Algorithm Study On Denoising And Feature Extraction Of Gearbox Fault Vibration Signal

As an essential common component which can interconnect and transmit the power in mechanical equipment,gearbox has been widely used in modern industrial equipment,such as metal cutting machine tool, aviational and powerful system, agricultural machinery, transport machinery,metallurgical machinery. As mechanical drive,the running state of gearbox directly affect the performance of mechanical drive system. So that it is very important to research the technology and method about fault diagnosis of gearbox,detect state and diagnose the fault of gearbox,and ensure gearbox in normal working state.Fault diagnosis of gearbox is state information by analyzing and processing the gearbox is operated, the quantitative recognition technology state, and amulti-disciplinary comprehensive technology in diagnosis of abnormal fault state. Vibration signals of the gearbox contains the working state of a huge amount of information, the fault diagnosis of gearbox vibration signal is a kind of effective method. Application of vibration signal analysis and fault diagnosis of the gearbox method, denoising, feature extraction and recognition of fault type are three of the most important problems, especially in fault feature extraction, it directly affects the accuracy of diagnosis results, has been recognized as the key link in fault diagnosis. From the point of engineering application, this thesis systematically investigated the fault feature extraction and fault vibrational signal denoising methods of the diesel engine applying spectral kurtosis, golden section, Nelder-Mead, wavelet analysis,FFT,PSO,SRS,SOT,etc.This thesis mainly studies the optimal filtering vibration signal of gearbox fault denoising and fault transient pulse feature extraction algorithm.The main contents are as follows:(1) This thesis analyses the principle of the vibrational signal analysis method of gearbox to provide theoretical support for the follow-up study on vibration signal denoising and fault feature extraction algorithm.(2) In order to solve the problem that the single golden section has slow speed this thesis presents an accelerated one-dimensional search algorithm.(3) In order to solve the problem that the single multi-dimensional algorithm has slow convergence speed and easily fall into local extremum,where the objective function is kurtosis maximum, this thesis presents an adaptive filtering algorithm based on one-dimensional search-multi-dimensional search method (parameter coarse-parameter tuning). According to the principle of frequency domain analysis of vibration signal analysis and wavelet transform,, using two different filtering methods, Chebyshev bandpass filtering and Morlet wavelet filtering.Parameters of Chebyshevbandpass filter and Morlet wavelet filter are separately optimized by spectral kurtosis-golden section-Nelder-Mead and golden section-Nelder-Mead,then denoising the fault vibrational signal of gearbox.(4) In the simulation study process of one dimension-multidimensional search hybrid optimized algorithm,according to the combination of one dimensional searchand multi-dimensional search we use several different algorithms to optimizing the parameters,such as spectral kurtosis,GA, golden section and Nelder-Mead.(5) On the basis of previous study the particle swarm optimization algorithm is applied to denoising the fault vibrational signal of gearbox.This thesis proposed a hybrid algorithm that effectively reduce the searching range of PSO, and save the optimized time based on accelerated one dimensional search and PSO.lt is used for parameters optimization of Chebyshev band-pass filter and Morlet wavelet filter,then denoising the fault vibrational signal of gearbox.(6) In order to transient fault feature extraction that can reflect gearbox information changes and future development trend of the fault,the shock response spectrum analysis and the transient analysis are applied to extract fault feature of gear in the gearbox, and successfully extracting three transient characteristics indexes which can measure the severity of fault, respectively shock response spectrum index SRS,natural frequency con and Oscillation damping ratio ζ in the gear meshing system.