![](/images/graphics-bg.png)
An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds
المؤلفون المشاركون
He, Ya
Feng, Kun
Hu, Minghui
Cui, Jinmiao
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-21، 21ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-08-13
دولة النشر
مصر
عدد الصفحات
21
التخصصات الرئيسية
الملخص EN
The compressive sensing (CS) theory provides a new slight to the big-data problem led by the Shannon sampling theorem in rolling element bearings condition monitoring, where the measurement matrix of CS tends to be designed by the random matrix (RM) to preserve the integrity of signal roughly.
However, when the signal to be analyzed is infected with strong noise, not only does the signal become insufficiently sparse, but the randomness of the measurement matrix will bring down the sensing efficiency, resulting in the loss of fault feature.
Thus, a sensing-enhanced CS scheme based on a series of modes after VMD decomposition is proposed under this paper.
The core of this scheme is as follows: (1) the principal mode of VMD with better sparsity replaces the raw signal for compressive sensing; (2) all these modes contain the time-frequency characteristics of the raw signal; (3) a new measurement matrix called mode-circulant matrix (MCM) is defined by circulating the mode matrix, and when the amount of samples is shrunk, the sensing efficiency can be enhanced greatly.
Besides, considering the fault signal of rolling bearings under variable speed, there is a need to use order tracking to overcome the nonstationarity of the signal before applying CS theory.
The analysis results of simulation and experiment prove that the VMD- and MCM-based CS can successfully extract the weak fault feature of rolling bearings with operating speed changing.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
He, Ya& Feng, Kun& Hu, Minghui& Cui, Jinmiao. 2020. An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds. Shock and Vibration،Vol. 2020, no. 2020, pp.1-21.
https://search.emarefa.net/detail/BIM-1209670
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
He, Ya…[et al.]. An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds. Shock and Vibration No. 2020 (2020), pp.1-21.
https://search.emarefa.net/detail/BIM-1209670
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
He, Ya& Feng, Kun& Hu, Minghui& Cui, Jinmiao. An MCM-Enhanced Compressive Sensing for Weak Fault Feature Extraction of Rolling Element Bearings under Variable Speeds. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-21.
https://search.emarefa.net/detail/BIM-1209670
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1209670
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
![](/images/ebook-kashef.png)
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
![](/images/kashef-image.png)