EMD在LabVIEW中的实现及其在水轮机主轴振动信号分析中的应用

LabVIEW Realization of EMD and Its Application in Vibration Signal Analysis of Turbine Main Shaft

针对LabVIEW中缺少经验模态分解(EMD)算法模块的问题,对LabVIEW进行了二次开发,建立了基于LabVIEW的EMD模块,为振动故障信号分析提供了有效的工具,进而以水轮机故障信号的振动特征和故障产生机理为依据,将此算法运用于水轮机主轴振动信号分析,以河北省西达水电站水轮机主轴振动数据为基本资料,对分解得到的高频本征模函数(IMF)分量做包络谱分析,提取故障信息,并与轴心轨迹分析方法相结合加以验证。结果表明,该方法能够有效判别出水轮机主轴故障类型,可应用于水轮机主轴振动信号分析。

Aiming at the absence of empirical mode decomposition（EMD）algorithm in the graphics software LabVIEW,the algorithm was used to secondarily exploit in the LabVIEW,and the EMD module based LabVIEW was established,which provides an effective tool for vibration fault signal analysis.Based on the fault developing mechanism and vibration characteristics of water turbine,the algorithm was used to analyze the fault signal of the main shaft in water turbine.The vibration data of main shaft in Xida Hydropower Station located in Hebei Province were analyzed.After decomposition,the component of high frequency intrinsic mode function（IMF）was gained.Then the envelope spectrum was used to analyze the IMF to extract fault information.Combined with the shaft centerline orbit analysis,the EMD algorithm can effectively distinguish the faults.The results verify that it is an effective method,which can be applied to vibration signal analysis of turbine main shaft.