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Design a degradation condition monitoring system scheme for rolling bearing using EMD and PCA

Jun Wu (School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan, China)
Chaoyong Wu (School of Naval Architecture and Ocean Engineering, Huazhong University of Science and Technology, Wuhan, China)
Yaqiong Lv (School of Logistics Engineering, Wuhan University of Technology,Wuhan, China)
Chao Deng (School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China)
Xinyu Shao (School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, China)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 8 May 2017

Abstract

Purpose

Rolling bearings based on rotating machinery are one of the most widely used in industrial applications because of their low cost, high performance and robustness. The purpose of this paper is to describe how to identify degradation condition of rolling bearing and predict its fault time in big data environment in order to achieve zero downtime performance and preventive maintenance for the rolling bearing.

Design/methodology/approach

The degradation characteristic parameters of rolling bearings including intrinsic mode energy and failure frequency were, respectively, extracted from the pre-processed original vibration signals using EMD and Hilbert transform. Then, Spearman’s rank correlation coefficient and PCA were used to obtain the health index of the rolling bearing so as to detect the appearance of degradations. Furthermore, the degradation condition of the rolling bearings might be identified through implementing the monotonicity analysis, robustness analysis and degradation analysis of the health index.

Findings

The effectiveness of the proposed method is verified by a case study. The result shows that the proposed method can be applied to monitor the degradation condition of the rolling bearings in industrial application.

Research limitations/implications

Further experiment remains to be done so as to validate the effectiveness of the proposed method using Apache Hadoop when massive sensor data are available.

Practical implications

The paper proposes a methodology for rolling bearing condition monitoring representing the steps that need to be followed. Real-time sensor data are utilized to find the degradation characteristics.

Originality/value

The result of the work presented in this paper form the basis for the software development and implementation of condition monitoring system for rolling bearings based on Hadoop.

Keywords

Acknowledgements

The authors are grateful to the technical editor and all reviewers for their valuable and constructive comments. The research is supported by the National Natural Science Foundation of China (NSFC) under Grant No. 51475189 and 51375181, the Foundation of the National Key Intergovernmental Special Project Development Plan of China under Grant No. 2016YFE0121700, and Fundamental Research Funds for the Central Universities under Grant No. 2016YXMS050.

Citation

Wu, J., Wu, C., Lv, Y., Deng, C. and Shao, X. (2017), "Design a degradation condition monitoring system scheme for rolling bearing using EMD and PCA", Industrial Management & Data Systems, Vol. 117 No. 4, pp. 713-728. https://doi.org/10.1108/IMDS-11-2016-0469

Publisher

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Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited