摘要
为了灵活处理复杂的大型同步发电机突然三相短路试验的动态数据,本文给出了如何利用LabWindows/CVI设计软件开发大型同步发电机动态参数辨识虚拟仪器(VI)的方法,其中重点阐述了通过混合编程原理调用MATLAB中的小波消噪法(wden())去除噪声对动态测试信号的干扰及利用非线性最小二乘回归算法(lsqcurvefit())直接对发电机各试验的数学模型中各分量优化组合后进行参数辨识。通过汽轮发电机QFSN-600-2YH的突然三相短路试验数据应用上述算法辨识了发电机的瞬态参数。
In order to flexibly process complicated transient data of sudden mree-pnase snort-circuit test of large synchronous generators, this paper presents methods of how to develop a virtual instrument （VI） to identify transient parameters of large synchronous machines on LabWindows/CVI platform, where it emphasizes the mixed programming method to call the MATLAB function （wdenO） which can eliminate the noise of a signal using wavelet arithmetic and the function （lsqcurvefit（）） that fits the noise-eliminated wave by nonlinear least square method. The present paper estimates the transient parameters of a turbogenerator （QFSN-600-2YH） from the short-circuit currents by the above methods.
出处
《大电机技术》
北大核心
2005年第6期21-23,共3页
Large Electric Machine and Hydraulic Turbine
