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A Parameter-Optimized DBN Using GOA and Its Application in Fault Diagnosis of Gearbox
المؤلفون المشاركون
Gai, Jingbo
Shen, Junxian
Wang, He
Hu, Yifan
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-03-17
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Aiming at the problems of poor self-adaptive ability in traditional feature extraction methods and weak generalization ability in single classifier under big data, an internal parameter-optimized Deep Belief Network (DBN) method based on grasshopper optimization algorithm (GOA) is proposed.
First, the minimum Root Mean Square Error (RMSE) in the network training is taken as the fitness function, in which GOA is used to search for the optimal parameter combination of DBN.
After that the learning rate and the number of batch learning in DBN which have great influence on the training error would be properly selected.
At the same time, the optimal structure distribution of DBN is given through comparison.
Then, FFT and linear normalization are introduced to process the original vibration signal of the gearbox, preprocess the data from multiple sensors and construct the input samples for DBN.
Finally, combining with deep learning featured by powerful self-adaptive feature extraction and nonlinear mapping capabilities, the obtained samples are input into DBN for training, and the fault diagnosis model for gearbox based on DBN would be established.
After several tests with the remaining samples, the diagnosis rate of the model could reach over 99.5%, which is far better than the traditional fault diagnosis method based on feature extraction and pattern recognition.
The experimental results show that this method could effectively improve the self-adaptive feature extraction ability of the model as well as its accuracy of fault diagnosis, which has better generalization performance.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Gai, Jingbo& Shen, Junxian& Wang, He& Hu, Yifan. 2020. A Parameter-Optimized DBN Using GOA and Its Application in Fault Diagnosis of Gearbox. Shock and Vibration،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1209923
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Gai, Jingbo…[et al.]. A Parameter-Optimized DBN Using GOA and Its Application in Fault Diagnosis of Gearbox. Shock and Vibration No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1209923
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Gai, Jingbo& Shen, Junxian& Wang, He& Hu, Yifan. A Parameter-Optimized DBN Using GOA and Its Application in Fault Diagnosis of Gearbox. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1209923
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1209923
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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