A method for fault diagnosis and location of robot rv reducer

Abstract

The invention relates to a fault diagnosis and positioning method for a robot RV reducer, in particular to a fault diagnosis and positioning method for a robot RV reducer based on signal adaptive splitting. The present invention comprises the following steps: acquiring the acoustic emission signal; adaptively splitting the acoustic emission signal; performing an initial frequency domain transformation on the signal; using a recursive neural network as a training model to train the split and processed signal; The signal is judged and combined with the angle data to locate the fault point. The invention is proposed on the basis of fully considering the operation mechanism of the RV reducer for the robot, and can accurately and quickly diagnose corresponding faults, improve the maintenance efficiency of the robot, and reduce operating costs.

Description

technical field [0001] The invention relates to the field of RV reducer fault diagnosis, in particular, it relates to a method for estimating the remaining life of an RV reducer and a method for detecting its wear degree. Background technique [0002] RV reducers are widely used in power transmission units of robots, precision instruments, etc. When the RV reducer is worn or its performance declines, it will seriously affect the quality of products produced or processed by robots or precision equipment, and even in the field of medical equipment. affect the health of patients. Therefore, the fault diagnosis and remaining life estimation of RV reducer have very important engineering significance and practical value. [0003] Acoustic emission, as a detection method for detecting weak stress signals inside or on the surface of materials, can detect changes in the surface smoothness and wear of the rotating parts inside the RV reducer due to wear. Compared with the traditiona...

AI Technical Summary

Problems solved by technology

Compared with the traditional use of vibration signals to detect the faults of rotating machinery parts, vibration signals are often detected when the degree of wear is relatively large. At this time, the RV reducer and its application scenarios that require high precision have already been used. Failure to avoid losses in a timely and effective manner

However, because the acoustic emission signal is at high frequency, the signal sampling rate is high, the data volume is large, and the signal characteristics are not obvious, which restricts the development of acoustic emission detection in the field of mechanical equipment wear detection, and cannot effectively and quickly obtain detection results.

[0004] The main shortcomings of these methods are related to the detection timeliness and signal processing speed, which directly affects the development of acoustic emission detection technology in the field of RV reducer detection.

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