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Trace Ratio Criterion-Based Kernel Discriminant Analysis for Fault Diagnosis of Rolling Element Bearings Using Binary Immune Genetic Algorithm
المؤلفون المشاركون
Yang, Wen-An
Xiao, Maohua
Zhou, Wei
Guo, Yu
Liao, Wenhe
Shen, Gang
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2016-01-10
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
The rolling element bearing is a core component of many systems such as aircraft, train, steamboat, and machine tool, and their failure can lead to reduced capability, downtime, and even catastrophic breakdowns.
Due to misoperation, manufacturing deficiencies, or the lack of monitoring and maintenance, it is often found to be the most unreliable component within these systems.
Therefore, effective and efficient fault diagnosis of rolling element bearings has an important role in ensuring the continued safe and reliable operation of their host systems.
This study presents a trace ratio criterion-based kernel discriminant analysis (TR-KDA) for fault diagnosis of rolling element bearings.
The binary immune genetic algorithm (BIGA) is employed to solve the trace ratio problem in TR-KDA.
The numerical results obtained using extensive simulation indicate that the proposed TR-KDA using BIGA (called TR-KDA-BIGA) can effectively and efficiently classify different classes of rolling element bearing data, while also providing the capability of real-time visualization that is very useful for the practitioners to monitor the health status of rolling element bearings.
Empirical comparisons show that the proposed TR-KDA-BIGA performs better than existing methods in classifying different classes of rolling element bearing data.
The proposed TR-KDA-BIGA may be a promising tool for fault diagnosis of rolling element bearings.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yang, Wen-An& Xiao, Maohua& Zhou, Wei& Guo, Yu& Liao, Wenhe& Shen, Gang. 2016. Trace Ratio Criterion-Based Kernel Discriminant Analysis for Fault Diagnosis of Rolling Element Bearings Using Binary Immune Genetic Algorithm. Shock and Vibration،Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1119865
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yang, Wen-An…[et al.]. Trace Ratio Criterion-Based Kernel Discriminant Analysis for Fault Diagnosis of Rolling Element Bearings Using Binary Immune Genetic Algorithm. Shock and Vibration No. 2016 (2016), pp.1-15.
https://search.emarefa.net/detail/BIM-1119865
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yang, Wen-An& Xiao, Maohua& Zhou, Wei& Guo, Yu& Liao, Wenhe& Shen, Gang. Trace Ratio Criterion-Based Kernel Discriminant Analysis for Fault Diagnosis of Rolling Element Bearings Using Binary Immune Genetic Algorithm. Shock and Vibration. 2016. Vol. 2016, no. 2016, pp.1-15.
https://search.emarefa.net/detail/BIM-1119865
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1119865
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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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
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