摘要
采用经验模态分解和能量特征值对振动加速度传感器获取的汽车齿轮箱振动信号进行特性分析.利用经验模态分解获得振动信号的本征模态函数,并对本征模态函数进行系数-能量计算,提取系统的特征信息,对汽车齿轮箱的故障进行诊断,从而实现在线监测汽车齿轮变速箱运转工作状态,及时发现齿轮箱的早期故障,提高汽车运行的安全性.仿真研究结果表明经验模态分解方法在故障信息诊断方面是可行的和有效的,并能够提高故障检测的可靠性.
Characteristics analysis of automobile change gear box vibration signals capture from vibrating acceleration sensor based on empirical mode decomposition （EMD） and energy characteristic value was proposed . The vibration signal was firstly decomposed into intrinsic mode function （IMF） by the empirical mode decomposition method. Then the fault information diagnosis of the automobile gearbox vibration signals could be extracted from the coefficient-energy value of intrinsic mode function. It was automobile security to do some research on how to monitor operating state of automobile significant for the incipient faults as soon as possible. Experiment results have shown the feasibility and efficiency of the EMD method in fault message diagnosis, additionally, the algorithm was very reliable to be implemented with fault detection.
出处
《安徽大学学报（自然科学版）》
CAS
北大核心
2009年第2期35-38,共4页
Journal of Anhui University(Natural Science Edition)
基金
国家自然科学基金资助项目(60771033)
安徽省教育厅自然科学基金资助项目(KJ2008B094)
