A Fault Diagnosis Method for Rolling Bearings Based on Feature Fusion of Multifractal Detrended Fluctuation Analysis and Alpha Stable Distribution
المؤلفون المشاركون
Xiong, Qing
Zhang, Weihua
Lu, Tianwei
Mei, Guiming
Liang, Shulin
المصدر
العدد
المجلد 2016، العدد 2016 (31 ديسمبر/كانون الأول 2016)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2015-12-24
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص EN
When rolling bearings fail, it is usually difficult to determine the degree of damage.
To address this problem, a new fault diagnosis method was developed to perform feature extraction and intelligent classification of various fault position and damage degree of rolling bearing signals.
Firstly, Multifractal Detrended Fluctuation Analysis (MFDFA) was used to compute five MFDFA features while five Alpha Stable Distribution (ASD) features were obtained by fitting the distribution to the vibration signals of each status and calculating the Probability Density Function (PDF).
Secondly, Kernel Principle Component Analysis (KPCA) was used to achieve dimensionality reduction fusion of the combination of original features to gain the Kernel Principle Component Fusion Features (KPCFFs).
Thirdly, the KPCFFs served as the input of Least Squares Support Vectors Machine (LSSVM) based on Particle Swarm Optimization (PSO) to assess rolling bearings’ fault position and damage severity.
Finally, the effectiveness of the method was validated by bench test data.
The results demonstrated that the developed method can achieve intelligent diagnosis of rolling bearings’ fault position and damage degree and can yield better diagnosis accuracy than single feature method or corresponding single feature fusion method.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Xiong, Qing& Zhang, Weihua& Lu, Tianwei& Mei, Guiming& Liang, Shulin. 2015. A Fault Diagnosis Method for Rolling Bearings Based on Feature Fusion of Multifractal Detrended Fluctuation Analysis and Alpha Stable Distribution. Shock and Vibration،Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1118783
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Xiong, Qing…[et al.]. A Fault Diagnosis Method for Rolling Bearings Based on Feature Fusion of Multifractal Detrended Fluctuation Analysis and Alpha Stable Distribution. Shock and Vibration No. 2016 (2016), pp.1-12.
https://search.emarefa.net/detail/BIM-1118783
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Xiong, Qing& Zhang, Weihua& Lu, Tianwei& Mei, Guiming& Liang, Shulin. A Fault Diagnosis Method for Rolling Bearings Based on Feature Fusion of Multifractal Detrended Fluctuation Analysis and Alpha Stable Distribution. Shock and Vibration. 2015. Vol. 2016, no. 2016, pp.1-12.
https://search.emarefa.net/detail/BIM-1118783
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1118783
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