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

Abstract

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.

Vehicle-Assisted Techniques for Health Monitoring of Bridges

“…The applied traffic load to a highway bridge structure depends on several parameters such as weight of vehicles, axle load, configuration of axles, position of vehicles on the bridge, number of vehicles, direction, and vehicle's speed [8]. Though it is very desirable to evaluate the in-service performance of a bridge structure, it is difficult to measure the incorporated time-varying vehicular parameters [9].…”

A novel identification procedure from ambient vibration data

“…These kinds of drawbacks led researchers to start looking at time domain systemidentification OMA techniques as a promising alternative. Different time domain methods have been developed such as the Least-square curve fitting technique, the Auto-Regressive model with a Moving Average of white noise (ARMA) [12], the Stochastic Subspace Identification techniques (SSI) [13], the Natural Excitation Technique (NExt) [14,15] and so on [16]. Further, correlation functions can also be employed for the modal identification for OMA just like IRFs for EMA [14].…”

Dynamic Characterization of Structures from Limited Measurements Using a Subspace System Identification Method

“…It is suitable for the system identification of structures with light damping and is effective with multiple input and output data. This method was extended to ERA-observer/Kalman filter identification (ERA-OKID), which extracts Markov parameters using the Observer Kalman filter considering the uncertainty of the structural response, and the ERA-natural excitation technique (ERA-NExT), which can solve the noise problem of input signals [3,5,6,10]. ERA has been widely utilized to monitor aerospace and civil structures when sufficient input and output data are available.…”

“…For bridges in particular, methods that utilize ambient vibration data without dynamic excitation are effective because the dynamic excitation of higher modes is difficult and vehicles must be controlled to acquire data [1]. SSI is generally known to have high reliability for estimating the modal characteristics of structures using only the output response [10]. A representative SSI technique is the numerical algorithm for subspace state-space system identification (N4SID) [11].…”

“…This technique has been developed over the past decade, mainly for evaluating the health of aircraft elements. Still, its system-level application to large civil structures, such as bridges and buildings, remains an open issue [10].…”