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Editorial Structural Health Monitoring and Assessment: Sensors and Analysis Mosbeh R. Kaloop , 1,2,3 Jong Wan Hu , 1,2 Emad Elbeltagi , 4 and Ahmed El Refai 5 1 Department of Civil and Environmental Engineering, Incheon National University, Incheon 22012, Republic of Korea 2 Incheon Disaster Prevention Research Center, Incheon National University, Incheon 22012, Republic of Korea 3 Department of Public Works and Civil Engineering, Mansoura University, Mansoura 35516, Egypt 4 Department of Structural Engineering, Mansoura University, Mansoura 35516, Egypt 5 Department of Civil and Water Engineering, Laval University, Québec, QC, Canada G1V 0A6 Correspondence should be addressed to Mosbeh R. Kaloop; [email protected] Received 13 March 2018; Accepted 13 March 2018; Published 30 May 2018 Copyright © 2018 Mosbeh R. Kaloop et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Structural health monitoring (SHM) aims to assess the behavior of structures and evaluate the performance of mate- rials during the life cycle of the structures. Such assessment should include the dierent parts of the structure and full assembly of the structure as a whole under dierent cases of loadings. SHM involves the integration of sensors, smart materials, data transmission, computational power, and pro- cessing inside the structure. Therefore, sensor properties and characteristics are essential parameters to detect the accurate behavior of structures. In addition, time and frequency domain analyses for structuresmembers or performance of materials should be evaluated to assess the full behavior of structures. Nowadays, sensors are developed based on the require- ments of the SHM system. In this issue, the structure behav- iors and environment conditions are measured and assessed to study the environment impact on structures. In addition, strain and temperature are measured for a bridge and the performance of the bridge under harsh environmental impact is studied. Moreover, the terrestrial laser scanning (TLS) is used to assess the deection of structures in three dimensions. Ultrasonic waves are used to assess materialsbehavior, and ber Bragg sensors are utilized to determine the damage indicator of a mine station. Real structures, materials, and experiments are evaluated and assessed in this issue to analyze and study the behavior of structures and performance of sensors, respectively. Time series and statistical analyses for strain measurements are used to assess the reliability of prestressed concrete box- girder bridge. The time and frequency domains are utilized to assess the bridge condition under real load eects. An innovation statistical window selection method is applied to extract the accurate deformation of structures using TLS measurements. Damage detection is evaluated and assessed based on experimental and real measurements using devel- opment statistical analyses in time domain. Also, a numerical method and experiments are used to assess the performance of noncontact ultrasonic sensors. In addition, the nonlinear evaluation of the damage behavior of a material is assessed and studied. Acknowledgments We wish to thank the reviewers of this special issue for their help in reviewing the submitted papers. Also, we would like to acknowledge the editorial board members for approving the publication of this special issue. Finally, the authors are grateful for both the eorts in the preparation of the manu- scripts and the choice of this journals special issue to publish their scientic and technical contributions. The rst and second editors are supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B2010120). They are also Hindawi Journal of Sensors Volume 2018, Article ID 9834958, 2 pages https://doi.org/10.1155/2018/9834958
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EditorialStructural Health Monitoring and Assessment: Sensorsand Analysis

Mosbeh R. Kaloop ,1,2,3 Jong Wan Hu ,1,2 Emad Elbeltagi ,4 and Ahmed El Refai5

1Department of Civil and Environmental Engineering, Incheon National University, Incheon 22012, Republic of Korea2Incheon Disaster Prevention Research Center, Incheon National University, Incheon 22012, Republic of Korea3Department of Public Works and Civil Engineering, Mansoura University, Mansoura 35516, Egypt4Department of Structural Engineering, Mansoura University, Mansoura 35516, Egypt5Department of Civil and Water Engineering, Laval University, Québec, QC, Canada G1V 0A6

Correspondence should be addressed to Mosbeh R. Kaloop; [email protected]

Received 13 March 2018; Accepted 13 March 2018; Published 30 May 2018

Copyright © 2018 Mosbeh R. Kaloop et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in anymedium, provided the original work is properly cited.

Structural health monitoring (SHM) aims to assess thebehavior of structures and evaluate the performance of mate-rials during the life cycle of the structures. Such assessmentshould include the different parts of the structure and fullassembly of the structure as a whole under different cases ofloadings. SHM involves the integration of sensors, smartmaterials, data transmission, computational power, and pro-cessing inside the structure. Therefore, sensor properties andcharacteristics are essential parameters to detect the accuratebehavior of structures. In addition, time and frequencydomain analyses for structures’ members or performanceof materials should be evaluated to assess the full behaviorof structures.

Nowadays, sensors are developed based on the require-ments of the SHM system. In this issue, the structure behav-iors and environment conditions are measured and assessedto study the environment impact on structures. In addition,strain and temperature are measured for a bridge and theperformance of the bridge under harsh environmentalimpact is studied. Moreover, the terrestrial laser scanning(TLS) is used to assess the deflection of structures in threedimensions. Ultrasonic waves are used to assess materials’behavior, and fiber Bragg sensors are utilized to determinethe damage indicator of a mine station.

Real structures, materials, and experiments are evaluatedand assessed in this issue to analyze and study the behavior ofstructures and performance of sensors, respectively. Time

series and statistical analyses for strain measurements areused to assess the reliability of prestressed concrete box-girder bridge. The time and frequency domains are utilizedto assess the bridge condition under real load effects. Aninnovation statistical window selection method is applied toextract the accurate deformation of structures using TLSmeasurements. Damage detection is evaluated and assessedbased on experimental and real measurements using devel-opment statistical analyses in time domain. Also, a numericalmethod and experiments are used to assess the performanceof noncontact ultrasonic sensors. In addition, the nonlinearevaluation of the damage behavior of a material is assessedand studied.

Acknowledgments

We wish to thank the reviewers of this special issue for theirhelp in reviewing the submitted papers. Also, we would liketo acknowledge the editorial board members for approvingthe publication of this special issue. Finally, the authors aregrateful for both the efforts in the preparation of the manu-scripts and the choice of this journal’s special issue to publishtheir scientific and technical contributions. The first andsecond editors are supported by Basic Science ResearchProgram through the National Research Foundation ofKorea (NRF) funded by the Ministry of Science, ICT &Future Planning (2017R1A2B2010120). They are also

HindawiJournal of SensorsVolume 2018, Article ID 9834958, 2 pageshttps://doi.org/10.1155/2018/9834958

supported by Post-Doctor Research Program in 2018through the Incheon National University (INU), Incheon,South Korea.

Mosbeh R. KaloopJong Wan HuEmad ElbeltagiAhmed El Refai

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