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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >Stochastic resonance in a high-order time-delayed feedback tristable dynamic system and its application
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Stochastic resonance in a high-order time-delayed feedback tristable dynamic system and its application

机译:随机共振在高阶时间延迟反馈追溯动态系统及其应用中

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摘要

A stochastic resonance (SR) tristable system based on a high-order time-delayed feedback is investigated and the feasibility of the system for weak fault signature extraction is discussed. The potential function, the mean first-passage time (MFPT) and the signal-to-noise ratio (SNR) are used to evaluate the model. Firstly, the potential function and stationary probability function (PDF) of the system are derived, and then the influence of the time delay parameters on the MFPT of the particles is analyzed. Secondly, the influences of time-delyed strength e and delyed length tau on the SR system from the perspective of the transition of the particles in the potential wells are discussed, and then the SNR and the effect of the parameters on the SNR are derived. In addition, the high-order time-delayed feedback tristable stochastic resonance (HTFTSR) system is used to deal with faulty bearing data and is compared with traditional tristable stochastic resonance (TSR). The result shows that the nonlinear system model can accurately identify the fault frequency and improve the energy of the characteristic signal under the appropriate system parameters. (C) 2019 Elsevier Ltd. All rights reserved.
机译:研究了基于高阶时间延迟反馈的随机谐振(SR)追溯系统,并讨论了系统弱故障签名提取的可行性。潜在功能,平均第一通道时间(MFPT)和信噪比(SNR)用于评估模型。首先,衍生系统的潜在功能和静止概率函数(PDF),然后分析了时间延迟参数对粒子MFPT的影响。其次,讨论了从潜在孔中颗粒的转变的角度对SR系统进行时间级强度E和杆状长度Tau的影响,然后推导了SNR和参数对SNR的影响。此外,使用高阶时间延迟反馈追溯随机谐振(HTFTSR)系统用于处理故障的轴承数据,并与传统的螺旋随机共振(TSR)进行比较。结果表明,非线性系统模型可以准确地识别故障频率并在适当的系统参数下提高特征信号的能量。 (c)2019年elestvier有限公司保留所有权利。

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