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摘要:非线性随机动力学是力学、数学、工程等多个领域关注的热点, 在航空航天、机械工程、生物生态等领域有广泛的应用. 多稳态动力系统作为其最重要的研究对象, 在随机扰动下具有丰富的动力学行为, 如随机分岔、随机共振等, 尤其是随机共振, 已经被应用于机械故障诊断、微弱信号检测和振动能量俘获等工程实际问题中. 本文主要综述了多稳态动力系统中的随机共振理论、方法及工程应用. 首先, 通过几类典型的非线性随机动力学系统, 介绍了随机共振的经典理论和度量指标; 其次, 重点阐述了多稳态动力学系统, 尤其是三稳态和周期势系统, 在各类噪声激励下的随机共振现象, 分析了其诱发机理、演化规律和研究方法; 最后, 介绍了多稳态动力系统中随机共振的几类应用实例, 并进一步给出了随机共振当前面临的难题和未来的发展趋势等开放性问题.Abstract:The nonlinear stochastic dynamical system has been an important subject in areas of mechanics, mathematics, engineering and so on, and finds various applications in different fields like mechanical engineering, aerospace engineering, ocean engineering, and biology. The multi-stable dynamical systems are conceptual nonlinear systems, coupling with stochastic excitations, which can exhibit complex dynamical behaviors, such as stochastic resonance and stochastic bifurcation. The stochastic resonance theory has been utilized effectively in many areas related to stochastic dynamics such as mechanical fault diagnosis, weak signal detection and vibration energy harvesting. This paper overviews the fundamental theories, methods and engineering applications of stochastic resonance in multi-stable dynamical systems. We introduce recent advances in theories and measure index of stochastic resonance via several classic examples of nonlinear dynamical systems. Then, we summarize the results of multi-stable dynamical systems under the excitation of different types of noise. The tri-stable and periodic systems are illustrated to show the occurrence principle, evolution mechanism and investigated techniques. Finally, three engineering applications of multi-stable dynamical systems are surveyed. Some open problems are presented to close this paper.
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图 2对称双稳态系统(1)的随机共振示意图(Gammaitoni et al. 1998)
图 3不同噪声强度下模型(7)的动力学响应, 其中
$a = 1.05$ ,$\varepsilon = 0.01$ ,$(x(0),y(0)) = (0,0)$ (Pikovsky & Kurths 1997)图 5(a)周期势函数(
$ a = 1 $ ), (b)离散的多稳态过程(靳艳飞和许鹏飞 2021)图 6耦合势函数(15)的平衡点在
$ x - y $ 相平面上的分布, 其中$ s $ ,$ u $ 和$ o $ 分别表示稳定结点、鞍点和不稳定结点(Xu & Jin 2018)图 7最大李雅普诺夫指数作为耦合强度
$ c $ 的函数曲线, 其中$ {{{\varepsilon _y}} \mathord{\left/ {\vphantom {{{\varepsilon _y}} {{\varepsilon _x}}}} \right. } {{\varepsilon _x}}} = 1 $ ,$ {{{\omega _y}} \mathord{\left/ {\vphantom {{{\omega _y}} {{\omega _x}}}} \right. } {{\omega _x}}} = {1 \mathord{\left/ {\vphantom {1 {12}}} \right. } {12}} $ (Xu & Jin 2018)图 8不同热噪声强度下系统平均输入能量相对初始位置出现的相外状态和相内状态(Liu & Jin 2013)
图 10功率谱放大因子作为噪声强度的函数随不同Lévy噪声参数
$ \alpha $ 和$ \beta $ 的变换情况(Liu & Kang 2018)图 14三稳态系统跃迁示意图(Nicolis 2012)
图 15三稳态随机共振悬臂梁结构示意图(Lu et al. 2013)
图 16系统在粗糙三势阱中的跃迁示意图(Li et al. 2016)
图 17信噪比(
$ {\rm{SNR}} $ )作为阻尼系数$ {\gamma _0} $ 的函数随五次非线性刚度系数$ {\kappa _5} $ 的变化曲线(Xu et al. 2019)图 18记忆时间
$ {\tau _c} $ 对噪声诱导共振的影响. (a)特征相关时间和(b)功率谱放大因子(Xu & Jin 2020)图 20轴承内圈故障信号检测. (a)和(b)原始信号和频谱, (c)和(d)随机共振条件下输出信号和频谱(Xu & Jin 2020)
图 22旋转环境下三稳态能量采集装置示意图. (a)安装在车轮上的三稳态能量收集装置, (b)三稳态压电能量采集器(THE)原理图, (c)与THE相连的标准整流电路(Zhang et al. 2022)
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