Envelope analysis is an effective technique of fault diagnosis for rolling element bearings (REBs). However, envelope analysis needs to select an appropriate frequency band of the signal. Numerous selection methods have been investigated, such as spectral kurtosis (SK) and wavelet packet kurtogram (WPK), which are based on kurtosis. Nevertheless, existing approaches are sometimes unable to identify bearing faults due to the contamination of discrete and random noises. In this paper, a novel method of fault diagnosis for bearings is proposed, which accumulates all or part of sub-band signals’ envelope spectrums at a given level in wavelet packet rather than demodulates one selected frequency sub-band signal. Two simulated signals and a real signal are analyzed to test the performance of the novel method. In the first case, stochastic impulses are added into the simulated outer race fault signal. The analysis shows that the novel approach is more robust to stochastic impulses than the other two methods such as SK and WPK. In the second case, the simulated signal containing two outer race faults from different REBs is analyzed using the three methods, respectively. The results show that the novel approach captures more useful information and detects the two different REBs’ faults contained in the same signal more effectively. Furthermore, the effectiveness of the novel method is validated by identifying the characteristic fault frequency of the real REB.
The multisource impact signal of rolling bearings often represents nonlinear and nonstationary characteristics, and quantitative description of the complexity of the signal with traditional spectrum analysis methods is difficult to be obtained. In this study, firstly, a novel concept of local frequency is defined to develop the limitation of traditional frequency. Then, an adaptive waveform decomposition method is proposed to extract the time-frequency features of nonstationary signals with multicomponents. Finally, the normalized Lempel–Ziv complexity method is applied to quantitatively measure the time-frequency features of vibration signals of rolling bearings. The results indicate that the time-frequency features extracted by the proposed method have clear physical meanings and can accurately distinguish the different fault states of rolling bearings. Furthermore, the normalized Lempel–Ziv complexity method can quantitatively measure the nonlinearity of the multisource impact signal. So, it supplies an effective basis for fault diagnosis of rolling bearings.
The multi-source impact signal of reciprocating compressor often represents nonlinear and non-stationary. For this reason, the fault features of the signal are difficult to quantitatively describe using conventional signal processing methods. In this paper, a novel adaptive waveform decomposition method was proposed to convert the strong non-stationary multi-component signal into stationary single-component signal. Subsequently, the signal was denoised with threshold-based mutual information to protect from being interfered by the noise. Finally, to measure the nonlinearity of reciprocating compressor signals in four states (normal valve sheets, gap valve sheets, fractured valve sheets, and bad spring), the normalized Lempel-Ziv complexity indexes were employed. The results reveal that the proposed method is capable of extracting the different faults states of reciprocating compressor accurately, which supplies a measure of fault diagnosis and maintenance strategy for the reciprocating compressor.
Rubbing is one of the most common and significant faults that exist in the rotor system. It exhibits extremely complicated dynamic behavior. Existing dynamic models are primarily based on the symmetrical rotor structure, in which the oil film forces at both ends of support are considered identical. However, in practice, the oil film force may be differently affected by multiple factors (e.g., viscosity of lubricants, the thickness of oil film, and clearance of journal bearing). In this study, a novel dynamic model of the rubbing rotor system under asymmetric oil film force was developed. Furthermore, based on the nonlinear rotor dynamic theory, its dynamic behavior with different parameters was analyzed, and the corresponding chaotic features were extracted. The results indicated that the evolution law of chaotic motion was more complicated, and the chaotic region of system response was obviously wider under the asymmetric oil film force than the symmetrical oil film force.
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