Fault Diagnosis of Gearbox in Multiple Conditions Based on Fine-Grained Classification CNN Algorithm
المؤلفون المشاركون
Jiang, Pengcheng
Cong, Hua
Wang, Jing
Zhang, Dongsheng
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-15، 15ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-06-20
دولة النشر
مصر
عدد الصفحات
15
التخصصات الرئيسية
الملخص EN
The use of the convolutional neural network for fault diagnosis has been a common method of research in recent years.
Since this method can automatically extract fault features, it has played a good role in some research studies.
However, this method has a clear drawback that the signals will be significantly affected by working conditions and sample size, and it is difficult to improve diagnostic accuracy by directly learning faults, regardless of working conditions.
It is therefore a research orientation worthy of a diagnosis of high precision defect in various working conditions.
In this article, using a fine-grained classification algorithm, the operating conditions of the object system are considered an approximate classification.
A specific failure in different working conditions is considered a beautiful classification.
Samples of different faults in different working conditions are learned uniformly and the common characteristics are extracted from the convolutional network so that different faults of different working conditions can simultaneously be identified on the basis of the entire sample.
Experimental results show that the method effectively uses the set of samples of the working conditions of the variables to obtain the dual recognition of defects and specific working conditions and the accuracy of the recognition is significantly higher than the method of learning regardless of working conditions.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Jiang, Pengcheng& Cong, Hua& Wang, Jing& Zhang, Dongsheng. 2020. Fault Diagnosis of Gearbox in Multiple Conditions Based on Fine-Grained Classification CNN Algorithm. Shock and Vibration،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1213673
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Jiang, Pengcheng…[et al.]. Fault Diagnosis of Gearbox in Multiple Conditions Based on Fine-Grained Classification CNN Algorithm. Shock and Vibration No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1213673
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Jiang, Pengcheng& Cong, Hua& Wang, Jing& Zhang, Dongsheng. Fault Diagnosis of Gearbox in Multiple Conditions Based on Fine-Grained Classification CNN Algorithm. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1213673
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1213673
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