Frequency Band Entropy And Its Application In Rolling Element Bearing Fault Diagnosis

With the rapid development of technology and industry, mechanical equipment has become more and more huge, complex, high-speed, effective, and heavy-load while they must face more and more harsh running conditions. Once they fail unexpectedly, the unexpected failure can increase maintenance cost, reduce production efficiency, and sometimes cause significant economic losses, or even catastrophic accidents. Therefore, it is necessary and important to realize effectively equipment condition monitoring and fault diagnosisHow to effectively extract features of the equipment running status and accurately determine the fault type has been a hot research field of fault diagnosis, and new methods and theory come out one after another to enrich and improve the mechanical fault diagnosis technology. Taking the rolling element bearing as the research object, this paper has proposed frequency band entropy(FBE) method and its application in fault diagnosis has been studied. The writer is aiming at providing a new indicator for the rolling bearing condition monitoring, and a new method for fault diagnosis signal preprocessing, the paper mainly including the following aspects:(1) From the viewpoint of theoretical analysis and engineering application, this paper's research background and significance of present study are elucidated. A state of the art review is thoroughly completed, which consists of fault diagnosis of machinery and equipment, the rolling bearing fault diagnosis, time-frequency analysis and information entropy theory. The issues to be resolved are summarized and the research content of this paper are established .(2) Several time-frequency analysis methods and information entropy theory which the whole theory is based on are described, then the spectral kurtosis method is introduced to propose the frequency band entropy. Frequency band entropy is defined as the complexity (or uncertainty)of the signal on a particular frequency (or within a particular frequency band), the FBE algorithm is given. At the last the FBE concept is extended from the viewpoint of filtering.(3) The vibration principle and failure characteristics of rolling bearings are described. The possibility of rolling bearing condition monitoring for FBE is discussed as well as its robustness and insensitivity to singular points. Then it's applied to the whole life data of rolling element bearing, and its performance in various stages of degradation is studied. Rolling element bearing fault test and accelerated fatigue life test are presented to support the above theory, and the analysis of experimental data indicates that FBE can be used as an effective complement of the existed condition monitoring indicators.(4) The determination of band-pass filter center frequency of resonance demodulation is a difficult problem. Time-frequency based FBE is used to solve this problem. For STFT-based FBE, parameters such as the discrete frequency points, analysis window length, window function are discussed; for wavelet packet transform-based FBE, the wavelet packet decomposition level and wavelet packet functions are discussed. Finally, the two methods are used in the simulation and test rolling element bearing fault diagnosis. The analysis results show that the FBE based on time-frequency analysis is able to accurately determine the resonance of the signal and enhance the effect of band-pass filter and envelope demodulation.(5) The method of combining FBE and genetic algorithm is proposed for the optimization of the resonance demodulation band-pass filter design. Minimum FBE as the genetic algorithm optimization goal, by selecting, crossover and mutation operations, genetic algorithm searches the optimal combination of center frequency and bandwidth within the range, then optimal filter is designed. It is proved by the analysis of the simulated signals and different signal to noise ratio experimental data that this method can effectively determine the filter center frequency and bandwidth, thereby improving the signal to noise ratio and the diagnosis of bearing faults.