摘要
为提高交流电力功率性能指标的测试精度和实时性,基于相关性分析和最小二乘误差理论,研究了交流电力智能传感器的粗信号处理方法.采用最小二乘特征参数法,对交流电压和电流值的初始采样点进行估算,获得了电力功率参数.在此基础上,将最小二乘特征参数法与相关分析法进行了比较,给出了基于相关分析法和最小二乘特征参数法进行功率测试的运算量公式,并分析了运算的复杂度.实验结果表明,当干扰幅值从信号幅值的3%放宽至12%时,基于最小二乘特征参数法的粗信号处理方法与现有方法相比,其计算工作量可减少49.4%,测试误差减少了2/3,同时降低了系统的信/噪比要求.
In order to improve the testing precision and real-time performance of the AC electrical power performance index,the coarse signal processing approach of AC power intelligent sensor was studied based on the theory of correlation analysis method and the least-squares method.The least-squares characteristic parameters method was used to estimate the initial sample points of AC voltage and AC current,and the electrical power parameters were obtained.The formulas of calculating quantity and computation complexity were discussed by comparing the least-squares characteristic parameters method with the correlation analysis method.The results show that when the noise signal amplitude is permitted from 3% to 12%,the proposed method can reduce the processing time by 49.4% and decrease the testing error by 2/3,and the requirement for the signal-to-noise ratio of the system can also be reduced as opposed to the traditional method.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2011年第4期598-603,共6页
Journal of Southwest Jiaotong University
基金
四川省教育厅科研基金资助项目(08ZC010)
四川省机械电子工程重点学科(西华大学)
四川省制造与自动化重点实验室(西华大学)研究基金
