A Novel Multiscale Deep Health Indicator with Bidirectional LSTM Network for Bearing Performance Degradation Trend Prognosis
المؤلفون المشاركون
Huang, Yujing
Wang, Han
Tang, Gang
Zhou, Youguang
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-17، 17ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-11-03
دولة النشر
مصر
عدد الصفحات
17
التخصصات الرئيسية
الملخص EN
As rolling bearings are the key components in rotating machinery, bearing performance degradation directly affects machine running status.
A tendency prognosis for bearing performance degradation is thus required to ensure the stability of operation.
This paper proposes a novel strategy for bearing performance degradation trend prognosis, including health indicator construction techniques and a performance degradation trend prediction method.
To more accurately represent the degradation trend, the multiscale deep bottleneck health indicator is proposed as a new synthesized health indicator to remove high-frequency detail signals from features, which can reduce possible fluctuations in conventional synthetic health indicators.
A suitable method for selecting the statistical characteristics required for fusion is also presented to solve the problem of information redundancy that affects trend representation.
In addition, a stacked autoencoder network is used for deep feature extraction of selected statistical features.
A bidirectional long short-term memory network prediction model is also proposed for the prediction of degradation trend, which can make full use of historical and future information to improve prediction accuracy.
Finally, experiments are carried out to verify the effectiveness of the proposed method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Wang, Han& Tang, Gang& Zhou, Youguang& Huang, Yujing. 2020. A Novel Multiscale Deep Health Indicator with Bidirectional LSTM Network for Bearing Performance Degradation Trend Prognosis. Shock and Vibration،Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1213102
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Wang, Han…[et al.]. A Novel Multiscale Deep Health Indicator with Bidirectional LSTM Network for Bearing Performance Degradation Trend Prognosis. Shock and Vibration No. 2020 (2020), pp.1-17.
https://search.emarefa.net/detail/BIM-1213102
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Wang, Han& Tang, Gang& Zhou, Youguang& Huang, Yujing. A Novel Multiscale Deep Health Indicator with Bidirectional LSTM Network for Bearing Performance Degradation Trend Prognosis. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-17.
https://search.emarefa.net/detail/BIM-1213102
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1213102
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