A new extension of unscented Kalman filter for structural health assessment with unknown input

Abdullah Al-Hussein, Achintya Haldar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A time-domain nonlinear system identification (SI)-based structural health assessment (SHA) procedure, using Unscented Kalman Filter (UKF) concept, is presented in this paper. It is a two-stage procedure. It integrates an iterative least squares technique and the unscented Kalman filter concept. The authors believe that the integrated procedure significantly improves the basic UKF concept. The procedure can assess the health of a structure using only a limited number of noise-contaminated acceleration time-histories measured only at a small part of a structure and does not need information on input excitation. The structures are represented by finite element models and the location and severity of defect(s) are assessed by tracking the changes in the stiffness properties of individual elements from their expected values. With the help of examples, it is demonstrated that the method is capable of accurately identifying defect-free and defective states of structures. Small and relatively large defects are introduced at different locations in the structure and the capability of the method to detect the health of the structure is examined. It is demonstrated that the accuracy of the method is much better than the other methods currently available for the structural health assessment. It is also superior to the extended Kalman filter. Considering the accuracy and robustness, the procedure can be used as a nondestructive structural health assessment procedure.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSPIE
Volume9061
ISBN (Print)9780819499875
DOIs
StatePublished - 2014
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014 - San Diego, CA, United States
Duration: Mar 10 2014Mar 13 2014

Other

OtherSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014
CountryUnited States
CitySan Diego, CA
Period3/10/143/13/14

Fingerprint

Unknown Inputs
Kalman filters
Kalman Filter
health
Health
Defects
defects
system identification
Nonlinear System Identification
Extended Kalman filters
Two-stage Procedure
nonlinear systems
Robustness (control systems)
Nonlinear systems
stiffness
Identification (control systems)
Expected Value
Finite Element Model
Stiffness
Least Squares

Keywords

  • Damage detection
  • Nonlinear system identification
  • Structural heath assessment
  • Unknown input
  • Unscented Kalman filter

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Al-Hussein, A., & Haldar, A. (2014). A new extension of unscented Kalman filter for structural health assessment with unknown input. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 9061). [90612Y] SPIE. https://doi.org/10.1117/12.2045184

A new extension of unscented Kalman filter for structural health assessment with unknown input. / Al-Hussein, Abdullah; Haldar, Achintya.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9061 SPIE, 2014. 90612Y.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Al-Hussein, A & Haldar, A 2014, A new extension of unscented Kalman filter for structural health assessment with unknown input. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 9061, 90612Y, SPIE, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014, San Diego, CA, United States, 3/10/14. https://doi.org/10.1117/12.2045184
Al-Hussein A, Haldar A. A new extension of unscented Kalman filter for structural health assessment with unknown input. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9061. SPIE. 2014. 90612Y https://doi.org/10.1117/12.2045184
Al-Hussein, Abdullah ; Haldar, Achintya. / A new extension of unscented Kalman filter for structural health assessment with unknown input. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 9061 SPIE, 2014.
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