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 high importance. Despite the availability… More >

Clyde K Coelho, Cristobal Hiche, Aditi Chattopadhyay

Structural Durability & Health Monitoring, Vol.7, No.1&2, pp. 65-82, 2011, DOI:10.3970/sdhm.2011.007.065

Abstract Low velocity impacts on composite plates often create subsurface damage that is difficult to diagnose. Fiber Bragg grating (FBG) sensors can be used to detect subsurface damage in composite laminates due to low velocity impact. This paper focuses on the prediction of impact loading in composite structures as a function of time using a support vector regression approach. A time delay embedding feature extraction scheme is used since it can characterize the dynamics of the impact using the sensor signals. The novelty of this approach is that it can be applied on complex geometries and does not require a dense… More >

Dennis Bäcker¹, Andreas Ricoeur², Meinhard Kuna¹

Structural Durability & Health Monitoring, Vol.7, No.1&2, pp. 1-22, 2011, DOI:10.3970/sdhm.2011.007.001

Abstract A new sensor concept for monitoring fatigue crack growth in technical structures is presented. It allows the in-situ determination of the position of the crack tip as well as the fracture mechanical quantities. The required data are obtained from a piezoelectric polymer film, which is attached to the surface of the monitored structure. The stress intensity factors and the crack tip position are calculated from electrical potentials obtained from a sensor array by solving the non-linear inverse problem. 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 of adhesively bonded joints. A… 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 detections. As one might expect,… 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 and in certain circumstances code… More >

Dongyue Gao¹, Yishou Wang¹, Zhanjun Wu¹, Rahim Gorgin¹

Structural Durability & Health Monitoring, Vol.9, No.3, pp. 233-252, 2013, DOI:10.32604/sdhm.2013.009.233

Abstract In this study, a Lamb wave-based damage extension diagnosis method to monitor the damage on typical structures of composite aircraft is proposed. First, an overview of the damage extension diagnosis method is given. In the method, probability-based damage diagnostic imaging was combined with empirical threshold value to distinguish damage location and estimate damage size in damage extension process. To validate the effectiveness of method, extension diagnosis of simulate delamination damage in typical structure on aircraft were processed. To illustrate the capability of the damage extension diagnostic method, a delamination growth monitoring experiment was performed in a typical reinforce component (Tjoint… More >

G. Savaidis¹, M. Malikoutsakis¹, A. Jagenbrein², A. Savaidis³, M. Soare⁴, M.V. Predoi⁴, A. Soare⁴, I.C. Diba⁴

Structural Durability & Health Monitoring, Vol.9, No.2, pp. 129-154, 2013, DOI:10.32604/sdhm.2013.009.129

Abstract Development of corrosion or/and fatigue crack propagation are the most common causes of structural degradation in road and railway tank vessels. An acoustic emission based monitoring procedure in conjunction with follow-up nondestructive testing is here proposed as a promising alternative to the conventional inspection processes enabling continuous health monitoring of the tank structures. Thereby, finite element analysis taking the respective ADR and RID tank design loads into account is proposed as a capable tool to be applied in early stages of development to reveal the hot spot areas, where acoustic emission sensors have to be positioned. The developed health monitoring… More >

A. Rama Mohan Rao¹, S. Krishna Kumar¹, K. Lakshmi¹

Structural Durability & Health Monitoring, Vol.8, No.3, pp. 271-294, 2012, DOI:10.32604/sdhm.2012.008.271

Abstract Current advancements in structural health monitoring, sensor and sensor network technologies have encouraged using large number of sensor networks in monitoring spatially large civil structures like bridges. Large amount of spatial information obtained from these sensor networks will enhance the reliability in truly assessing the state of the health of the structure. However, if sensors go faulty during operation, the feature extraction techniques embedded into SHM scheme may lead to an erroneous conclusion and often end up with false alarms. Hence it is highly desirable to robustly detect the faulty sensors, isolate and correct the data, if the data at… More >