Study On The Application Of Cyclostationary Theory In Gear And Rolling Ellement Bearing Fault Diagnosis

Rotating machinery is the most widely used machinical equipment. Its fault signals show non-stationary characteristics due to its complex structure, therefore it is not easy to extract its fault feature using the traditional signal processing methods based on the stationary theory. However,when its failure, it will have a cyclical impact or friction due to the physical structure which is symmetry or similar symmetry and the running feature of rotating machinery, and modulation phenomena occurs, therefore its fault signal is essentially cyclostationary, i.e., the statistics of the signal are periodic. It belongs to a special kind of non-stationary signal, and implies cyclostationary property. Aiming at the cyclotationary property of fault signal of rotating machinery, the question for discussion studies cyclostationary methods for the analysis and feature extraction methods for the gear and rolling element bearing fault signal.The vibration signals of the gear and the rolling element bearing which are the fault-prone parts in the most widely used rotating machinery are taken as the study object in this paper. Based on the analysis of the gear and the rolling elements fault signal characteristics, effective cyclostationary analysis methods are sought to extract the fault signal feather through the theory research and the experiment data analysis using cyclic stastics and cyclostationary analysis methods as the main tools. The contents are as follows: from the viewpoint of theoretical analysis and engineering application, the background and significance of the present study are elucidated. A state of art review is thoroughly completed, which consists of the domestic and aboard study status quo, development and tendency of fault diagnosis principle and fault diagnosis methods of the gear and the rolling element bearing and the cyclostationary method application in machinery fault diagnosis. On the base of the brief introduction of cyclostationary phenomena and basic concepts of cyclic statistics, the second order cyclostaionary analysis demodulation and denoise methods, and the digital realization methods are researched. The fault principles and characteristics are analysed, and the cyclostationary analysis methods are applied in the fault characteristics extraction of the gear and rolling element bearing fault signal.The theory research and the experiment data analysis verify that the fault diagnosis methods based on the cylostationarity are more helpful than those based on the stationary hypothesis in extracting the fault characteristics. To some extent, the better results of experiment data analysis also verify the ability of cyclic autocorrelation function, cyclic spectral density, and degree of cyclostationarity to extract the rotating machinery fault characteristics.