Abstract




 
   

IJE TRANSACTIONS A: Basics Vol. 32, No. 1 (January 2019) 121-126    Article in Press

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  ROLLING BEARING FAULT ANALYSIS BY INTERPOLATING WINDOWED DFT ALGORITHM
 
X. Li, L. Han, H. Xu, Y. Yang and H. Xiao
 
( Received: July 08, 2018 – Accepted in Revised Form: October 26, 2018 )
 
 

Abstract    This paper focuses on the problem of accurate Fault Characteristic Frequency (FCF) estimation of rolling bearing. Teager-Kaiser Energy Operator (TKEO) demodulation has been applied widely to rolling bearing fault detection. FCF can be extracted from vibration signals, which is pre-treatment by TEKO demodulation method. However, because of strong noise background of fault vibration signal, it is difficult to extract FCF with high precision. In this paper, the improved algorithm of rolling bearing fault diagnosis is analyzed. Based on the envelope analysis by TKEO demodulation, it combines zero padding technique and the Improved Iterative Windowed Interpolation DFT (IIWIpDFT) algorithm to correct demodulated signal. Experimental result shows that the proposed algorithm decreases Root Mean Square Error (RMSE) of FCF(inner race) form about 2Hz~5.5Hz to about 0.5Hz for short data length, the same treatment also decreases RMSE form about 1.1Hz~3Hz to about 0.4~0.5Hz for longer data length in most cases. Meanwhile, the RMSE of FCF (outer race) improved 2.3 to 84.5% as compared to the application of traditional TEKO demodulation alone.

 

Keywords    Rolling Bearing, Teager-Kaiser Energy Operator, Fault Diagnosis, Interpolated DFT, Fault Characteristic Frequencyl

 

چکیده   

این مقاله بر روی مسئله دقیق بودن فرکانس مشخصه شکست (FCF) نورد غلتکی تمرکز دارد. دمودولاسیون اپراتورTKEO به طور گسترده ای برای شناسایی خطای غلتک استفاده شده است. FCF می تواند از سیگنال های ارتعاشی استخراج شود که پیش از درمان با استفاده از روش TEKO است. با این حال، به دلیل سابقه قوی نویز سیگنال ارتعاش خطا، استخراج FCF با دقت بالا مشکل است. در این مقاله، الگوریتم بهبود یافته تشخیص غلط نورد تحمل شده مورد تجزیه و تحلیل قرار گرفته است. بر اساس تجزیه و تحلیل پاکت توسط TKEO، آن را ترکیبی از تکنیک صفر پوسته و الگوریتم DFT بهبود پنجره های متحرک برای اصلاح سیگنال دمودوله می باشد. نتیجه آزمایش نشان می دهد که الگوریتم پیشنهادی خطای مربع متوسط ریشه RMSE و FCF (نژاد درونی) را از حدود 2Hz ~ 5.5Hz به حدود 0.5Hz برای طول داده های کوتاه را کاهش می دهد، همین روش همچنین RMSE را در حدود 1.1Hz ~ 3Hz به حدود٪ 0.4 تا 0.5Hz برای طول داده های طولانی در اکثر موارد حاصل می شود. در عین حال، RMSE FCF (نژاد بیرونی) 2.3٪ به 84.5٪ افزایش یافته است در مقایسه با استفاده از دمودولاسیون سنتی TEKO به تنهایی می باشد.

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