摘要
针对Hg-CEMS中光电倍增管输出的电压峰信号噪声统计特性随工况的变化而变化,提出了一种模糊扩展卡尔曼滤波(FEKF)算法。该算法根据实际观测新息的均值和方差通过模糊控制器对观测噪声的理论方差阵不断调整,从而实现卡尔曼滤波器对含噪电压峰信号的自适应滤波处理。仿真结果表明,在理论噪声特性偏离实际工况时,该方法滤波效果明显优于常规扩展卡尔曼滤波算法,且具有较强的适应性。
A fuzzy extended Kalman filter（ FEKF） algorithm is proposed to deal with the changes of the statistical characteristics of the voltage peak signal noise of the output of the photomultiplier tube in Hg-CEMS that vary with the operating conditions. The algorithm continuously adjusts the theoretical variance matrix of the observation noise by the fuzzy controller according to the mean and variance of the actual observation innovation,so as to realize the Kalman filter adaptive filtering of the noisy voltage peak signal. The simulation results show that when the theoretical noise characteristics deviate from the actual operating conditions,the filtering effect of this method is obviously better than the conventional extended Kalman filter algorithm,and it has a strong adaptability.
作者
骆毅
程力
段钰锋
蔡欣
LUO Yi;CHENG Li;DUAN Yufeng;CAI Xin(Key Laboratory of Energy Thermal Conversion and Control of Ministry of Education,Southeast University,Nanjing 210096,China;Jiangsu Huadian Wangting Power Plant,Jiangsu Suzhou 215155,China)
出处
《工业仪表与自动化装置》
2018年第3期3-6,共4页
Industrial Instrumentation & Automation
基金
国家重点研发计划项目(2016YFC0201105)
作者简介
骆毅（1992-），男，硕士研究生，主要从事热工自动化与仪器信号处理方向的研究。
