کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6956513 | 1451876 | 2013 | 21 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A new statistical modeling and detection method for rolling element bearing faults based on alpha-stable distribution
ترجمه فارسی عنوان
روش جدید آماری مدل سازی و تشخیص برای گسل های تحمل عنصر نورد براساس توزیع پایدار آلفا
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
Due to limited information given by traditional local statistics, a new statistical modeling method for rolling element bearing fault signals is proposed based on alpha-stable distribution. In order to fully take advantages of complete information provided by alpha-stable distribution, this paper focuses on testing the validity of the proposed statistical model. A number of hypothetical test methods were applied to practical bearing fault vibration signals with different fault types and degrees. Through testing on the consistency of three alpha-stable parameter estimation methods, and the probability density function fitting level between fault signals and their corresponding hypothetical alpha-stable distributions, it can be concluded that such a non-Gaussian model is sufficient to thoroughly describe the statistical characteristics of bearing fault signals with impulsive behaviors, and consequently the alpha-stable hypothesis is verified. In the meantime, a new bearing fault detection method based on kurtogram and α parameter of the alpha-stable model is proposed, experimental results have shown that the proposed method has better performance on detecting incipient bearing faults than that based on the traditional kurtogram.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanical Systems and Signal Processing - Volume 41, Issues 1â2, December 2013, Pages 155-175
Journal: Mechanical Systems and Signal Processing - Volume 41, Issues 1â2, December 2013, Pages 155-175
نویسندگان
Gang Yu, Changning Li, Jianfeng Zhang,