[1]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.[doi:10.3969/j.issn.1001-0505.2016.02.004]
 Yao Zhigang,Peng Kaixiang.Data-driven based optimal filter design for KPI system[J].Journal of Southeast University (Natural Science Edition),2016,46(2):249-254.[doi:10.3969/j.issn.1001-0505.2016.02.004]
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基于数据驱动的KPI系统最优滤波器设计()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
46
期数:
2016年第2期
页码:
249-254
栏目:
自动化
出版日期:
2016-03-20

文章信息/Info

Title:
Data-driven based optimal filter design for KPI system
作者:
姚智刚彭开香
北京科技大学自动化学院, 北京100083
Author(s):
Yao Zhigang Peng Kaixiang
School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
关键词:
KPI 残差 观测器 滤波器
Keywords:
KPI(key performance index) residual observer filter
分类号:
TP29
DOI:
10.3969/j.issn.1001-0505.2016.02.004
摘要:
为了优化基于数据驱动的嵌入式故障诊断滤波器设计,采用KPI(key performance index)思想设计FDI(fault detection and isolation)残差,研究基于mDOs观测器的闭环Kalman滤波器设计方法,实现故障诊断和系统状态的有效观测.首先,基于采样数据得到大型复杂系统的KPI子空间模型,定义了跟踪误差,得到了闭环滤波器;其次,将残差序列表示为Hankel模型,通过定义正交投影补矩阵并选择恰当的数据列,构建出新的阈值矩阵;最后,得到Kalman滤波增益的计算方法,并给出了最优Kalman滤波器的设计步骤.结果表明,优化后残差的幅值降低至优化前的1/2.基于数据驱动的KPI系统最优滤波器设计,可提高对弱小故障监测的灵敏度,实现系统状态估计和故障诊断的性能优化.
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 index), 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 tracking 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 residual. The data-driven based optimal filter design for the KPI system can improve the monitoring sensitivity for tiny fault and optimize both status estimating and fault diagnosis.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2015-08-04.
作者简介: 姚智刚(1980—),男,博士,讲师,xyhk_yzg@163.com.
基金项目: 国家自然科学基金资助项目(61473033).
引用本文: 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. DOI:10.3969/j.issn.1001-0505.2016.02.004.
更新日期/Last Update: 2016-03-20