中文摘要：

特征提取是机械设备状态监测和故障诊断过程中最基本、最关键的一部分,针对现有各种提取方法的不同缺点,提出一种自适应信号分解技术来实现旋转机械振动信号的特征提取。该方法是一种改进的匹配追踪算法,不需要构造任何参数表达的基函数,而是将观察信号分解为一系列波形的组合,这些波形由非参数波形估计方法计算而来,用以匹配信号的局部结构。非参数波形估计方法中模板信号的自适应调整使该方法也不需要具有任何信号的先验知识,因而在实际应用中具有更加良好的柔性和适应性。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,即使是在噪声和信号中特征波形频带重叠的情况下也能将信号分离和提取出来。

英文摘要：

Feature extraction of vibration signal as a part of condition monitoring and fault diagnosis of mechanical equipment is a fundamental and key issue and has been proven to be highly effective. Focusing on the defects of different signal representation, an adaptive signal decomposition technique is presented to extract fault feature waveform from vibration signals. This method is a modified algorithm of matching pursuit （MP） which decomposes the observed signal into series of expansion of waveforms, these waveforms are calculated by the nonparametric waveform estimation （NWE） and used to best match the signal local structures. So, the construction of general basis function described by some parameters is unnecessary. A prior information about the observed signal is no more required for the template signal in the NWE owing to applying the adaptive template signal, which felicitates the method for a wide variety of applications. Both computer simulation and experimental results verify this approach is practicable and effective, even if the noise frequency band coinsides with that of the feature waveform of the signal.