scholarly journals Health Monitoring of Civil Infrastructures by Subspace System Identification Method: An Overview

2020 ◽  
Vol 10 (8) ◽  
pp. 2786 ◽  
Author(s):  
Hoofar Shokravi ◽  
Hooman Shokravi ◽  
Norhisham Bakhary ◽  
Seyed Saeid Rahimian Koloor ◽  
Michal Petrů
Keyword(s):  
System Identification ◽  
Health Monitoring ◽  
Civil Engineering ◽  
Damage Identification ◽  
Engineering Structures ◽  
Practical Applications ◽  
Damage Scenarios ◽  
Advantages And Disadvantages ◽  
Civil Engineering Structures ◽  
Subspace System Identification

Structural health monitoring (SHM) is the main contributor of the future’s smart city to deal with the need for safety, lower maintenance costs, and reliable condition assessment of structures. Among the algorithms used for SHM to identify the system parameters of structures, subspace system identification (SSI) is a reliable method in the time-domain that takes advantages of using extended observability matrices. Considerable numbers of studies have specifically concentrated on practical applications of SSI in recent years. To the best of author’s knowledge, no study has been undertaken to review and investigate the application of SSI in the monitoring of civil engineering structures. This paper aims to review studies that have used the SSI algorithm for the damage identification and modal analysis of structures. The fundamental focus is on data-driven and covariance-driven SSI algorithms. In this review, we consider the subspace algorithm to resolve the problem of a real-world application for SHM. With regard to performance, a comparison between SSI and other methods is provided in order to investigate its advantages and disadvantages. The applied methods of SHM in civil engineering structures are categorized into three classes, from simple one-dimensional (1D) to very complex structures, and the detectability of the SSI for different damage scenarios are reported. Finally, the available software incorporating SSI as their system identification technique are investigated.

scholarly journals Parameter Identification for Structural Health Monitoring with Extended Kalman Filter Considering Integration and Noise Effect

2018 ◽  
Vol 8 (12) ◽  
pp. 2480 ◽  
Author(s):  
Liyu Xie ◽  
Zhenwei Zhou ◽  
Lei Zhao ◽  
Chunfeng Wan ◽  
Hesheng Tang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Structural Health Monitoring ◽  
Parameter Identification ◽  
Extended Kalman Filter ◽  
Health Monitoring ◽  
Civil Engineering ◽  
Damage Identification ◽  
Engineering Structures ◽  
Structural Health ◽  
Civil Engineering Structures

Since physical parameters are much more sensitive than modal parameters, structural parameter identification with an extended Kalman filter (EKF) has received extensive attention in structural health monitoring for civil engineering structures. In this paper, EKF-based parameter identification technique is studied with numerical and experimental approaches. A four-degree-of-freedom (4-DOF) system is simulated and analyzed as an example. Different integration methods are examined and their influence to the final identification results of the structural stiffness and damping is also studied. Furthermore, the effect of different kinds of noise is studied as well. Identification results show that the convergence speed and estimation accuracy under Gaussian noises are better than those under non-Gaussian noises. Finally, experiments with a five-story steel frame are conducted to verify the damage identification capacity of the EKF. The results show that stiffness with different damage degrees can be identified effectively, which indicates that the EKF is capable of being applied for damage identification and health monitoring for civil engineering structures.

scholarly journals Use of Time- and Frequency-Domain Approaches for Damage Detection in Civil Engineering Structures

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
V. H. Nguyen ◽  
J. Mahowald ◽  
S. Maas ◽  
J.-C. Golinval
Keyword(s):  
Damage Detection ◽  
Frequency Domain ◽  
Prestressed Concrete ◽  
Civil Engineering ◽  
Damage Identification ◽  
Real Life ◽  
Hankel Matrix ◽  
Principal Component ◽  
Engineering Structures ◽  
Civil Engineering Structures

The aim of this paper is to apply both time- and frequency-domain-based approaches on real-life civil engineering structures and to assess their capability for damage detection. The methodology is based on Principal Component Analysis of the Hankel matrix built from output-only measurements and of Frequency Response Functions. Damage detection is performed using the concept of subspace angles between a current (possibly damaged state) and a reference (undamaged) state. The first structure is the Champangshiehl Bridge located in Luxembourg. Several damage levels were intentionally created by cutting a growing number of prestressed tendons and vibration data were acquired by the University of Luxembourg for each damaged state. The second example consists in reinforced and prestressed concrete panels. Successive damages were introduced in the panels by loading heavy weights and by cutting steel wires. The illustrations show different consequences in damage identification by the considered techniques.

Review on Damage Identification and Diagnosis Research of Civil Engineering Structure

2014 ◽  
Vol 1006-1007 ◽  
pp. 34-37 ◽  
Author(s):  
Hong Ni ◽  
Ming Hui Li ◽  
Xi Zuo
Keyword(s):  
Structural Damage ◽  
Civil Engineering ◽  
Damage Identification ◽  
Engineering Structures ◽  
Engineering Structure ◽  
Civil Engineering Structure ◽  
Structure Damage ◽  
Development Direction ◽  
Structural Damage Identification ◽  
Civil Engineering Structures

This paper first describes the importance of structural damage identification and diagnosis in civil engineering, and introduces domestic and foreign status of damage identification and diagnosis methods, and on the basis of this, it also introduces all kinds of methods for damage identification and diagnosis of civil engineering structures, and finally puts forward the development direction of civil engineering structure damage identification and diagnosis.

scholarly journals Smart Sensing Technologies for Structural Health Monitoring of Civil Engineering Structures

2010 ◽  
Vol 2010 ◽  
pp. 1-13 ◽  
Author(s):  
M. Sun ◽  
W. J. Staszewski ◽  
R. N. Swamy
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Smart Materials ◽  
Civil Engineering ◽  
Piezoelectric Sensors ◽  
Sensors And Actuators ◽  
Engineering Structures ◽  
Structural Health ◽  
Civil Engineering Structures ◽  
Smart Sensing

Structural Health Monitoring (SHM) aims to develop automated systems for the continuous monitoring, inspection, and damage detection of structures with minimum labour involvement. The first step to set up a SHM system is to incorporate a level of structural sensing capability that is reliable and possesses long term stability. Smart sensing technologies including the applications of fibre optic sensors, piezoelectric sensors, magnetostrictive sensors and self-diagnosing fibre reinforced composites, possess very important capabilities of monitoring various physical or chemical parameters related to the health and therefore, durable service life of structures. In particular, piezoelectric sensors and magnetorestrictive sensors can serve as both sensors and actuators, which make SHM to be an active monitoring system. Thus, smart sensing technologies are now currently available, and can be utilized to the SHM of civil engineering structures. In this paper, the application of smart materials/sensors for the SHM of civil engineering structures is critically reviewed. The major focus is on the evaluations of laboratory and field studies of smart materials/sensors in civil engineering structures.

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