ORCID Profile
0000-0002-0436-5176
Current Organisation
University of Technology Sydney
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Publisher: Springer Science and Business Media LLC
Date: 16-06-2020
Publisher: Elsevier BV
Date: 06-2023
Publisher: Elsevier BV
Date: 08-2021
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 07-2022
Publisher: SAGE Publications
Date: 21-05-2019
Abstract: This paper demonstrates the feasibility of simultaneously identifying both the location and severity of structural damage in a beam by using two independent moving load experiments. First, a simple but sufficiently accurate single degree of freedom model is presented to simulate the structure efficiently over a wide range of relevant inputs. We then introduce a damage sensitive feature (DSF) based on the integral of the velocity time history of the beam at its midspan when the load moves over the beam. A critical velocity, a function only of the beam’s first natural frequency and length, is obtained for the proposed DSF, upon which the damage can be located more accurately. The only required data for the damage detection is the midspan velocity-time history of the cracked beam subjected to a moving load, and the midspan static deflection of the intact beam subjected to a load of the same magnitude. In the last section of this paper, the capability of the proposed DSF is examined in the presence of noise. The results demonstrate the capability of the proposed method to find both the damage location and severity successfully, and methods for further reducing the effects of noise are suggested.
Publisher: SPIE
Date: 22-03-2021
DOI: 10.1117/12.2582649
Publisher: Hindawi Limited
Date: 23-10-2022
DOI: 10.1002/STC.2867
Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier BV
Date: 11-2023
Publisher: MDPI AG
Date: 27-12-2021
DOI: 10.3390/S22010153
Abstract: This study presents a comprehensive review of the history of research and development of different damage-detection methods in the realm of composite structures. Different fields of engineering, such as mechanical, architectural, civil, and aerospace engineering, benefit excellent mechanical properties of composite materials. Due to their heterogeneous nature, composite materials can suffer from several complex nonlinear damage modes, including impact damage, delamination, matrix crack, fiber breakage, and voids. Therefore, early damage detection of composite structures can help avoid catastrophic events and tragic consequences, such as airplane crashes, further demanding the development of robust structural health monitoring (SHM) algorithms. This study first reviews different non-destructive damage testing techniques, then investigates vibration-based damage-detection methods along with their respective pros and cons, and concludes with a thorough discussion of a nonlinear hybrid method termed the Vibro-Acoustic Modulation technique. Advanced signal processing, machine learning, and deep learning have been widely employed for solving damage-detection problems of composite structures. Therefore, all of these methods have been fully studied. Considering the wide use of a new generation of smart composites in different applications, a section is dedicated to these materials. At the end of this paper, some final remarks and suggestions for future work are presented.
Publisher: ACM
Date: 07-07-2021
Publisher: Elsevier BV
Date: 02-2022
Publisher: Elsevier BV
Date: 04-2022
Publisher: Elsevier BV
Date: 12-2019
Publisher: Springer Science and Business Media LLC
Date: 02-2018
Publisher: Elsevier BV
Date: 08-2022
Publisher: Elsevier BV
Date: 10-2022
Publisher: Elsevier BV
Date: 11-2021
Publisher: Springer International Publishing
Date: 24-02-2012
Publisher: Elsevier BV
Date: 04-2021
Publisher: SPIE
Date: 19-04-2022
DOI: 10.1117/12.2630797
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 11-2020
Publisher: MDPI AG
Date: 30-03-2023
DOI: 10.3390/BUILDINGS13040918
Abstract: The development of Structural Health Monitoring (SHM) and Non-Destructive Testing (NDT) techniques has rapidly evolved and matured over the past few decades. Advances in sensor technology have facilitated deploying SHM systems for large-scale structures and local NDT of structural members. Although both methods have been successfully applied to identify structural damage in various systems, Environmental and Operational Condition (EOC) variations can influence sensor measurements and mask damage signatures in the structural response. EOCs include environmental conditions, such as temperature, humidity, and wind, as well as operational conditions, such as mass loading, vibration, and boundary conditions. The effect of EOCs can significantly undermine the reliability and robustness of damage assessment technologies and limit their performance. Thus, successful SHM and NDT systems can compensate for changing EOCs. This paper provides a state-of-the-art review of the effects of EOCs on SHM and NDT systems. It presents recent developments in advanced sensing technology, signal processing, and analysis techniques that aim to eliminate the masking effect of EOC variations and increase the damage sensitivity and performance of SHM and NDT systems. The paper concludes with current research challenges, trends, and recommendations for future research directions.
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 04-2021
Publisher: Elsevier BV
Date: 11-2021
Publisher: Elsevier
Date: 2022
No related grants have been discovered for Mohsen Mousavi.