Research On Key Techniques For Fault Diagnosis Of Rolling Element Bearing In Heavy Noise

The condition monitoring of rotating machinery is important in terms of system maintenance and process automation. Rolling element bearing failure is one of the foremost causes of breakdown in rotating machinery. Such bearing failure can be catastrophic in certain situations such as in automatic processing machines. So it is very significant to research on bearing condition monitoring and fault diagnosis techniques, especially for bearing incipient fault. The practice shows that the envelope demodulation method based on Hilbert transformation offers a reliable method for the bearing fault diagnosis with modulation phenomenon. Aiming to address bearing fault diagnosis in heavy noise, new envelope demodulation methods were explored in this dissertation. The main contributions are described as follows:In terms of fault mechanism of bearing, dynamic behaviors of rolling element bearings with surface waviness, local defects, radial clearances and other factors considered were further perfected based on some existing models. Since any bearing has surface waviness to a certain degree due to the manufacturing process, surface waviness and other factors should be taken into account in simulating bearing local defects vibration signals, and this was well coincide with the. real-life situations. The accordance of vibration properties obtained from the mathematical model with those from the experimental data verified the validity of the proposed model.In the viewpoint of signal analysis, Morlet wavelet and Harmonic wavelet, in nature, belong to the complex analytical band-pass filter, and are usually used to extract vibration signal envelopes. Aiming at the insufficiency on Morlet wavelet and Harmonic wavelet, a novel complex analytical band-pass filter was constructed with the Gibbs phenomenon occurring slightly, the characteristics of nearly box on frequency domain, and rapid decay on time domain. On this basis, a comb-filter and envelope-demodulator method based on combining complex analytical band-pass filters was proposed. This technique integrates comb-filtering and envelope-demodulating. The experiment results show that a clear, noiseproof and fault-tolerant envelope spectrum could be obtained with the proposed method. The S-transform (ST), as extension to the ideas of the short time Fourier transform and the wavelet transform, could be applied in the envelope demodulation. Multi-resolution ST envelope spectrum was proposed to analyze bearing vibration signal with cycle-modulating feature efficiently, and the calculation method was presented correspondingly. In order to restrain noise within pass-band, the novel method for detection, enhancement and reconstruction of principal periodic component in envelope based on Multi-resolution ST envelope spectrum and singular value ratio (SVR) spectrum was adopted. Owing to the improved approach was employed in reconstructing the matrix of singular value decomposition (SVD), the precision frequency determination was enhanced. It was shown that the new de-noising method could reduce the noise and extract the period of the signal effectively, and could be effectively applied in the vibration envelope extraction for a roller bearing system in different noise level.In comparison with other suppression noise methods, because signals could be strengthened by noise in stochastic resonance (SR) system, the SR effect has particular advantages on enhancing and detecting weak signals. In terms of numerical solution for a SR model, an improved solution based on a fourth order Runge-Kutta algorithm was presented to enhance the resonance effect. However, the optimization of system parameter and noise intensity is complicated and difficult in a SR system. A novel genetic adaptive SR algorithm, used to optimize system parameter and noise intensity, was presented here. Aiming at traditional adiabatic elimination SR in small parameters is not adapt to engineering weak signal detection in large parameters, based on the researches of re-scaling, frequency-shifted and re-scaling methods, a method based on the S-transform and rescaling was presented for amplitude modulated signal detection. The effectiveness of the proposed method was demonstrated on both simulation signals and real vibration signals of bearing. It was shown to be superior to the spectrum analysis and the common envelope demodulation analysis. The method could extract bearing fault feature in heavy noise.It was shown that the proposed envelope-demodulation methods in this dissertation were demonstrated on their validity and superiority to the common envelope demodulation methods. It's worth reling that they would have a promising application for the fault diagnosis of rolling element bearings.