Rui Lu¹, Zhanjun Wu¹, Qi Zhou¹, Hao Xu^1,*

Structural Durability & Health Monitoring, Vol.13, No.3, pp. 267-287, 2019, DOI:10.32604/sdhm.2019.06323

Abstract Structural health monitoring (SHM) is a research focus involving a large category of techniques performing in-situ identification of structural damage, stress, external loads, vibration signatures, etc. Among various SHM techniques, those able to monitoring structural deformed shapes are considered as an important category. A novel method of deformed shape reconstruction for thin-walled beam structures was recently proposed by Xu et al. [1], which is capable of decoupling complex beam deformations subject to the combination of different loading cases, including tension/compression, bending and warping torsion, and also able to reconstruct the full-field displacement distributions. However, this… More >

A. Joshuva¹, V. Sugumaran²

Structural Durability & Health Monitoring, Vol.13, No.2, pp. 181-203, 2019, DOI:10.32604/sdhm.2019.00287

Abstract Wind turbine blades are generally manufactured using fiber type material because of their cost effectiveness and light weight property however, blade get damaged due to wind gusts, bad weather conditions, unpredictable aerodynamic forces, lightning strikes and gravitational loads which causes crack on the surface of wind turbine blade. It is very much essential to identify the damage on blade before it crashes catastrophically which might possibly destroy the complete wind turbine. In this paper, a fifteen tree classification based machine learning algorithms were modelled for identifying and detecting the crack on wind turbine blades. The More >

Yajie Sun^1,2,*, Yanqing Yuan², Qi Wang², Lihua Wang³, Enlu Li², Li Qiao⁴

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 409-420, 2019, DOI:10.32604/cmc.2019.03642

Abstract The signal processing problem has become increasingly complex and demand high acquisition system, this paper proposes a new method to reconstruct the structure phased array structural health monitoring signal. The method is derived from the compressive sensing theory and the signal is reconstructed by using the basis pursuit algorithm to process the ultrasonic phased array signals. According to the principles of the compressive sensing and signal processing method, non-sparse ultrasonic signals are converted to sparse signals by using sparse transform. The sparse coefficients are obtained by sparse decomposition of the original signal, and then the More >

Mengyue He¹, Zhifang Zhang^1,*, Karthik Ram Ramakrishnan²

Structural Durability & Health Monitoring, Vol.12, No.4, pp. 213-256, 2018, DOI:10.32604/sdhm.2018.05122

Abstract Fibre reinforced polymer (FRP) composite laminates are now commonly used in many structural applications, especially in the aerospace industry, where margins of safety are kept low in order to minimise weight. Timely detection and assessment of damage (in particular delaminations) in composite laminates are therefore critical, as they can cause loss of structural integrity affecting the safe operation of the composite structures. The current trend is towards implementation of structural health monitoring (SHM) systems which can monitor the structures in situ without down time. In this paper, first, the current available SHM techniques for delamination… More >

Kong Fah Tee ^1,*

Structural Durability & Health Monitoring, Vol.12, No.3, pp. 129-147, 2018, DOI:10.3970/sdhm.2018.04316

Abstract Structural health monitoring (SHM) is a vast, interdisciplinary research field whose literature spans several decades with focusing on condition assessment of different types of structures including aerospace, mechanical and civil structures. The need for quantitative global damage detection methods that can be applied to complex structures has led to vibration-based inspection. Statistical time series methods for SHM form an important and rapidly evolving category within the broader vibration-based methods. In the literature on the structural damage detection, many time series-based methods have been proposed. When a considered time series model approximates the vibration response of… More >

Amafabia, Daerefa-a Mitsheal¹, Montalvão, Diogo², David-West, Opukuro¹, Haritos, George¹

Structural Durability & Health Monitoring, Vol.11, No.2, pp. 91-147, 2017, DOI:10.3970/sdhm.2017.011.091

Abstract Structural Health Monitoring (SHM) is the process of collecting, interpreting and analysing data from structures in order to determine its health status and the remaining life span. Composite materials have been extensively use in recent years in several industries with the aim at reducing the total weight of structures while improving their mechanical properties. However, composite materials are prone to develop damage when subjected to low to medium impacts (i.e. 1-10 m/s and 11-30 m/s respectively). Hence, the need to use SHM techniques to detect damage at the incipient initiation in composite materials is of… More >

Vincenzo Gulizzi^1,2, Piervincenzo Rizzo^2,3, Alberto Milazzo⁴

Structural Durability & Health Monitoring, Vol.10, No.1, pp. 19-54, 2014, DOI:10.3970/sdhm.2014.010.019

Abstract The electromechanical impedance (EMI) method is one of the many nondestructive evaluation approaches proposed for the health monitoring of aerospace, civil, and mechanical structures. The method consists of attaching or embedding one or more wafer-type piezoelectric transducers (PZTs) to the system of interest, the host structure, and measuring certain electrical characteristics of the transducers. As these characteristics are also related to the impedance of the host structure, they can be used to infer the mechanical properties of the monitored structure. In the study presented in this paper, we utilize the EMI to monitor the quality… More >

Salman A. Albinali¹, David R. Jacques²

Structural Durability & Health Monitoring, Vol.10, No.1, pp. 1-17, 2014, DOI:10.3970/sdhm.2014.010.001

Abstract An analytic approach to exploring the tradespace associated with Structural Health Monitoring (SHM) systems is presented. Modeling and simulation of the life cycle of a legacy aircraft and the expected operational and maintenance events that could occur is shown. A focus on the SHM system detection of a significant crack length and the possibility of False Alarm (FA), miss detection and mishap events is investigated. The modeling approach allows researchers to explore the tradespace associated with safe and critical crack lengths, sensor thresholds, scheduled maintenance intervals, falsely triggered maintenance actions, and mishaps due to missed… More >

V. Mallardo^1,2, M.H. Aliabadi³

Structural Durability & Health Monitoring, Vol.9, No.4, pp. 287-323, 2013, DOI:10.32604/sdhm.2013.009.287

Abstract The optimum location of the sensors is a critical issue of any successful Structural Health Monitoring System. Sensor optimization problems encompass mainly three areas of interest: system identification, damage identification and impact identification. The current paper is intended as a review of the state of the art at the year 2012 and going back to 1990. The above topics have been dealt with in separate contexts so far but they contain interesting common elements to be exploited. More >

Mehdi Mohammadpour Lima^1,2, Dane Miller¹, Jeung-Hwan Doh¹

Structural Durability & Health Monitoring, Vol.9, No.4, pp. 269-285, 2013, DOI:10.32604/sdhm.2013.009.269

Abstract Iran is located in a seismic prone region with several earthquakes occurring annually causing extensive damage to structures and infrastructure. Guilan province is located in the northern part of the country, exhibiting a large population, moderate climate and extensive river system. This region experiences high humidity, several active faults and high seismic hazard potential. This highlights the importance of an active and extensive maintenance and rehabilitation program for the bridges in this region. Structural Health Monitoring (SHM) is an engineering tool used to control changing conditions of infrastructure providing useful information for management, decision making… More >