基于稀疏采样的电能质量信号采集方法

Method of power quality signal acquisition based on sparse sampling

由于电能质量信号当中含有丰富的高频分量,如果使用基于传统的香农/奈奎斯特采样定理的频率进行采样,会对采样系统以及后续的数据存储和传输带来巨大的挑战。针对以上问题,提出一种基于稀疏采样的电能质量信号采集方法。通过模拟信息转换器将模拟电能信号转化为离散信号,采用基于压缩感知原理的稀疏采样方式对电能质量信号进行重构,从而高效准确地获取电能质量信号,发现可能的故障信号,保证电力系统稳定运行,提高居民和工业用电质量。实验结果表明,采用该算法对电能质量信号进行重构,所得信号与实际信号之间误差较小,可以高效准确地采集电能质量信号。

Because the power quality signal contains abundant high frequency components, it will bring great challenges to sampling system and subsequent data storage and transmission if the sampling frequency is determined by Shannon/Nyquist theorem. In view of the above problems, a new method of power quality signal acquisition based on sparse sampling was proposed. Analog electrical signals were transformed for discrete signals by analog-to-information converter and the power quality signals awere reconstructed by the sparse sampling method based on the compressed sensing principle. Thus the power quality signals could be obtained efficiently and accurately, the possible fault signals could be found, the power system could be kept in the stable operation and the quality of residential and industrial power could be improved. The experimental results show that, the error between the signal obtained by reconstruction and the actual signal is small and the method proposed in this paper can be used to collect power quality signals efficiently and accurately.