摘要
软件同步是数字化测量工频信号常用的采样方法。参数自寻优智能采样用爬山搜索法使误差判据最小,得到每个测量周期的采样次数N和采样间隔tS,最大限度地减小了同步误差或周期截断误差。进一步校正参数自寻优,让测量值乘上一个针对实时周期Tp寻优得到的校正参数kc,使其能最大限度地逼近信号的实际值。遍历频点的仿真结果表明:最优采样参数使工频范围内67%以上频率点的同步误差为零,其余点上的失步也在1～3个td(微处理器中定时器的分辨率),采样精度达到10-5数量级;传统采样法的测量值经校正后向零误差逼近,采样精度达10-6数量级;在基波条件下寻优得来的参数Nt、S和kc对未知谐波同样有效。分析了自寻优智能采样法的实时性,提出了“软件硬化”的思想,使微处理器开销压缩,提高了在线寻优效率。
The software synchronization is always used in digital measuring of power frequency. The intelligent sampling with parameter self-optimizing uses mountain-climb searching with minimal error criterion to obtain the sampling number N and the interval ts of each measurement period,which reduces the synchronization error or cycle truncation error. The real value is approached by multiplying the measured value by the correction parameter k c,which is self-optimized according to real-time period Tp. Simulation results prove ：the synchronous errors of over 67 % of covered periods are zero,and the remainders are only （1- 3）td（timer resolution of microprocessor） , the sampling precision is about 10^-5;after the correction,the measured value by traditional sampling approaches zero error,and the sampling precision is about 10^-6;the optimized parameters for fundamental are also effective on unknown harmonics. The real- time performance of intelligent sampling with parameter self-optimizing is analyzed and the idea of ＂software hardening＂ is proposed to lower microprocessor load and increase online optimizing efficiency.
出处
《电力自动化设备》
EI
CSCD
北大核心
2007年第6期66-70,共5页
Electric Power Automation Equipment
关键词
软件同步采样
参数自寻优
误差频谱
校正参数
软件硬化
software synchronous sampling
parameter self-optimizing
error spectrum
correction parameter
software hardening
