参数化局部特征尺度分解及其在复合故障诊断中的应用研究

Parameterized local characteristic scale decomposition and its application in composite fault diagnosis

为了消除局部特征尺度分解方法出现一阶导数不连续的问题,设计了Hermite插值与可调参数相结合的解决方案。构造了参数化Hermite插值方法,通过调整可调参数可以进一步逼近理想曲线;提出了参数化局部特征尺度分解方法,该方法的核心在于利用了参数化Hermite插值获得拟合曲线,并通过调整可调参数λ获得了更加理想的分量信号,克服了LCD分解过程中出现的拟合误差问题,并将所提方法应用于复合故障仿真信号和实际信号。研究结果表明:与LCD和经验模态分解方法相比,PLCD方法可以有效地提取微弱信号的故障特征。

In order to eliminate the discontinuity of the first derivative in local characteristic scale decomposition(LCD)method,the solution of Hermite interpolation combined with adjustable parameters was designed.A parameterized Hermite interpolation method was constructed,which could be further approximated by adjusting the adjustable parameters.A parameterized local characteristic scale decomposition method was proposed,the core of this method was to obtain fitting curve by parameterized Hermite interpolation.The more ideal component signal was got by adjusting adjustable parametersλ,the fitting error of LCD in decomposition process was overcame.The proposed method was applied to simulated and actual signals of composite faults.The results indicate that compared with LCD and empirical mode decomposition(EMD),PLCD can effectively extract the fault features of weak signals.