توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱Gear fault diagnosis via non–stationary adaptive MARTIN distance
نویسنده(ها): ،
اطلاعات انتشار: Scientia Iranica، هجدهم،شماره۱، ۲۰۱۱، سال
تعداد صفحات: ۷
In this paper, a new method of gear fault diagnosis is proposed based on a combination of the time synchronized averaging method (TSA), time–varying ARMA model and MARTIN distance. This method contains three major steps. In the first step, a TSA method is proposed for averaging the gearbox signal. The second step deals with selection of a proper ARMA model for a signal produced via a gearbox and using an adaptive filter (with a weighted least square algorithm) for identifying the time–varying parameters of the model. In the last step, a new time–varying distance is defined for gear fault diagnosis. The proposed distance is an extension of the MARTIN distance. Finally, as the case study, the method is used on a YAMAHA gearbox for identifying gear faults. The results of the diagnosis are satisfactory.
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