东南大学学报（自然科学版）2016，Vol.46Issue(2)：249-254,6.DOI:10.3969/j.issn.1001-0505.2016.02.004
基于数据驱动的 KPI 系统最优滤波器设计
Data-driven based optimal filter design for KPI system
摘要
Abstract
In order to optimize the data-driven design of embedded fault diagnosis filters, a FDI ( fault detection and isolation) residual generator is presented based on KPI ( key performance in-dex) , and a design method for the closed-loop Kalman filter based on the multi-diagnostic observers ( mDOs) is studied to realize fault diagnosis and effective observation for system status.First, the KPI subspace model for the large complex system is obtained based on the sampling data.The track-ing error is defined, and the closed-loop filter is realized.Then, the residual sequence is expressed as the Hankel mode.A new threshold matrix is constructed by defining an orthogonal projection complement matrix as well as selecting appropriate data columns.Finally, the calculation method for the Kalman filter gain is obtained, and the design steps for the optimal Kalman filter are described. The results show that the amplitude of the optimized residual is half that of the pre-optimized residu-al.The data-driven based optimal filter design for the KPI system can improve the monitoring sensi-tivity for tiny fault and optimize both status estimating and fault diagnosis.关键词
KPI/残差/观测器/滤波器Key words
KPI( key performance index)/residual/observer/filter分类
信息技术与安全科学引用本文复制引用
姚智刚,彭开香..基于数据驱动的 KPI 系统最优滤波器设计[J].东南大学学报（自然科学版）,2016,46(2):249-254,6.基金项目
国家自然科学基金资助项目（61473033）． （）
