Analysis On The Fault Signal Of RV Series Worm Gear Reducer

Rotating machinery fault diagnosis has been a hot research, and it is prone to failure in the harsh working environment for the worm wheel worm gear reducer. In this paper, the signal analysis techniques of worm gear fault are explored to seek a more simple, effective method for the detection of worm wheel worm gear reducer. In this paper, using the vibration detection and acoustic emission detection of two kinds to detect the worm gear fault, the main work focuses on the following contents:Firstly, studying the characteristics of RV series worm gear reducer, mechanical structure, vibration mechanism, common fault types of worm gear, fault causes and worm gear worm gear fault signal characteristics. And preliminary application of traditional signal analysis technology, the speed reducer vibration signals and acoustic emission signal in time-frequency domain, frequency domain and time domain analysis of the characteristics.Secondly, According to the characteristics of vibration signals and acoustic emission signals, combining the methods of wavelet analysis and the Hilbert-Huang transform to analysis and process the worm gear fault signals. Through the analysis and processing of simulation signal, solved the problem of wavelet analysis of choosing wavelet base, decomposition level and threshold denoising, and proposed using the autocorrelation algorithm selected the experience of Hilbert-Huang Transform in modal decomposition of the intrinsic mode functionsThirdly, In the experimental stage, in order to adopt worm gear set fault signal, to built the worm gear reducer test experiment platform, using the signal acquisition device of the vibration and acoustic emission to acquisition the worm gear fault signals in different fault conditions, at the same time according to the change of the worm wheel tooth faults, using JD45+gear measuring instrument to measurement the worm gear geometry parameters. By analyzing test data of worm gear reducer failure in normal and verify, wavelet analysis and the Hilbert-Huang transform combined can effectively restrain the background noise, extracting the feature of gear fault signal.Finally, compared to the two analysis techniques vibration signal detection and acoustic emission testing, two methods based on the characteristics of the collected signal is different, and each has advantages and disadvantages, in engineering application, based on the actual needs of the different requirements to select reducer fault detection method and signal analysis technology.