Research on Fault Feature Extraction Method of Rolling Bearing Based on NMD and Wavelet Threshold Denoising
المؤلفون المشاركون
Xiao, Maohua
Wei, Weihua
Wu, Dan
Wen, Kai
Zhang, Cunyi
Zhao, Xiao
المصدر
العدد
المجلد 2018، العدد 2018 (31 ديسمبر/كانون الأول 2018)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2018-08-19
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Rolling bearings are the core components of the machine.
In order to save costs and prevent accidents caused by bearing failures, the rolling bearing fault diagnosis technology has been widely used in the industrial field.
At present, the proposed methods include wavelet transform, morphological filtering, empirical mode decomposition (EMD), and ensemble empirical mode decomposition (EEMD), which have obvious shortcomings.
As it is difficult to extract the fault characteristic frequency caused by nonlinear and nonstationary features of the rolling bearing fault signal, this paper presents a fault feature extraction method of rolling bearing based on nonlinear mode decomposition (NMD) and wavelet threshold denoised method.
First of all, the fault signal was preprocessed via wavelet threshold denoising.
Then, the denoised signal was decomposed by using NMD.
Next, the mode component envelope spectrum was made.
Finally, the fault characteristic frequency of rolling bearing was extracted.
The method was compared with EMD through the simulation experiment and rolling bearing fault experiment.
Meanwhile, two indicators including signal-noise ratio (SNR) and root-mean-square error (RMSE) were also established to evaluate the fault diagnosis ability of this method, and the results show that this method can extract the fault characteristic frequency accurately.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xiao, Maohua& Wen, Kai& Zhang, Cunyi& Zhao, Xiao& Wei, Weihua& Wu, Dan. 2018. Research on Fault Feature Extraction Method of Rolling Bearing Based on NMD and Wavelet Threshold Denoising. Shock and Vibration،Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1215556
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xiao, Maohua…[et al.]. Research on Fault Feature Extraction Method of Rolling Bearing Based on NMD and Wavelet Threshold Denoising. Shock and Vibration No. 2018 (2018), pp.1-11.
https://search.emarefa.net/detail/BIM-1215556
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xiao, Maohua& Wen, Kai& Zhang, Cunyi& Zhao, Xiao& Wei, Weihua& Wu, Dan. Research on Fault Feature Extraction Method of Rolling Bearing Based on NMD and Wavelet Threshold Denoising. Shock and Vibration. 2018. Vol. 2018, no. 2018, pp.1-11.
https://search.emarefa.net/detail/BIM-1215556
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1215556
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر