Abstract
In this study, a diagnostic method for gear wear fault is proposed, which is based on the ultra-complete independent component analysis. The ultra-complete analysis model is constructed, and the similar source signals more than mixing signals are separated. Based on the typical features of the fault source signal, the useful component of the mixing signals can be found. As the fault source signal and similar fault source signal are similar, the magnification range of similar shapes can be estimated by using the interval estimation method. The mapping between one-way varying magnification time domain and rotary component fault degree is identified, and the fault degree judgment standard can be established. Thus, the fault degree can be determined. The method is used to deal with the state monitoring data of the gear, and the analysis results show that the diagnostic method is of practical value.
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