کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6953668 | 1451822 | 2018 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fault feature extraction based on combination of envelope order tracking and cICA for rolling element bearings
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Vibration from incipient faults of rolling element bearings (REBs) is usually too weak to be observed in a conventional spectrum analysis. The envelope analysis or high-frequency resonance technique is an effective tool for the incipient fault detection of REBs. The newly developed envelope order tracking, an improved version of the envelope analysis, can be well performed even in a varying-speed condition. However, the envelope order tracking can be invalid for multi-impulsive sources. To address this issue, a scheme for the weak feature extraction of faulty REBs has been proposed in this paper by combining the envelope order tracking and the constrained independent component analysis (cICA). In the proposed scheme, the envelope order tracking approach is utilized to obtain the envelopes of sensor observed mixtures at different positions. Then, the envelopes are turned from the time domain into the angle domain by the constant-angle increments resampling scheme in the computed order tracking (COT). Subsequently, the cICA method is employed to extract the interesting envelope independent components (ICs) by a reference signal, which is constructed according to the prior-known feature frequency of the bearing. As a result, the faults related features can be clearly exposed in the spectra of the obtained interesting envelope ICs. Simulations and experimental results support the proposed method positively.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanical Systems and Signal Processing - Volume 113, December 2018, Pages 131-144
Journal: Mechanical Systems and Signal Processing - Volume 113, December 2018, Pages 131-144
نویسندگان
Tangfeng Yang, Yu Guo, Xing Wu, Jing Na, Rong-Fong Fung,