The Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Iterative Random Forest

المؤلفون المشاركون

Qin, Xiwen
Dong, Xiaogang
Guo, Jiajing
Guo, Yu

المصدر

Shock and Vibration

العدد

المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2020-02-12

دولة النشر

مصر

عدد الصفحات

11

التخصصات الرئيسية

هندسة مدنية

الملخص EN

Rolling bearing is a critical part of machinery, whose failure will lead to considerable losses and disastrous consequences.

Aiming at the research of rotating mechanical bearing data, a fault identification method based on Variational Mode Decomposition (VMD) and Iterative Random Forest (iRF) classifier is proposed.

Furthermore, EMD and EEMD are used to decompose the data.

At the same time, three mainstream classifiers were selected as the benchmark model.

The results show that the proposed model has the highest recognition accuracy.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Qin, Xiwen& Guo, Jiajing& Dong, Xiaogang& Guo, Yu. 2020. The Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Iterative Random Forest. Shock and Vibration،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1209657

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Qin, Xiwen…[et al.]. The Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Iterative Random Forest. Shock and Vibration No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1209657

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Qin, Xiwen& Guo, Jiajing& Dong, Xiaogang& Guo, Yu. The Fault Diagnosis of Rolling Bearing Based on Variational Mode Decomposition and Iterative Random Forest. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1209657

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1209657