Fault Detection And Diagnosis Of Rotating Machinery

Rotating machinery is the key equipment in mechnical industry and it plays an important role in the aerospace, petroleum, electricity, iron, steel and other industry applications. Rolling element bearings are one of the key parts in rotating machinery equipments, whose running condition decides the operating conditions of machineries directly. In the complex working envirements of machinery with significant coupling effects among mechanical equipments, the traditional envelope spectrum analysis or Hilbert-Huang transform analysis usually cannot work efficiently. To solve the aforementioned problems, we have studied vibration faults in various rolling element bearings and proposed several improved envelope analysis methods that can eleminate the disadvantage of traditional methods. The main content and contributions are represented as followed:1. The independent component analysis (ICA) technology is employed and incorporated with the envelope spectrum analysis to present a novel combined fault detection method. Taking the fact that ICA can deal with coupling signals effectively, the proposed method can remedy the problem that the tradional envelope analysis may not work well under the condition with coupling effects among different mechanical parts.2. A short-time Fourier transform based method is studied to obtain the signal energy distribution, which can be used for the parameter selection of the bandpass filter. The ununiform band design of the vibrative resonation in conventional envelope analysis schemes is thus avoided. Then a characteristics detection method of rolling element bearings is investigated combining the short-time Fourier transform and ICA. 3. A combined analysis technology based on the ICA and Hilbert-Huang transform is proposed to detect the fault characteristics under complex coupling effects. The Hilbert-Huang transform is utilized to replace the traditional envelope analysis, such that the difficulties of conventional envelope analysis schemes for the multi-component signals are solved.Simulations and practical experimental tests are conducted to show the validity and the effectivenss of the proposed approaches. This study appropriately extends the usage of envelope analysis technology and Hilbert-Huang transform technology. Those presented results will benefit the academic study as well as the practical applications of the condition monitoring and faults diagnosis of rotating machineries.