采用余弦拟合的随机共振反演技术研究  

Study of Stochastic Resonance Recovery Based on Cosine Fitting

作　　者：谭继勇[1] 陈雪峰[1] 何正嘉[1] 

机构地区：[1]西安交通大学机械制造系统工程国家重点实验室,西安710049

出　　处：《西安交通大学学报》2010年第1期41-45,共5页Journal of Xi'an Jiaotong University

基　　金：国家自然科学基金资助项目(50875195);全国优秀博士论文资助项目(2007B33)

摘　　要：针对当前随机共振反演方法实施过程流程复杂、需要调节的参数繁多、对幅值的估计不准,以及难以处理频率相差较大的多频信号等诸多问题,提出了一种新的采用余弦拟合的随机共振反演算法.该算法采用移频变尺度随机共振检测频率,利用所得频率设计余弦曲线对输入信号进行最小二乘拟合,不需对特殊点进行特别处理,幅值不受波形畸变的影响,因此可以处理频率相差任意大小的多频信号.通过数值仿真和机车走行部故障的诊断,验证了该算法具有较强的工程实用性,同时结合频谱校正技术可以进一步提高该方法的精确性,更准确地检测出信号频率及幅值.The conventional stochastic resonance recovery techniques are facing some troubles,such as the complex process,too many parameters,wrong estimated amplitudes,and especially the difficulty for processing the multifrequency signals with frequencies staying far away from one another.A new strategy is proposed,where frequency-shifted and re-scaling stochastic resonance are adopted to detect frequencies,the input signals are least square fitted with cosines designed based on the acquired frequencies,and no special postprocessing is required for the distorted points,the waveform distortion has no influence on the amplitude quantization.Almost all the multifrequency signals can be processed.The effectiveness is validated by a simulation and a fault quantitative diagnostic case of electric locomotive running parts.The amplitude of periodic signals can be reduced by non-periodic sampling,the accuracy is thus developed by involving the spectrum correction technology,and more accurate signal frequencies and amplitudes can be detected.

关 键 词：余弦拟合 随机共振 反演 

分 类 号：TH17[机械工程—机械制造及自动化]