多稳态匹配随机共振在机械早期故障特征提取中的应用

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振动与冲击 ›› 2023, Vol. 42 ›› Issue (11) : 87-95.

论文

谯自健1,2,3,4,陈帅1,马莉5,赖志慧6,刘健7,许学方8,梅一丹9

作者信息 +

Multistable matching stochastic resonance with its application to mechanical incipient fault characteristic extraction

QIAO Zijian1,2,3,4, CHEN Shuai1, MA Li5, LAI Zhihui6, LIU Jian7,XU Xuefang8, MEI Yidan9

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文章历史 +

摘要

传统单稳态或双稳态随机共振方法的势函数稳态结构单一，难以匹配复杂多变的输入信号；固定尺度因子忽略了与势结构、输入信号之间的协同增强作用；且一阶系统易遭受低频噪声干扰，依赖高通滤波器辅助。因此，提出自适应二阶多稳态匹配随机共振方法，并应用于机械早期故障的微弱特征提取。该方法的优势在于：（1）多稳态势结构的多样性可与不同的输入信号实现有效匹配；（2）能实现输入信号、势结构、尺度因子三者之间的协同作用；（3）二阶多稳态随机共振能够抑制低频噪声干扰。仿真分析和机车轴承故障诊断案例表明：提出的方法相比单稳态和双稳态随机共振方法具有更强的微弱特征增强与提取能力。

Abstract

It is difficult for traditional monostable and bistable stochastic resonance (SR) methods to match with complicated and variable input signals due to the single stable structure of the potential function. Moreover, the scaling factor is generally fixed as a constant, thereby neglecting the synergistic effect among the potential structure, input signal and scaling factor. In addition, since traditional SR methods are based on first-order model, they easily suffer from the noise interference in the low frequency, thereby strongly depending on the help of highpass filter. Therefore, an adaptive second-order multistable matching SR method is proposed to extract weak characteristics in mechanical incipient faults. The method has three advantages: (1) the diversity of multistable potential structure is able to achieve the adaptive matching with different input signals, (2) the optimal synergistic effect among input signal, potential structure and scaling factor is obtained and (3) second-order multistable SR is able to suppress the noise interference in the low frequency. Finally, the proposed method is validated using simulated and experimental data. The results show that the proposed method is able to not only extract weak characteristics from the original vibration signals, but also possess stronger enhancment performance than the traditional methods.

导出引用

谯自健1,2,3,4,陈帅1,马莉5,赖志慧6,刘健7,许学方8,梅一丹9. 多稳态匹配随机共振在机械早期故障特征提取中的应用[J]. 振动与冲击, 2023, 42(11): 87-95

QIAO Zijian1,2,3,4, CHEN Shuai1, MA Li5, LAI Zhihui6, LIU Jian7,XU Xuefang8, MEI Yidan9. Multistable matching stochastic resonance with its application to mechanical incipient fault characteristic extraction[J]. Journal of Vibration and Shock, 2023, 42(11): 87-95

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