自适应随机共振在信号特征提取中的应用  

Application of adaptive stochastic resonance in signal feature extraction

作　　者：杨波[1,2] 夏虹[1,2] 尹文哲 王志超[1,2] 张汲宇 姜莹莹 YANG Bo;XIA Hong;YIN Wenzhe;WANG Zhichao;ZHANG Jiyu;JIANG Yingying(Key Laboratory of Nuclear Safety and Advanced Nuclear Energy Technology,Ministry of Industry and Information Technology,Harbin Engineering University,Harbin 150001,China;Fundamental Science on Nuclear Safety and Simulation Technology Laboratory,Harbin Engineering University,Harbin 150001,China)

机构地区：[1]哈尔滨工程大学核安全与先进核能技术工业和信息化部重点实验室,黑龙江哈尔滨150001 [2]哈尔滨工程大学核安全与仿真技术重点学科实验室,黑龙江哈尔滨150001

出　　处：《哈尔滨工程大学学报》2022年第12期1750-1758,共9页Journal of Harbin Engineering University

基　　金：国家自然科学基金项目(U21B2083).

摘　　要：针对强背景噪声下旋转机械振动信号特征难以提取的问题,本文提出了一种自适应多稳态欠阻尼随机共振方法应用于该信号的特征提取。本文对随机共振的机理、计算方法等理论进行了研究,通过仿真实验验证了该方法的适用性,通过采用粒子群优化算法对随机共振系统中涉及到的参数进行自适应选择,利用该方法在滚动轴承实验数据上进行了验证。结果表明:本文所提出的方法能够有效过滤掉信号中的噪声信号,同时放大信号的特征,提高输出信号的信噪比。Under strong background noise,the features of rotating machinery′s vibration signals cannot be easily extracted.An adaptive multistable underdamped stochastic resonance(SR)method is proposed to solve this problem.First,the theory of the mechanism and calculation method of SR is investigated to verify the applicability of the method through simulation experiments.Then,the parameters involved in the SR system are selected adaptively by a particle swarm optimization algorithm,verifying the method on the experimental data of rolling bearings.The results show that the proposed method can effectively filter out noise signals,amplify the signal characteristics,and improve the signal-to-noise ratio of output signals.

关 键 词：核电厂 旋转机械 振动信号 自适应 滚动轴承 随机共振 粒子群优化 特征提取 

分 类 号：TL48[核科学技术—核技术及应用]