基于大数据分析的电力计量装置故障诊断技术研究

Research on Fault Diagnosis Technology of Electric Power Metering Device Based on Big Data Analysis

故障诊断可以保证电力计量装置的安全稳定运行。为提高故障诊断精度,提出了基于大数据分析的电力计量装置故障诊断技术研究。利用电力计量装置的电流基波频率和极对数,计算电力计量装置的脉振磁势,由于电力计量装置的内部转子在脉冲磁场下会失去平衡,影响电力计量装置的气隙磁导,通过计算电力计量装置的磁力,分析电力计量装置的故障大数据。引入共振稀疏分解,对电力计量装置故障信号进行稀疏分解,提取故障诊断需要的信号特征,根据故障信号的运行周期,计算故障信号的特性,利用故障诊断函数,判断电力计量装置是否发生故障,实现电力计量装置的故障诊断。实验结果表明,该技术对电力计量装置的电压故障数据和电流故障数据具有较高的诊断精度。

Fault diagnosis can ensure the safe and stable operation of power metering devices.In order to improve the accuracy of fault diagnosis,the research on fault diagnosis technology of power metering device based on Big data analysis is proposed.The pulsating magnetic potential of the power metering device is calculated by using the current fundamental frequency and pole pair of the power metering device.Considering that the internal rotor of the power metering device will lose balance under the pulse magnetic field,which will affect the air gap magnetic conductance of the power metering device,the fault Big data of the power metering device is analyzed by calculating the magnetic force of the power metering device.Introducing resonance sparse decomposition to perform sparse decomposition on the fault signal of the power metering device,extracting the signal features required for fault diagnosis,calculating the characteristics of the fault signal based on the operating cycle of the fault signal,and using the fault diagnosis function to determine whether the power metering device has malfunctioned,achieving fault diagnosis of the power metering device.The experimental results indicate that this technology has high diagnostic accuracy for voltage fault data and current fault data of power metering devices.