摘要
为了解决常规谱分析技术在列车轴承故障诊断中的误诊和漏诊问题,分析了列车轴承频带变化类故障的振动机理,研究了一种基于数据插值重采样分析的诊断方法;通过脉冲触发式整周期采样技术以及等角度重采样、特诊谱提取技术等信号处理方法,实现列车频带变化类故障的精确诊断.仿真分析与实验结果表明,该诊断方法能准确、有效地识别列车轴承早期故障.
To solve the problems of the conventional spectral analysis method in train bearing fault diagnosis that always lead to misdiagnosis and missed diagnosis,the paper analyzes the vibration mechanism of the train bearing spectrum-varying fault,and proposes a diagnosis method based on data interpolation re-sampling analysis.The train bearing＇s vibration integral periodic and equal angle signal is collected through the pulse-triggered sampling method which is researched in this paper.Through the data interpolation and characteristic spectral identification method,the train＇s vibration frequency spectrum-varying fault is easy to be diagnosed.Simulation analysis and experimental results show that this diagnostic method can accurately and effectively identify the train early bearing fault.
出处
《北京工业大学学报》
EI
CAS
CSCD
北大核心
2012年第5期678-682,共5页
Journal of Beijing University of Technology
基金
国家'八六三'计划资助项目(2006AA11Z230)
湖南省教育厅科学研究资助项目(08C329)
关键词
频带变化类故障
列车轴承
整周期采样
特征谱分析
frequency spectrum band varying fault
train bearing
integral periodic signal sampling
characteristic spectrum analysis
