Gearbox Fault Diagnosis, Based On Wavelet Analysis

With the development and progress of current world's science and technology, mechanical equipments play a greater and greater role in the practical producing and they can accomplish tasks which people can not imagine in the harsh environment. However, they will also fail to work sometimes. In this way, they will bring great losses to the enterprise. In order to reduce the loss rate caused by the fault diagnosis of equipments, people invent the fault diagnosis technology of equipments and its purpose is to diagnose and prevent failures quickly.The source of this paper is JCMFVD60T hydraulic transmission forklift produced by GanZhou Five Rings Machine Corporation. It applies the Wavelet analysis theory to carry out researches on the box's fault characteristic signals aiming at the intense vibrations and excessive noise appearing in the internal of the transmission.This paper is adopting Wavelet analysis theory to carry out fault diagnosis. Firstly, It analyzes the vibration mechanism and failure mode of the internal gearbox gear, shaft and bearing ,and also study the theory of signal analysis including the continuous wavelet transform, discrete wavelet transform, multi-resolution analysis theory, Mallat algorithm and wavelet packet decompositionSecondly because Signal diagnostics includes time domain and frequency domain analysis, through analyzing and making comparison of the advantages and disadvantages of two methods, we can sure that the behind work uses frequency-domain analysis is the best, then we transform the experimental results of signal from time domain into the Time-frequency domain and analyze it.Finally, in diagnosis process we apply the wavelet analysis in MATLAB application to reduce noise of signals and select wavelet packet to decompensate and extract fault characteristic frequency by Power spectrum. Though the analysis we can conclude that meshing frequency of the gear is just the fault characteristic frequency which indicates that there are some local defects of the gear.