Based on Soft Competition ART Neural Network Ensemble and Its Application to the Fault Diagnosis of Bearing
المؤلفون المشاركون
Xu, Zengbing
Wang, Zhigang
Yi, Cancan
Liu, Changming
Yang, Dan
Mu, Hailin
المصدر
Mathematical Problems in Engineering
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-07-03
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
This paper presents a novel method for fault diagnosis based on an improved adaptive resonance theory (ART) neural network and ensemble technique.
The method consists of three stages.
Firstly, the improved ART neural network is comprised of the soft competition technique based on fuzzy competitive learning (FCL) and ART based on Yu’s norm, the neural nodes in the competition layer are trained according to the degree of membership between the mode node and the input, and then fault samples are classified in turn.
Secondly, with the distance evaluation technique, the optimal features are obtained from the statistical characteristics of original signals and wavelet coefficients.
Finally, the optimal features are input into the neural network ensemble (NNE) based on voting method to identify the different fault categories.
The proposed method is applied to the fault diagnosis of rolling element bearings, and testing results show that the neural network ensemble can reliably classify different fault categories and the degree of faults, which has a better classification performance compared with the single neural network.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yang, Dan& Mu, Hailin& Xu, Zengbing& Wang, Zhigang& Yi, Cancan& Liu, Changming. 2017. Based on Soft Competition ART Neural Network Ensemble and Its Application to the Fault Diagnosis of Bearing. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1189896
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yang, Dan…[et al.]. Based on Soft Competition ART Neural Network Ensemble and Its Application to the Fault Diagnosis of Bearing. Mathematical Problems in Engineering No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1189896
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yang, Dan& Mu, Hailin& Xu, Zengbing& Wang, Zhigang& Yi, Cancan& Liu, Changming. Based on Soft Competition ART Neural Network Ensemble and Its Application to the Fault Diagnosis of Bearing. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1189896
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1189896
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