کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
292403 509840 2006 25 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی عمران و سازه
پیش نمایش صفحه اول مقاله
Wavelet filter-based weak signature detection method and its application on rolling element bearing prognostics
چکیده انگلیسی

De-noising and extraction of the weak signature are crucial to fault prognostics in which case features are often very weak and masked by noise. The wavelet transform has been widely used in signal de-noising due to its extraordinary time-frequency representation capability. In this paper, the performance of wavelet decomposition-based de-noising and wavelet filter-based de-noising methods are compared based on signals from mechanical defects. The comparison result reveals that wavelet filter is more suitable and reliable to detect a weak signature of mechanical impulse-like defect signals, whereas the wavelet decomposition de-noising method can achieve satisfactory results on smooth signal detection. In order to select optimal parameters for the wavelet filter, a two-step optimization process is proposed. Minimal Shannon entropy is used to optimize the Morlet wavelet shape factor. A periodicity detection method based on singular value decomposition (SVD) is used to choose the appropriate scale for the wavelet transform. The signal de-noising results from both simulated signals and experimental data are presented and both support the proposed method.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Sound and Vibration - Volume 289, Issues 4–5, 7 February 2006, Pages 1066–1090
نویسندگان
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