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Novel outlier-resistant extended Kalman filter for robust online structural identification
He-Qing Mu; Ka-Veng Yuen
2014-05-29
Source PublicationJournal of Engineering Mechanics
ISSN1943-7889
Volume141Issue:1
Abstract

Structural health monitoring (SHM) using dynamic response measurement has received tremendous attention over the last decades. In practical circumstances, outliers may exist in the measurements that lead to undesirable identification results. Therefore, detection and special treatment of outliers are important. Unfortunately, this issue has rarely been taken into systematic consideration in SHM. In this paper, a novel outlier-resistant extended Kalman filter (OR-EKF) is proposed for outlier detection and robust online structural parametric identification using dynamic response data possibly contaminated with outliers. Instead of definite judgment on the outlierness of a data point, the proposed OR-EKF provides the probability of outlier for the measurement at each time step. By excluding the identified outliers, the OR-EKF ensures the stability and reliability of the estimation. In the illustrative examples, the OR-EKF is applied to parametric identification for structural systems with time-varying stiffness in comparison with the plain EKF. The structural response measurements are contaminated with outliers in addition to Gaussian noise. The proposed OR-EKF is capable of outlier detection, and it can capture the degrading stiffness trend with more stable and reliable results than the EKF. 

KeywordBayesian Inference Model Updating Online Algorithm Outlier Detection Robust Kalman Filter Structural Health Monitoring System Identification
DOI10.1061/(ASCE)EM.1943-7889.0000810
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering
WOS SubjectEngineering, Mechanical
WOS IDWOS:000346638100003
PublisherASCE-AMER SOC CIVIL ENGINEERS, 1801 ALEXANDER BELL DR, RESTON, VA 20191-4400
The Source to ArticleScopus
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Cited Times [WOS]:54   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorKa-Veng Yuen
AffiliationFaculty of Science and Technology, Univ. of Macau, Macao 999078, China.
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
He-Qing Mu,Ka-Veng Yuen. Novel outlier-resistant extended Kalman filter for robust online structural identification[J]. Journal of Engineering Mechanics,2014,141(1).
APA He-Qing Mu,&Ka-Veng Yuen.(2014).Novel outlier-resistant extended Kalman filter for robust online structural identification.Journal of Engineering Mechanics,141(1).
MLA He-Qing Mu,et al."Novel outlier-resistant extended Kalman filter for robust online structural identification".Journal of Engineering Mechanics 141.1(2014).
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