Experimental tests of substructure approaches for health monitoring system

Lijun Xie, Longxi Luo, Akira Mita, Maria Q. Feng

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

Abstract

Two substructure approaches combined with different statistical techniques are presented in the paper to reduce the challenges in the health monitoring system, such as the computation complexity, the number of unknown parameters and the number of sensors. In the approaches, a complete structure is divided into smaller substructures which are modelled as a series of single-degree-of-freedom (SDOF) systems by manipulating the equations of motion of the substructures. Newmark's method is utilized to construct the discrete systems only containing accelerations from the continuous systems. The structural parameters are then separately identified in each system using statistical techniques. A new substructure approach incorporated with the constrained least square algorithm is proposed by the authors. This new approach along with the previous substructure approach based on the ARMAX models are both evaluated and compared in two laboratory experiments including system identification of a three-story structure and damage detection of a two-story structure. All the possible ways to segment the shear structure into substructures are also investigated in the study, where the substructures with lower model errors are selected. The proposed substructure approaches are able to estimate structural parameters every two seconds, and the structural performance is evaluated through the rates of changes of structural parameters. A real-time structural health monitoring (SHM) system can be realized based on the proposed substructure approaches with processing several accelerations each time.

Original languageEnglish
Title of host publicationStructural Health Monitoring 2017
Subtitle of host publicationReal-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
EditorsFu-Kuo Chang, Fotis Kopsaftopoulos
PublisherDEStech Publications
Pages1099-1106
Number of pages8
ISBN (Electronic)9781605953304
DOIs
Publication statusPublished - 2017 Jan 1
Event11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017 - Stanford, United States
Duration: 2017 Sep 122017 Sep 14

Publication series

NameStructural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017
Volume1

Other

Other11th International Workshop on Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance, IWSHM 2017
CountryUnited States
CityStanford
Period17/9/1217/9/14

ASJC Scopus subject areas

  • Health Information Management
  • Computer Science Applications

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  • Cite this

    Xie, L., Luo, L., Mita, A., & Feng, M. Q. (2017). Experimental tests of substructure approaches for health monitoring system. In F-K. Chang, & F. Kopsaftopoulos (Eds.), Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017 (pp. 1099-1106). (Structural Health Monitoring 2017: Real-Time Material State Awareness and Data-Driven Safety Assurance - Proceedings of the 11th International Workshop on Structural Health Monitoring, IWSHM 2017; Vol. 1). DEStech Publications. https://doi.org/10.12783/shm2017/13974