کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
8145070 1524068 2018 23 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A multiscale noise tuning stochastic resonance for fault diagnosis in rolling element bearings
ترجمه فارسی عنوان
تنظیم صدا سر و صدا چندگانه رضایت تصادفی برای تشخیص خطا در بلبرینگ عنصر نورد
کلمات کلیدی
رزونانس تصادفی سه گانه، تنظیم صدا سر و صدای زیاد، نسبت سیگنال به نویز، بسته های موجک تبدیل می شوند شناسایی خطای ماشین،
موضوعات مرتبط
مهندسی و علوم پایه فیزیک و نجوم فیزیک اتمی و مولکولی و اپتیک
چکیده انگلیسی
Condition monitoring of rotating machinery is important to extend the mechanical system's reliability and operational life. However, in many cases, useful information is often overwhelmed by strong background noise and the defect frequency is difficult to be extracted. Stochastic resonance (SR) is used as a noise-assisted tool to amplify weak signals in nonlinear systems, which can detect weak signals of interest submerged in the noise. The multiscale noise tuning SR (MSTSR), which is originally based on discrete wavelet transform (DWT), has been applied to identify the fault characteristics and has also increased the signal-to-noise ratio (SNR) improvement of SR. Therefore, a novel tri-stable SR method with multiscale noise tuning (MST) is proposed to extract fault signatures for fault diagnosis of rotating machinery. The wavelet packets transform (WPT) based MST can obtain better denoising effect and higher SNR of resonance output compared with the traditional SR method. Thus the proposed method is well-suited for enhancement of rotating machine fault identification, whose effectiveness has been verified by means of practical vibration signals carrying fault information from bearings. Finally, it can be concluded that the proposed method has practical value in engineering.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chinese Journal of Physics - Volume 56, Issue 1, February 2018, Pages 145-157
نویسندگان
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