Intelligent Monitoring Method of Current Transformer Abnormal Data Based on N-LMS Algorithm
In order to improve the accuracy of intelligent monitoring of current transformer abnormal data and meet the monito-ring requirements of multiple working conditions,an intelligent monitoring method of current transformer abnormal data based on N-LMS algorithm is designed.This paper sets the sampling parameters of power grid reference voltage signal to obtain the value of data characteristic dimension ality by random sampling method,and process the voltage value by equal width method to obtain the relationship between each group of data.In order to avoid the influence of voltage waveform distortion on the detec-tion results,the adaptive filtering method is used to detect the harmonic current,so that the feedback error is close to zero.The rough set rules of current transformer are extracted,the decision table is made,and the fault section is determined by com-bining with the decision table.The design of intelligent monitoring method of current transformer abnormal data based on N-LMS algorithm is realized.The experimental results show that the monitoring method has high accuracy in the monitoring of leakage current,capacitance and harmonic current waveform,the dielectric loss monitoring of phase boost process of current transformer and the dielectric loss monitoring of phase a step-down process of current transformer,and meets the design re-quirements of the method.
万方数据
维普
