摘要
将时频原子分解(time-frequency atom decomposition,TFAD)方法应用于电气化铁路谐波检测,然而计算量过大,制约了TFAD方法在信号处理中的应用。为降低其计算复杂度,利用差分进化(differential evolution,DE)算法优化原子参数,实现原子的最优匹配。通过对电气化铁路谐波电流实测数据的仿真分析,结果表明:基于DE的TFAD方法可以准确检测出相应的基波及各次谐波分量,验证了该算法的有效性。
When time-frequency atom decomposition （TFAD） method is applied to harmonic detection of electrified railway, too heavy calculation burden of TFAD restricts its application in signal processing. To reduce the computational complexity of TFAD, atom parameters are optimized by differential evolution （DE） and optimal matching among atoms is implemented. Simulation analysis on measured harmonic current data of electrified railway shows that using the DE-based TFAD method corresponding fundamental component and various harmonic components can be accurately detected, thus the effectiveness of the proposed algorithm is verified.
出处
《电网技术》
EI
CSCD
北大核心
2012年第12期211-216,共6页
Power System Technology
基金
国家自然科学基金项目(51177138)
中央高校基本科研业务费专项资金项目(SWJTU11ZT07)~~
关键词
时频原子分解
差分进化
谐波检测
电气化铁路
time-frequency atom decomposition
differential evolution
harmonic detection
electrified railway
