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Application of recurrence dynamic analysis to running-in state recognition

Minglong Peng (School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang, China)
Yuankai Zhou (School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang, China and Jiangsu Provincial Key Laboratory of Advanced Manufacturing for Marine Mechanical Equipment, Jiangsu University of Science and Technology, Zhenjiang, China)
Xue Zuo (School of Mechanical Engineering, Jiangsu University of Science and Technology, Zhenjiang, China and Jiangsu Provincial Key Laboratory of Advanced Manufacturing for Marine Mechanical Equipment, Jiangsu University of Science and Technology, Zhenjiang, China)

Industrial Lubrication and Tribology

ISSN: 0036-8792

Article publication date: 11 June 2021

Issue publication date: 3 August 2021

121

Abstract

Purpose

The purpose of this paper is to study the dynamic features of friction coefficient during running-in state based on recurrence analysis, so as to recognize the running-in state of crankshaft journal bearings.

Design/methodology/approach

The friction coefficient was measured in the friction experiments and the dynamic features are analyzed by recurrence plots (RPs), unthreshold recurrence plots (URPs) and recurrence quantification analysis.

Findings

During the running-in process, RPs have gone through disrupted patterns, drift patterns and homogeneous patterns successively. URP shows that the phase trajectory spirals in the disrupted pattern gradually converge in the drift pattern and remain stable in the homogeneous pattern. Three independent measures, recurrence rate, entropy and laminarity, are chosen to characterize friction coefficient from the perspective of point, diagonal line and vertical line structures of the RPs.

Originality/value

The results provide a feasible way to monitor the running-in process and recognize the running-in state.

Keywords

Acknowledgements

The project is supported by the National Natural Science Foundation of China (Grant No. 51705216, 52005226), Natural Science Foundation of Jiangsu Province (Grant Nos. BK20170584 and BK20190971).

Citation

Peng, M., Zhou, Y. and Zuo, X. (2021), "Application of recurrence dynamic analysis to running-in state recognition", Industrial Lubrication and Tribology, Vol. 73 No. 5, pp. 756-764. https://doi.org/10.1108/ILT-12-2020-0481

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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