摘要
针对经典双稳随机共振系统(CBSR)的输出饱和现象降低系统输出信噪比的问题,提出一种改进型双稳随机共振系统。将CBSR中限制粒子运动的四次型势函数改进为分段二次型双稳势函数,并代入到由势函数、噪声以及微弱周期信号驱动的朗之万方程中,得到非饱和分段双稳随机共振系统。该系统结构简单,可通过调节系统参数实现最佳随机共振。进一步,通过绝热近似理论,得到表征系统性能的输出信噪比表达式,当输出信噪比随系统参数以及噪声参数增加呈现非单调变化时,系统发生随机共振。将改进系统应用于轴承故障诊断,结果表明,在相同参数下,改进系统的输出信噪比共振曲线整体高于CBSR及分段非线性双稳随机共振系统(PNBSR),系统能够有效检测出故障信号频率,在内外圈故障诊断中,输出信噪比较PNBSR系统分别提高了2.4 dB与1.8 dB,证明改进系统可有效增强系统输出信噪比。
Aiming at the problem that the output saturation of the classical bistable stochastic resonance system(CBSR)reduces the output signal-to-noise ratio of the system,an improved bistable stochastic resonance system is proposed.The quaternary potential function which restricts particle motion in CBSR is improved to the piecewise quadratic potential function and substituted into Langevin equation driven by potential function,noise and weak periodic signal,thus an unsaturated piecewise bistable stochastic resonance system is obtained.The improved system is simple in structure and can achieve the best stochastic resonance by adjusting the system parameters.Furthermore,the expression of the output signal-to-noise ratio(SNR)is obtained following adiabatic approximation theory.It is found that when the output SNR changes nonmonotonically with the increasing system parameters and noise parameters,stochastic resonance occurs in the system.Simulation shows that with the same parameters,the output SNR resonance curves of the improved system are higher than those of the CBSR and PNBSR systems.The improved system is applied to the bearing fault diagnosis,and the experimental results indicate that in the inner and outer ring fault diagnosis,the output SNR of PNBSR system is increased by 2.4 dB and 1.8 dB respectively,which verifies that the improved system can effectively enhance the output SNR of the system.
作者
王慧
张刚
张天骐
WANG Hui;ZHANG Gang;ZHANG Tianqi(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《西安交通大学学报》
EI
CAS
CSCD
北大核心
2020年第4期110-117,共8页
Journal of Xi'an Jiaotong University
基金
国家自然科学基金资助项目(61771085)
重庆市教育委员会科研资助项目(KJQN201900601)。
关键词
随机共振
轴承故障诊断
信噪比
周期信号
stochastic resonance
bearing fault diagnosis
signal-to-noise ratio
periodic signal
