CAJ | 학술논문

针对机械设备状态监测和故障诊断过程中的特征提取问题,提出一种基于白噪声统计特性来实现机械振动信号振动模式提取的方法.该方法是对经验模式分解算法(Empirical mode decomposition,EMD)的一种发展,应用归一化白噪声在EMD中具有的统计特性,可以自适应地消除机械振动信号经EMD分解产生的高频噪声分量及低频虚假分量,得到反映信号实际物理意义的振动模式分量集.对该振动模式分量集进行Hilbert变换,提取出信号的Hilbert时频特征.整个特征提取过程不需要构造任何参数表达的基函数及相关滤波函数,也无需有关信号的任何先验知识,因而在实际应用中具有更好的适用性.仿真信号和转子试验台试验信号验证该方法的可行性和有效性.
침대궤계설비상태감측화고장진단과정중적특정제취문제,제출일충기우백조성통계특성래실현궤계진동신호진동모식제취적방법.해방법시대경험모식분해산법(Empirical mode decomposition,EMD)적일충발전,응용귀일화백조성재EMD중구유적통계특성,가이자괄응지소제궤계진동신호경EMD분해산생적고빈조성분량급저빈허가분량,득도반영신호실제물리의의적진동모식분량집.대해진동모식분량집진행Hilbert변환,제취출신호적Hilbert시빈특정.정개특정제취과정불수요구조임하삼수표체적기함수급상관려파함수,야무수유관신호적임하선험지식,인이재실제응용중구유경호적괄용성.방진신호화전자시험태시험신호험증해방법적가행성화유효성.
Focusing on feature extraction in condition monitoring and fault diagnosis of mechanical equipment, a method based on the characteristics of white noise is presented to extract vibration mode from mechanical vibration signal. This method is a developed algorithm of empirical mode decomposition (EMD), which adaptively eliminates high frequency noise components and low frequency false components by applying the characteristics of normalized white noise under EMD, so the intrinsic mode set reflecting actual physical meaning of vibration signal is obtained. Hilbert transform is performed to the extracted intrinsic mode set, and the Hilbert time-frequency feature of observed signals are extracted. In the whole feature extracting process, the construction of general basis function described by some parameters and related filter function is unnecessary, and any prior information about the observed signal is no more required, so the method has a better applicability in actual applications. Both computer simulation and rotor set experimental results verify this approach is feasible and effective.