An Integrated Fault Identification Approach for Rolling Bearings Based on Dual-Tree Complex Wavelet Packet Transform and Generalized Composite Multiscale Amplitude-Aware Permutation Entropy
المؤلفون المشاركون
Yang, Xiaoqiang
Liu, Wuqiang
Shen, Jinxing
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-18، 18ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-11-27
دولة النشر
مصر
عدد الصفحات
18
التخصصات الرئيسية
الملخص EN
The health condition of rolling bearings, as a widely used part in rotating machineries, directly influences the working efficiency of the equipment.
Consequently, timely detection and judgment of the current working status of the bearing is the key to improving productivity.
This paper proposes an integrated fault identification technology for rolling bearings, which contains two parts: the fault predetection and the fault recognition.
In the part of fault predetection, the threshold based on amplitude-aware permutation entropy (AAPE) is defined to judge whether the bearing currently has a fault.
If there is a fault in the bearing, the fault feature is adequately extracted using the feature extraction method combined with dual-tree complex wavelet packet transform (DTCWPT) and generalized composite multiscale amplitude-aware permutation entropy (GCMAAPE).
Firstly, the method decomposes the fault vibration signal into a set of subband components through the DTCWPT with good time-frequency decomposing capability.
Secondly, the GCMAAPE values of each subband component are computed to generate the initial candidate feature.
Next, a low-dimensional feature sample is established using the t-distributed stochastic neighbor embedding (t-SNE) with good nonlinear dimensionality reduction performance to choose sensitive features from the initial high-dimensional features.
Afterwards, the featured specimen representing fault information is fed into the deep belief network (DBN) model to judge the fault type.
In the end, the superiority of the proposed solution is verified by analyzing the collected experimental data.
Detection and classification experiments indicate that the proposed solution can not only accurately detect whether there is a fault but also effectively determine the fault type of the bearing.
Besides, this solution can judge the different faults more accurately compared with other ordinary methods.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Wuqiang& Yang, Xiaoqiang& Shen, Jinxing. 2020. An Integrated Fault Identification Approach for Rolling Bearings Based on Dual-Tree Complex Wavelet Packet Transform and Generalized Composite Multiscale Amplitude-Aware Permutation Entropy. Shock and Vibration،Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1212906
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Wuqiang…[et al.]. An Integrated Fault Identification Approach for Rolling Bearings Based on Dual-Tree Complex Wavelet Packet Transform and Generalized Composite Multiscale Amplitude-Aware Permutation Entropy. Shock and Vibration No. 2020 (2020), pp.1-18.
https://search.emarefa.net/detail/BIM-1212906
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Wuqiang& Yang, Xiaoqiang& Shen, Jinxing. An Integrated Fault Identification Approach for Rolling Bearings Based on Dual-Tree Complex Wavelet Packet Transform and Generalized Composite Multiscale Amplitude-Aware Permutation Entropy. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-18.
https://search.emarefa.net/detail/BIM-1212906
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1212906
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