Fault Diagnosis Method Research of Mechanical Equipment Based on Sensor Correlation Analysis and Deep Learning
Joint Authors
Wang, Yanxue
Duan, Lixiang
Bai, Tangbo
Yang, Jianwei
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-04
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Large-scale mechanical equipment monitoring involves various kinds and quantities of information, and the present research on multisensor information fusion may face problems of information conflicts and modeling complexity.
This paper proposes an analysis method combining correlation analysis and deep learning.
According to the characteristics of monitoring data, three types of correlation coefficients between sensors in different states are obtained, and a new composite correlation analytical matrix is established to fuse the multisource heterogeneous data.
The matrix represents fault feature information of different equipment states and helps further image generation.
Meanwhile, a convolutional neural network-based deep learning method is developed to process the matrix and to discover the relationship between results and equipment states for fault diagnosis.
To verify the method of this paper, experimental and field case studies are performed.
The results show that it can accurately identify fault states and has higher diagnostic efficiency and accuracy than traditional methods.
American Psychological Association (APA)
Bai, Tangbo& Yang, Jianwei& Duan, Lixiang& Wang, Yanxue. 2020. Fault Diagnosis Method Research of Mechanical Equipment Based on Sensor Correlation Analysis and Deep Learning. Shock and Vibration،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1213639
Modern Language Association (MLA)
Bai, Tangbo…[et al.]. Fault Diagnosis Method Research of Mechanical Equipment Based on Sensor Correlation Analysis and Deep Learning. Shock and Vibration No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1213639
American Medical Association (AMA)
Bai, Tangbo& Yang, Jianwei& Duan, Lixiang& Wang, Yanxue. Fault Diagnosis Method Research of Mechanical Equipment Based on Sensor Correlation Analysis and Deep Learning. Shock and Vibration. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1213639
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1213639