Using recurrence plots for stability analysis of ring-on-disc tribopairs

Sun, Guodong; Zhu, Hua; Ding, Cong

doi:10.1108/ilt-07-2018-0265

Cited by 6 publications

(1 citation statement)

References 28 publications

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“…For example, Ding et al [13,14] utilized the correlation dimension to monitor wear state changes while proposing a new characteristic parameter called moving cut data-approximate entropy that accurately identifies the wear state during friction. Sun et al [15] found that recurrence plots and recurrence quantification analysis can be used to characterize each stage of the friction process. Zhou et al [16] researched the chaos properties of the friction temperature during friction.…”

Section: Introductionmentioning

confidence: 99%

Online tracking and prediction of slip ring degradation using chaos theory based on LSTM neural network

Zuo¹,

Zhu²,

Zhou³

2023

Meas. Sci. Technol.

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Online monitoring of the slip ring was important to ensure the normal operation of the wind turbine equipment. The current-carrying friction experiment was carried out to simulate the degradation process of the slip ring. The chaotic parameter enclosing radius and statistical parameter root mean square were used to characterize the multi-sensor signals comprehensively. A new health indicator was proposed to evaluate the degradation state of slip ring based on the long and short-term memory (LSTM) neural network. It was fused by the signals of friction vibration, friction torque, voltage and electric current. The health indicator shows a better prediction effect by the prediction model. At the severe stage of the slip ring, the evaluation criteria MAE, RMSE, and MAPE of the health indicator are 0.0055,0.0043 and 4.5470%, which are much better than the RMS of the vibration signal. The results verify that the method can effectively determine the real-time degradation state of the slip ring.

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Section: Introductionmentioning

confidence: 99%

Online tracking and prediction of slip ring degradation using chaos theory based on LSTM neural network

Zuo¹,

Zhu²,

Zhou³

2023

Meas. Sci. Technol.

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A Recursive Characteristics Analysis-Based Stationarity Evaluation Model for Friction-Induced Attractors in the Sliding Friction Process

Sun

Zhang

et al. 2021

Journal of Tribology

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In this study, the coefficient of friction signals throughout the running-in process were examined by sliding a ring against a static disc. By reconstructing the scalar time-series into multi-dimensional phase-spaces, friction-induced attractors were obtained and quantified by recursive characteristics analysis, which can effectively realize the running-in status identification. Moreover, a recursive characteristics analysis-based evaluation model was established to investigate the stationarity of the friction-induced attractors based on the recurrence quantification analysis (RQA) measures. The analyses of the numerically simulated signals and experimental results indicate that the extracted model is an intuitive and effective method. Furthermore, to improve the stationary of the friction-induced attractors, the normal pressure should be low, whereas the relative sliding velocities should be increased appropriately. These results would contribute to the revelation of the recursive characteristics of the tribosystem, and the improvement of the stationarity of friction-induced attractors.

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Correlation Between Friction Coefficient and Friction Vibration in Running-In Process Based on Cross Recurrence Plots

Zhou

Peng

Zuo

et al. 2021

Journal of Tribology

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Friction coefficient is difficult to measure in real application, whether it can be replaced by friction coefficient for dynamic analysis is an urgent issue to be solved. To study the correlation between the two signals, the friction tests were carried out under dry friction, starved and flooded lubrications, respectively. Cross recurrence plot (CRP) and its measures (recurrence rate, determinism, average diagonal line length and entropy) were used to explore the correlation. The results show that the more obvious the diagonal structures in CRPs, the stronger the correlation between the two signals, and average diagonal length is more sensitive to the degree of correlation. Irrespective of lubrication conditions, friction coefficient and vibration measured in a friction system have similar recursive characteristics. Thus, friction coefficient or vibration can be selected according to the convenience of measurement to monitor the running-in process.

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Using recurrence plots for stability analysis of ring-on-disc tribopairs

Cited by 6 publications

References 28 publications

Online tracking and prediction of slip ring degradation using chaos theory based on LSTM neural network

Online tracking and prediction of slip ring degradation using chaos theory based on LSTM neural network

A Recursive Characteristics Analysis-Based Stationarity Evaluation Model for Friction-Induced Attractors in the Sliding Friction Process

Correlation Between Friction Coefficient and Friction Vibration in Running-In Process Based on Cross Recurrence Plots

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