摘要
为提高发电机励磁系统参数辨识精度,以MEC3300T型励磁系统为例,提出分别采用伪随机信号和阶跃信号作为扰动信号,利用混沌遗传算法对励磁系统的参数进行辨识,分析了不同的采样频率下不同扰动信号与参数辨识精度的关系及在相同的采样频率下不同信噪比的扰动信号对参数辨识精度的影响。结果表明,采用PRBS信号作为扰动信号时,辨识结果的相对误差随着采样频率的改变有一定的波动,而STEP信号为扰动信号时辨识结果的相对误差相对稳定;同一采样频率下,采样PRBS与STEP信号辨识结果的相对误差均随信噪比的增加呈指数增长。
In order to improve the accuracy of parameter identification for generator excitation system,this paper proposes pseudo-random signal(PRBS) and step signal(STEP) to be disturbance signal,and the parameters are identified by using chaos genetic algorithm based on excitation system MEC3300T,respectively.And then the relationship between disturbance signal and the accuracy of parameter identification is analyzed for different sampling frequencies.Finally,it analyzes the impact of disturbance signals with different signal-to-noise ratio on the accuracy of parameter identification.The results show that the relative errors change with the sampling frequency when the disturbance signal is PRBS while the relative error remains stable when it is STEP;the PRBS and STEP sampling signal with the same frequency,the relative error grows in exponential form along with the increase of signal-to-noise rate(SNR).
出处
《水电能源科学》
北大核心
2013年第6期177-181,共5页
Water Resources and Power
基金
国家自然科学基金资助重点项目(51137002)
江苏省自然科学基金资助项目(BK2011026)
关键词
励磁系统
扰动信号
混沌遗传算法
辨识精度
excitation system
disturbance signal
chaotic genetic algorithm
identification accuracy