Abstract
The vibration signal of local gear fault is mainly composed of two components. One is the resonant signal and noise signal and the other one is the transient impulse signal including fault information. The quality factors corresponding to the two components are different. Hence, a method to diagnose local gear fault based on composite quality factor basis and parallel basis pursuit is proposed. First, two different quality factors bases are established using wavelet transform of variable quality factors to obtain the decomposition coefficient. Next, the parallel basis pursuit is adopted for the optimization of the decomposition coefficient. With the derived optimal decomposition coefficient, the resonant components with different quality factors can be reconstructed. By discussing the sparsity of signals treated with different quality factors bases, the suitable composite quality factor basis is selected to perform sparse decomposition on the signal. Besides, the obtained resonant component with low quality factor is subject to demodulation analysis, so as to derive the fault information. The feasibility and validity of the algorithm are shown by the results from simulation signal and practical application of local gear faults.
Highlights
Gear is a very important transmission part of rotating machineries
It is necessary to monitor the operating state of gear and perform fault diagnosis. When local faults such as pitting and teeth breaking occur on a gear, the complex vibration signals generated by the interaction of periodic rotation of machine, periodic excitation by the fault, and interferences from surrounding environment consist of periodic component and random component, which are expressed as modulation format
A common method used in the fault diagnosis in gear is the envelope demodulation technique
Summary
Gear is a very important transmission part of rotating machineries. The normal operation of gear is directly related to producing benefit and facility security [1, 2]. In order to solve the problem, Li proposed a sparse decomposition method based on resonant signal [13] and construct a basis functions according to the QF which is the ratio of center frequency to band. By this way, the transient impact signal and the periodic signal of persistent oscillation can be distinguished. In order to further manifest the effectiveness of separating the high and low resonant components in the signal using the sparse decomposition method with QF basis, a signal, as shown, is constructed.
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