自适应ANC技术在热工特征信号提取中的应用研究

Study on Adaptive Noise Cancelling and Its Application on Characteristic Extracting for Thermal Process

随着对火电厂控制运行水平的要求不断提高,先进的控制、诊断、优化功能需要一些难以测量或测量不准确的状态参量,而该类参量往往包含有很多噪声干扰难以直接分析。为更好分析热工过程对象特性,还原被噪声所掩盖的潜在信息,提出了一种改进的Sigmoid函数变步长LMS算法,利用自适应噪声抵消的方法对受到扰动影响的热工对象输出数据进行分析处理,降低干扰因素影响,从而使原始特征信号得到相对精确的恢复。现场数据分析表明了该算法的有效性和可行性。

Along with the increasing requests of the control level for power plant operation,the accurate state parameters are needed for the advanced control,diagnosis and optimization function.But the clarity of the signal of the state parameter is obscured by all kinds of noise in thermal system and difficult to analyse.To analyse the thermal system and pick up the information covered by the noise,an improved variable step -size LMS method based on Sigmoid function was presented.Adaptive noise canceling method is used to process the input and output signal of thermal system,and the disturbance is reduced,the characteristic of the system is extracted.The experiment proves this method is effective and feasible for thermal processes signal analyzing.