Structural Health Monitoring and Damage Identification

2020 ◽  
pp. 1-72
Author(s):  
R. Fuentes ◽  
E.J. Cross ◽  
P.A. Gardner ◽  
L.A. Bull ◽  
T.J. Rogers ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Identification ◽  
Structural Health

scholarly journals Structural health monitoring and damage identification for composite panels using smart sensor

2016 ◽  
Vol 27 (17) ◽  
pp. 2313-2323 ◽  
Author(s):  
Nisreen N. Ali Al-Adnani ◽  
F Mustapha ◽  
SM Sapuan ◽  
MR Raizal Saifulnaz
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Identification ◽  
Composite Panels ◽  
Smart Sensor ◽  
Structural Health

scholarly journals Kappa-PSO-FAN based method for damage identification on composite structural health monitoring

2018 ◽  
Vol 95 ◽  
pp. 1-13 ◽  
Author(s):  
Mario A. de Oliveira ◽  
Nelcileno V.S. Araujo ◽  
Daniel J. Inman ◽  
Jozue Vieira Filho
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Identification ◽  
Structural Health

scholarly journals A multi-way data analysis approach for structural health monitoring of a cable-stayed bridge

2018 ◽  
Vol 18 (1) ◽  
pp. 35-48 ◽  
Author(s):  
Mehrisadat Makki Alamdari ◽  
Nguyen Lu Dang Khoa ◽  
Yang Wang ◽  
Bijan Samali ◽  
Xinqun Zhu
Keyword(s):  
Data Analysis ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Large Scale ◽  
Damage Identification ◽  
Tensor Analysis ◽  
Support Vector ◽  
Damage Scenarios ◽  
Structural Health ◽  
Cable Stayed Bridge

A large-scale cable-stayed bridge in the state of New South Wales, Australia, has been extensively instrumented with an array of accelerometer, strain gauge, and environmental sensors. The real-time continuous response of the bridge has been collected since July 2016. This study aims at condition assessment of this bridge by investigating three aspects of structural health monitoring including damage detection, damage localization, and damage severity assessment. A novel data analysis algorithm based on incremental multi-way data analysis is proposed to analyze the dynamic response of the bridge. This method applies incremental tensor analysis for data fusion and feature extraction, and further uses one-class support vector machine on this feature to detect anomalies. A total of 15 different damage scenarios were investigated; damage was physically simulated by locating stationary vehicles with different masses at various locations along the span of the bridge to change the condition of the bridge. The effect of damage on the fundamental frequency of the bridge was investigated and a maximum change of 4.4% between the intact and damage states was observed which corresponds to a small severity damage. Our extensive investigations illustrate that the proposed technique can provide reliable characterization of damage in this cable-stayed bridge in terms of detection, localization and assessment. The contribution of the work is threefold; first, an extensive structural health monitoring system was deployed on a cable-stayed bridge in operation; second, an incremental tensor analysis was proposed to analyze time series responses from multiple sensors for online damage identification; and finally, the robustness of the proposed method was validated using extensive field test data by considering various damage scenarios in the presence of environmental variabilities.

On Structural Health Monitoring of Wind Turbine Blades

2013 ◽  
Vol 569-570 ◽  
pp. 628-635 ◽  
Author(s):  
Jonas Falk Skov ◽  
Martin Dalgaard Ulriksen ◽  
Kristoffer Ahrens Dickow ◽  
Poul Henning Kirkegaard ◽  
Lars Damkilde
Keyword(s):  
Structural Health Monitoring ◽  
Wind Turbine ◽  
Health Monitoring ◽  
Damage Identification ◽  
State Of The Art ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Noise And Vibration ◽  
Structural Health ◽  
Temperature Noise

The aim of the present paper is to provide a state-of-the-art outline of structural health monitoring (SHM) techniques, utilizing temperature, noise and vibration, for wind turbine blades, and subsequently perform a typology on the basis of the typical 4 damage identification levels in SHM. Before presenting the state-of-the-art outline, descriptions of structural damages typically occurring in wind turbine blades are provided along with a brief description of the 4 damage identification levels.

Structural Health Monitoring for Steel Structures

2013 ◽  
Vol 351-352 ◽  
pp. 1088-1091
Author(s):  
Xin Wang ◽  
Wei Bing Hu
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Identification ◽  
Steel Structures ◽  
Fingerprint Analysis ◽  
Structural Health ◽  
Network Methods ◽  
Different Types ◽  
The Impact ◽  
Identification Strategy

The process of implementing a damage identification strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring. Many different types and degrees accidents take place, especially some important collapse accidents, the significance of steel structural health monitoring has been recognized. The introduction begins with a brief research status of steel structural health monitoring in china and the world. The paper analyzes the projects and contents of steel structures monitoring from nine aspects and summarizes the diagnosis methods of steel structural damages which include power fingerprint analysis, the methods of model correction and system identification, neural network methods, genetic algorithm and wavelet analysis, it provides us theoretical guidence. In conclusion, structural health monitoring for steel structures could reduce the impact of such disasters immediately after natural hazards and man-made disasters both economically and socially, thus it is becoming increasingly important.

scholarly journals Optimization-Based Evolutionary Data Mining Techniques for Structural Health Monitoring

2020 ◽  
Vol 9 (1) ◽  
pp. 14-23 ◽  
Author(s):  
Meisam Gordan ◽  
Zubaidah Binti Ismail ◽  
Hashim Abdul Razak ◽  
Khaled Ghaedi ◽  
Haider Hamad Ghayeb
Keyword(s):  
Data Mining ◽  
Exact Solution ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Damage ◽  
Damage Identification ◽  
Optimization Problems ◽  
Engineering Optimization ◽  
Structural Health ◽  
Structural Damage Identification

In recent years, data mining technology has been employed to solve various Structural Health Monitoring (SHM) problems as a comprehensive strategy because of its computational capability. Optimization is one the most important functions in Data mining. In an engineering optimization problem, it is not easy to find an exact solution. In this regard, evolutionary techniques have been applied as a part of procedure of achieving the exact solution. Therefore, various metaheuristic algorithms have been developed to solve a variety of engineering optimization problems in SHM. This study presents the most applicable as well as effective evolutionary techniques used in structural damage identification. To this end, a brief overview of metaheuristic techniques is discussed in this paper. Then the most applicable optimization-based algorithms in structural damage identification are presented, i.e. Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Imperialist Competitive Algorithm (ICA) and Ant Colony Optimization (ACO). Some related examples are also detailed in order to indicate the efficiency of these algorithms.

Structural Health Monitoring and Damage Identification

2021 ◽  
pp. 1-72
Author(s):  
R. Fuentes ◽  
E. J. Cross ◽  
P. A. Gardner ◽  
L. A. Bull ◽  
T. J. Rogers ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Damage Identification ◽  
Structural Health
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