计量学报2017，Vol.38Issue(5)：602-606,5.DOI:10.3969/j.issn.1000-1158.2017.05.18
基于自适应随机共振的齿轮微弱冲击故障信号增强提取方法研究
Enhancement and Extraction of Gear Weak Impact Fault Signal Based on an Adaptive Stochastic Resonance
摘要
Abstract
Aiming at the problem of impact signal detection under strong noise background,an adaptive stochastic resonance method for enhancement and extraction of gear weak impact Fault Signal is proposed.First,a new modified kurtosis index is constructed by using kurtosis index and correlation coefficient,which is applied as the measurement index of stochastic resonance for the detection of impact signals.Second,a data segmentation algorithm via sliding window is adopted to segment the impact signal with different impact amplitudes into multiple sub-signals with single impact component,which are used as the system input of stochastic resonance.And the genetic algorithm is employed to realize the adaptive selection of system parameters.Finally,the proposed method is applied to gearbox fault diagnosis of traveling unit of electric locomotive.The results show that this method can effectively extract the features of gear fault.关键词
计量学/冲击特征提取/随机共振/滑动窗/修正峭度指标/齿轮箱故障诊断Key words
metrology/impact feature extraction/stochastic resonance/sliding window/modified kurtosis index/fault diagnosis of gearbox分类
通用工业技术引用本文复制引用
李继猛,张云刚,张金凤,谢平..基于自适应随机共振的齿轮微弱冲击故障信号增强提取方法研究[J].计量学报,2017,38(5):602-606,5.基金项目
国家自然科学基金(51505415) （51505415）
中国博士后科学基金(2015M571279) （2015M571279）
秦皇岛市科技支撑计划项目(201502A008) （201502A008）
