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组合模函数方法及其在机械故障诊断中的应用

, PP. 85-89

Keywords: 机械工程,经验模式分解,健康监测,振动分析,时频分析

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Abstract:

针对信号被噪声污染时,经验模式分解(empiricalmodedecomposition,EMD)分析信号得到的本征模函数(intrinsicmodefunction,IMF)会发生明显畸变,从而降低经验模式分解精度这一问题,提出了组合模函数方法。该方法利用经验模式分解算法对信号进行分解,然后将特定的本征模函数组合起来,从而得到一个新的带宽依据信号特点自适应变化的带通滤波器,揭示信号特征。将所提出的方法应用于仿真数据及某电厂发电机组高压缸振动超限故障数据分析。结果表明组合模函数方法能够较好地解决本征模函数畸变问题,明显提高经验模式分解精度,有助于精确提取故障特征和正确诊断故障类型;组合模函数方法对工程环境采集的机械设备故障数据分析和特征提取具有一定实用价值。

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