is sampling time, an acquisition card is NI9234, acquisition software is SignalExpress, and sampling frequency is 25600 Hz;
2. the method for realizing zero-phase filtering and singular value denoising by utilizing matlab software is used for carrying out filtering and deburring processing on the current signal I (t) to obtain a filtered current signal I1(t); wherein the zero phase filter parameters are as follows: chebyshev type 1, 5-order, 0.2 cutoff low pass, 0.1 equal ripple; a time-frequency matrix used in the singular value denoising process is obtained through short-time Fourier transform, the length of a short-time Fourier transform window is 1024, and the step length is 128; the results are shown in FIG. 4;
the following calculation processes and output results are all completed in matlab software;
3. by the formula
Calculating the current signal I1(t) phase phi (t) by the formula
Calculating the current signal I1(t) instantaneous frequency f (t), the results are shown in FIG. 5;
4. by the formula
Wherein the number p of pole pairs of the motor is equal to 5, the instantaneous rotating speed n (t) of the motor shaft is obtained through calculation, and the instantaneous rotating speed n (t) is calculated through a formula
The instantaneous rotation angle θ (t) is calculated, and the result is shown in fig. 6;
5. taking the maximum order ratio vmaxEqual to 30, by formula
Calculating equal-angle sampling interval delta theta to be equal to 6; sampling the instantaneous rotation angle theta (t) according to the equal-angle sampling interval of 6 degrees to obtain an equal-angle instantaneous rotation angle sequence theta1(t); cubic spline interpolation is carried out on the instantaneous turning angle theta (t) by utilizing matlab software to obtain the equal-angle instantaneous turning angle theta1A time series T at (T);
6. calculating the frequency f corresponding to the highest rotation speed of the motor1Namely: converting the unit r/min of the rotating speed into degree/s, and realizing the cutoff frequency f by utilizing matlab software1The low-pass filter filters the vibration signal S (t) to obtain a filtered vibration signal S1(t); realization of S pair by utilizing matlab software1(T) carrying out cubic spline interpolation to obtain a vibration sequence S at the time sequence T2(t), as shown in FIG. 7;
7. by the formula
Calculating a sequence of order ratios L, where n is the vibration sequence S2(t) has a length equal to 817;
8. vibration sequence S by utilizing matlab software2(t) performing Fast Fourier Transform (FFT) to obtain a ratio spectrum sequence S3(t); taking the order ratio sequence L as an abscissa, and taking the order ratio spectrum sequence S3(t) (m is half of the length of the sequence L equal to 408.5, and 408)) as the ordinate, and a scale spectrum is plotted, and as shown in FIG. 8, the extracted scale spectrum is used for spectrum analysis, and the scale spectrum of 1, 2, 3, 4, and 16 orders are observedAnd the specific components respectively correspond to the order corresponding to the conversion frequency of the motor shaft of the second joint, the order corresponding to the 2, 3 and 4 frequency doubling of the conversion frequency and the order corresponding to the meshing frequency of the sun wheel and the planet wheel, and other obvious orders do not appear in addition, so that the second joint is judged to have no fault. The method is used for carrying out order ratio analysis on different joints to realize state monitoring and early fault diagnosis on each joint arm of the robot, and the condition that the robot is suddenly stopped due to the expiration of the service life of parts or some emergencies to damage a production line and influence production is prevented.
Claims (3)
1. A joint robot fault diagnosis method based on current and vibration signals is characterized by comprising the following specific steps:
(1) synchronously acquiring a motor current signal I (t) and a vibration signal S (t) of an ith joint of the robot in the process of rotating any angle, wherein t is sampling time;
(2) filtering and deburring the current signal I (t) by adopting a method of combining zero-phase filtering with singular value denoising to obtain a filtered current signal I1(t)；
(3) By the formula
Calculating the current signal I1(t) phase phi (t) by the formula
Calculating the current signal I1(t) instantaneous frequency f (t);
(4) by the formula
Wherein p is the number of pole pairs of the motor, the instantaneous rotating speed n (t) of the motor shaft is obtained through calculation, and the instantaneous rotating speed n (t) is obtained through a formula
Calculating to obtain an instantaneous rotation angle theta (t) of the motor shaft;
(5) by passingFormula (II)
Calculating an equal-angle sampling interval delta theta; maximum order ratio vmaxIs an integer greater than or equal to 1;
(6) sampling the instantaneous rotation angle theta (t) according to the equal-angle sampling interval delta theta obtained by calculation in the step (5) to obtain an equal-angle instantaneous rotation angle sequence theta1(t)；
(7) Cubic spline interpolation is carried out on the instantaneous corner theta (t) to obtain an equal-angle instantaneous corner sequence theta1(T) time series T;
(8) carrying out low-pass filtering on the vibration signal S (t) acquired in the step (1) to obtain a filtered signal S1(t) for S1(T) carrying out cubic spline interpolation to obtain a vibration sequence S of the time sequence T2(t)；
(9) By the formula
Wherein N ═ 0, 1, 2, 3,. and N-1, maximum order ratio vmaxIs an integer greater than or equal to 1, calculating a sequence of order ratios L, where n is a vibration sequence S2(t) length;
(10) for vibration sequence S2(t) performing fast Fourier transform to obtain a ratio spectrum sequence S3(t)；
Taking the order ratio sequence L as an abscissa, and taking the order ratio spectrum sequence S3(t) drawing a scale spectrum with the first m values as vertical coordinates, wherein the m value is half of the length of the scale sequence L, and if L is an odd number, rounding the half of the length of the scale sequence L downwards;
and observing whether fault characteristic order ratios of all parts of the robot joint exist in order ratio components in the order ratio spectrum, if so, indicating that the parts have faults, and if not, indicating that the joints have no faults, thereby completing vibration signal order ratio analysis and realizing robot joint fault diagnosis and state detection.
2. The joint robot fault diagnosis method based on current and vibration signals according to claim 1, characterized in that: and acquiring a motor current signal I (t) of the ith joint of the robot through a current sensor.
3. The joint robot fault diagnosis method based on current and vibration signals according to claim 1, characterized in that: and acquiring a vibration signal S (t) of the ith joint of the robot through an acceleration sensor.
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| CN113405795A (en) * | 2021-06-22 | 2021-09-17 | 昆明理工大学 | Weak fault identification method for joint RV reducer |
| CN113985276A (en) * | 2021-10-18 | 2022-01-28 | 上海电气风电集团股份有限公司 | Fault diagnosis method and device of wind generating set |
| CN114441125A (en) * | 2021-12-24 | 2022-05-06 | 北京化工大学 | Non-contact type turbine machinery high-rotating-speed blade vibration multi-mode decomposition method |
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| CN114608821A (en) * | 2022-03-01 | 2022-06-10 | 北京辰宇航康科技有限公司 | Method and device for determining order spectrum of vibration signal of rotating machine |
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| 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 |
| 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 |
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