The Application Of Fault Diagnosis In Mine Elevator Based On Wavelet Analysis

Mine elevator is the rotating machinery under variable working condition, which can produce non-stationary vibration signal in its working process. The signal includes some characteristic information that can reflect running state of mechanical equipment, making use of those signals effectively and carrying out fault diagnosis is very important to ensure that mine elevator can run reliably and economically.In this paper, a deep study of wavelet analysis has been held on, which is the edge technology in the field of signal processing, achieving the fault diagnosis of mine elevator based on wavelet analysis and power spectrum analysis. Firstly, the paper summarizes common fault types, vibration characteristics and common methods, performs the vibration testing to the JKM3.25×4(Ⅱ) mine elevator. Secondly,the paper uses the different wavelet basic functions to detect and analyze vibration signal based on the theory of wavelet analysis, finding the wavelet basic functions which adapts to analyzes fault signal. Finally, the paper writes program uses the software MATLAB to analyze vibration signal combining wavelet analysis with power spectrum analysis, extracts the characteristic information and diagnoses the fault cause.The study shows that wavelet analysis has incomparable advantage over classical Fourier analysis, which is a perfect tool to process non-stationary signal. It can realize simultaneous localization between time-domain and frequency-domain by decomposing and reconstructing signal, and have the obvious superiority on extracting characteristic information of weak signal. An effective method of fault diagnosis is carrying out power spectrum analysis to restructure signal based on wavelet transform.