摘要
引入基于高斯滤波的自适应去噪算法,结合R检验法进行历史数据的稳态检测.选取某1 000MW机组的总风量数据,在相同参数条件下对该方法和中值滤波法进行仿真对比.结果表明:自适应高斯滤波法具有更好的去噪效果和突变点信息保留能力,基于该方法的稳态检测对短时间稳态检验的灵敏度较高,且对稳态与非稳态的状态切换边界识别更准确.
Combining the de-noising algorithm based on adaptive Gauss filter with the R-statistic method,a steady-state detection was carried out to power plant history data.Taking the total air volume data of a1 000 MW unit as an object of study,simulation comparison was made between the previously proposed method and the median filter method under same working conditions.Results show that the method based on adaptive Gauss filter has better de-noising effectiveness and larger retention capacity on point mutation information,which is of high sensitivity in short time steady-state detection,and of high accuracy in switching boundary identification between steady-state and unsteady-state detection.
出处
《动力工程学报》
CAS
CSCD
北大核心
2014年第9期708-713,共6页
Journal of Chinese Society of Power Engineering
基金
国家自然科学基金重点资助项目(51036002)
关键词
自适应高斯滤波
稳态检测
R检验法
在线检测
adaptive Gauss filter
steady-state detection
R-statistic method
on-line detection
