摘要
针对机械系统早期微弱故障信号难识别诊断问题,提出一阶线性系统调参广义随机共振的特征提取方法,该方法基于调节一阶线性系统参数,可以得到信噪比取极大值的广义随机共振现象。为得到清晰的特征信号,以可辨识性为优化目标,给出了系统参数、信号频率、采样频率等参数之间的选择关系。滑动轴承试验台上转子轴的早期微弱故障模拟实验,验证了此方法的有效性。
Aiming at recognizing a weak fault signal in its early stage, a feature extraction method of a signal based on the parameter-adjusted stochastic resonance （SR） of a first-order linear system in a broad sense was presented here. This method was based on a generalized stochastic resonance phenomenon that the output signal-to-noise ratio （SNR） reaches a maximum by tuning parameters of a first-order linear system. To acquire a more distinct characteristic signal, the selecting relations among system parameters, signal frequencies and sampling rates were explained taking the best signal reognition as an optimization objective. Finally, the analog test rotor shaft＇s early weak fault obtained on a test-bed of sliding bearings verified the effectiveness of this method.
出处
《振动与冲击》
EI
CSCD
北大核心
2014年第17期1-5,共5页
Journal of Vibration and Shock
基金
国家自然科学基金(51275336)
高等学校博士学科点专项科研基金(20120032110001)
关键词
一阶线性系统
调参广义随机共振
微弱信号
故障诊断
first-order linear system
parameter-adjusted SR in a broad sense
weak signal
fault diagnosis
作者简介
第一作者冷永刚男，教授，1964年11月生
通信作者 田祥友男，硕士，1989年9月生
