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An adaptive vibrational resonance method based on cascaded varying stable-state nonlinear systems and its application in rotating machine fault detection

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Abstract

A weak character signal with low frequency can be detected based on the mechanism of vibrational resonance (VR). The detection performance of VR is determined by the synergy of a weak low-frequency input signal, an injected high-frequency sinusoidal interference and the nonlinear system(s). In engineering applications, there are many weak fault signals with high character frequencies. These fault signals are usually submerged in strong background noise. To detect these weak signals, an adaptive detection method for a weak high-frequency fault signal is proposed in this paper. This method is based on the mechanics of VR and cascaded varying stable-state nonlinear systems (VSSNSs). Partial background noise with high frequency is regarded as a special type of high-frequency interference and an energy source that protrudes a weak fault signal. In this way, high-frequency background noise is utilized in a VSSNS. To improve the detection ability, manually generated high-frequency interference is injected into another VSSNS. The VSSNS can be transformed into a monostable state, bistable state or tristable state by tuning the system parameters. The proposed method is validated by a simulation signal and industrial applications. The results show the effectiveness of the proposed method to detect a weak high-frequency character signal in engineering problems.

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Acknowledgements

The authors gratefully acknowledge support from the National Natural Science Foundation of China (52075094, 51705321), the Fundamental Research Funds for the Central Universities (2232019D3-29), the China Postdoctoral Science Foundation (2017M611576) and the Initial Research Funds for Young Teachers of Donghua University.

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Authors and Affiliations

  1. College of Mechanical Engineering, Donghua University, Shanghai, 201620, China

    Lei Xiao & Junxuan Tang

  2. E. ON Climate & Renewables UK Limited, Coventry, CV4 8LG, UK

    Rusmir Bajric

  3. Army Military Transportation University, Tianjin, 300161, China

    Jingsong Zhao

  4. China North Vehicle Research Institute, Fengtai District, Beijing, 100072, China

    Xinghui Zhang

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  1. Lei Xiao
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  2. Rusmir Bajric
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  3. Jingsong Zhao
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  4. Junxuan Tang
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  5. Xinghui Zhang
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Correspondence to Lei Xiao.

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Xiao, L., Bajric, R., Zhao, J. et al. An adaptive vibrational resonance method based on cascaded varying stable-state nonlinear systems and its application in rotating machine fault detection. Nonlinear Dyn 103, 715–739 (2021). https://doi.org/10.1007/s11071-020-06143-y

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  • DOI: https://doi.org/10.1007/s11071-020-06143-y

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