摘要
滤波法是稳态检测应用较广泛的方法 ,但它不适用于检测变量含有过失误差的情况 ,而实际过程测量变量常含有过失误差。该文对滤波法进行改进 ,用新假设代替原不合理假设 ,根据数理统计理论 ,推导出用于稳态检测的统计量。该统计量能应用于检测数据含过失误差的情况 ,且当数据不含过失误差时 ,可以推导出原统计量。数值实验结果显示 ,原方法用于检测数据含过失误差时稳态检测失效 。
Filtering methods for checking steady state processes can not give correct results when the measurements have gross errors, which often occurs in chemical processing. A new method was developed using probability and statistics theory to develop a statistical filtering variable for steady state tests. The filter is applicable to steady state tests with process data containing gross errors. Previous filtering methods can be derived from the new method for process data without gross errors. Numerical experiments show that the new method reliably provides correct results when measurements have gross errors, while the old method fails to identify steady state.
出处
《清华大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2004年第9期1160-1162,共3页
Journal of Tsinghua University(Science and Technology)
基金
国家"八六三"高技术项目 ( 2 0 0 1AA413 2 2 0 )
关键词
稳态检测
滤波法
均值法
方差法
steady state test
filtered method
mean test method
variance test method