电子测量与仪器学报

贺利芳,熊清,刘文浩.MCKD在一种新型随机共振系统下的转动体故障诊断研究[J].电子测量与仪器学报,2024,38(8):188-200

MCKD在一种新型随机共振系统下的转动体故障诊断研究

Research on rotating machinery fault diagnosis using MCKDunder a novel stochastic resonance system

DOI：

英文关键词:signal processing fault diagnosis output saturation stochastic resonance MCKD-UTSOSR

基金项目:重庆市自然科学基金面上（CSTB2023NSCQ-MSX0235, cstc2021jcyj-msxmX0836）项目资助

作者	单位
贺利芳	重庆邮电大学通信与信息工程学院重庆400065
熊清	重庆邮电大学通信与信息工程学院重庆400065
刘文浩	重庆邮电大学通信与信息工程学院重庆400065

Author	Institution
He Lifang	School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications (CQUPT), Chongqing 400065, China
Xiong Qing	School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications (CQUPT), Chongqing 400065, China
Liu Wenhao	School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications (CQUPT), Chongqing 400065, China

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中文摘要:

为解决由高阶项限制引起的输出饱和问题，利用分段势函数抗饱和的优良特性，提出了一种新的非饱和三稳二阶随机共振(UTSOSR)系统。首先，通过仿真实验验证了该系统能够显著改善经典三稳二阶随机共振系统的输出饱和问题。其次，基于绝热近似理论，推导出UTSOSR系统的稳态概率密度, 平均首次通过时间和功率谱放大因子(SA)，并通过分析系统各参数对这些性能指标的影响，来更加深入地探究系统的动力学行为。将SA和信噪比增益(Gsnr)作为评价指标，通过数值仿真验证了UTSOSR系统具有更优越的信号增强和抗噪声性能。同时，为了获得更优的输出性能，将最大相关峭度解卷积(MCKD)与UTSOSR系统相结合，提出MCKD-UTSOSR方法对目标信号特征进行提取。最后，联合遗传算法和变步长网格优化算法寻找MCKD-UTSOSR方法的最优参数，并应用于转动体微弱故障信号检测。数据分析结果表明，MCKD-UTSOSR方法相比于其他方法，其信噪比提升了1.128 9~23.585 4 dB，谱峰峰值提升了88.423~7 488.118 133，为实际工程中高效的信号处理和故障检测提供了创新和可靠的解决方案。

英文摘要:

To address the issue of output saturation caused by higher-order term constraints, we propose a novel unsaturated tri-stable second-order stochastic resonance (UTSOSR) system that leverages the excellent anti-saturation properties of piecewise potential function. First, simulation experiments verified that this system can significantly mitigate the output saturation problem of classical tri-stable second-order stochastic resonance system. Next, based on the adiabatic approximation theory, we derived the steady-state probability density, mean first-passage time, and spectral amplification factor (SA) of the UTSOSR system. By analyzing the influence of various system parameters on these performance metrics, we can further explore the system’s dynamic behavior in greater depth. Subsequently, using the SA and the signal-to-noise ratio gain (Gsnr) as evaluation metrics, numerical simulations were conducted to verify the superior signal enhancement and noise robustness performance of the UTSOSR system. Additionally, to achieve superior output performance, we combined maximum correlated kurtosis deconvolution (MCKD) with the UTSOSR system, proposing the MCKD-UTSOSR method for extracting target signal features. Finally, a combined approach using genetic algorithm and variable step-size grid optimization algorithm is employed to identify the optimal parameters for the MCKD-UTSOSR method in bearing fault diagnosis. The data analysis results indicate that compared to other methods, the MCKD-UTSOSR method improved the signal-to-noise ratio by 1.128 9~23.585 4 dB and the spectral peak value by 88.423~7 488.118 133. This provides an innovative and reliable solution for efficient signal processing and fault detection in practical engineering applications.

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