针对经验模态分解(Empirical Mode Decomposition,EMD)中存在的端点效应问题,提出一种波形特征匹配延拓与余弦窗函数相结合的改进方法.首先对信号进行波形特征匹配延拓,实现延拓数据与原信号交界处的光滑过渡,避免边界处瞬时频率的跳跃；其次针对该延拓方法存在延拓误差的问题,对信号加余弦窗处理,将延拓误差控制在信号两端,使其无法(或以较慢速度)向数据内部发展,保证信号有效数据的正确分解,提高信号的分解精度,实现EMD算法的改进.通过仿真分析和不对中故障诊断实例研究表明,该方法能较好地抑制EMD端点效应,实现旋转机械故障的有效诊断.%For the end effect of empirical mode decomposition ( EMD) , a novel improved method combining waveform feature matching extension and cosine window function was proposed. Firstly, waveform feature matching extension was used to achieve a smooth transition at the junction of an original signal and its extension and avoid the instantaneous frequency jump at the boundary. Secondly, aiming at existing extension error in the extension method, the signal was processed with cosine window function. Thus, the error was controlled at both ends so that it could not spread or spreaded at a slower speed to the internal signal. This ensured the correct decomposition of the effective data, and raised the decomposition accuracy to realize the EMD algorithm improvement. Simulation results and misalignment fault diagnosis examples showed that the improved method can inhibit end effect effectively in rotating machinery fault diagnosis.
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