Structural Complexity in Structural Health Monitoring: Design of Laboratory Model and Test Plan

Abstract

Many researchers in the field of civil structural health monitoring (SHM) have developed and tested their methods on simple to moderately complex laboratory structures such as beams, plates, frames, and trusses. Fieldwork has also been conducted by many researchers and practitioners on more complex operating bridges. Most laboratory structures do not adequately replicate the complexity of truss bridges. Informed by a brief review of the literature, this paper documents the design and proposed test plan of a structurally complex laboratory bridge model that has been specifically designed for the purpose of SHM research. Preliminary results have been presented in the companion paper. IntroductionThe structural complexity of operational bridges poses a significant challenge for structural health monitoring (SHM) researchers. Reference [1] highlights that a 'primary source of epistemic uncertainty [in structural identification] is related to the relatively high level of structural complexity typical of constructed systems,' (p. 406). Ciloglu [2] found that structural complexity contributes significantly to the uncertainty of structural identification by operational modal analysis (OMA). Aktan et al. [3] argue that the basic assumptions that enable system identification of structures do not hold true for more complex constructed systems, particularly in a climate with daily temperature fluctuations of more than 10°C where temperature and humidity can have a significant effect on the vibration characteristics of an operational structure.

Structural Complexity in Structural Health Monitoring: Preliminary Experimental Modal Testing and Analysis

“…This paper has presented the preliminary modal testing and analysis of the bridge model which was described in the companion paper [1]. The aim of the experiment was presented.…”

“…The superstructure was modeled in Microstran as a space frame using the material specifications detailed by Cowled et al [1]; however, the substructure was not modeled for this preliminary numerical model. The boundary conditions at the base of the tower frames were treated as simple pins, whereas the boundary conditions at the anchor tie down points were treated as rollers.…”

“…18.1), which was designed and constructed in response to an identified need to conduct structural health monitoring research on more complex structures, as argued in the companion paper [1].…”

A pattern recognition system based on acoustic signals for fault detection on composite materials

“…Although many methods have been developed for structural monitoring and damage detection, there are still many difficulties in their practical implementation (Alvandi and Cremona, 2006;Farrar and Worden, 2007). These difficulties are due to the complexity of the mechanics of the structural damage and due to the uncertainty of many factors influencing the dynamic behavior of a structure (Cowled et al, 2015). A potential solution to this problem is the implementation of a pattern recognition methodology based on machine learning algorithms.…”

تعیین مشخصات سازه با استفاده از پارامترهای مودال سازه و بکارگیری الگوریتم‌های بهینه‌سازی: ژنتیک، اجتماع ذرات و آموزش و یادگیری

“…The Teaching-learning-based Optimization exhibited the highest convergence rate and the lowest error compared to the Genetic Algorithm and Particle Swarm Optimization. For example, in the two-dimensional truss, the values of the objective function in the last iteration of the Genetic Algorithm, Particle Swarm Optimization, and Teaching-learning-based Optimization were 0.012 , 4 6 7 Modified total modal assurance criterion (MTMAC) 8 Grey Wolf Optimization (GWO) 9 Gradient-based Optimization 10 Slime mold algorithm 11 Marine predators algorithm 12 Ant lion optimizer 13 Whale optimization algorithm 14 Grasshopper optimization algorithm 15 Modal assurance criterion 16 Natural frequency vector assurance criterion 17 ( 2 )…”