scholarly journals Structural Health Monitoring: From Sensing Technology Stepping to Health Diagnosis

2011 ◽  
Vol 14 ◽  
pp. 753-760 ◽  
Author(s):  
LI Hui ◽  
OU Jinping
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Structural Health ◽  
Sensing Technology ◽  
Health Diagnosis

Research on Application Issues of Structural Health Monitoring System Based on Optical Fiber Sensing Technology

2015 ◽  
Vol 744-746 ◽  
pp. 235-243 ◽  
Author(s):  
Fan Yong Meng ◽  
Li Min Jia ◽  
Xiao Huan Shen ◽  
Jun Wei Dong
Keyword(s):  
Structural Health Monitoring ◽  
Optical Fiber ◽  
Monitoring System ◽  
Health Monitoring ◽  
Health Monitoring System ◽  
Structural Health ◽  
Fiber Sensing ◽  
Structural Health Monitoring System ◽  
Sensing Technology ◽  
Optical Fiber Sensing

Introduced the development situation and trend of structural health monitoring, discussed the advantages and insufficiencies of application issues of the structural health monitoring system based on optical fiber sensing technology, combined with engineering case, analyzed the sensors’ survival rate, system reliability, temperature compensation and some other issues, according to the specific problem proposed the corresponding solutions or concrete measure.

Machine learning paradigm for structural health monitoring

2020 ◽  
pp. 147592172097241
Author(s):  
Yuequan Bao ◽  
Hui Li
Keyword(s):  
Machine Learning ◽  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Degrees Of Freedom ◽  
Monitoring Data ◽  
Learning Paradigm ◽  
Structural Health ◽  
Diagnosis And Prognosis ◽  
Cable Force ◽  
Health Diagnosis

Structural health diagnosis and prognosis is the goal of structural health monitoring. Vibration-based structural health monitoring methodology has been extensively investigated. However, the conventional vibration–based methods find it difficult to detect damages of actual structures because of a high incompleteness in the monitoring information (the number of sensors is much fewer with respect to the number of degrees of freedom of a structure), intense uncertainties in the structural conditions and monitoring systems, and coupled effects of damage and environmental actions on modal parameters. It is a truth that the performance and conditions of a structure must be embedded in the monitoring data (vehicles, wind, etc.; acceleration, displacement, cable force, strain, images, videos, etc.). Therefore, there is a need to develop completely novel structural health diagnosis and prognosis methodology based on the various monitoring data. Machine learning provides the advanced mathematical frameworks and algorithms that can help discover and model the performance and conditions of a structure through deep mining of monitoring data. Thus, machine learning takes an opportunity to establish novel machine learning paradigm for structural health diagnosis and prognosis theory termed the machine learning paradigm for structural health monitoring. This article sheds light on principles for machine learning paradigm for structural health monitoring with some examples and reviews the existing challenges and open questions in this field.

scholarly journals Structural Health Monitoring of Civil Infrastructure Using Optical Fiber Sensing Technology: A Comprehensive Review

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
X. W. Ye ◽  
Y. H. Su ◽  
J. P. Han
Keyword(s):  
Structural Health Monitoring ◽  
Optical Fiber ◽  
Health Monitoring ◽  
Optical Fiber Sensors ◽  
Civil Infrastructure ◽  
Fiber Sensors ◽  
Structural Health ◽  
Fiber Sensing ◽  
Sensing Technology ◽  
Optical Fiber Sensing

In the last two decades, a significant number of innovative sensing systems based on optical fiber sensors have been exploited in the engineering community due to their inherent distinctive advantages such as small size, light weight, immunity to electromagnetic interference (EMI) and corrosion, and embedding capability. A lot of optical fiber sensor-based monitoring systems have been developed for continuous measurement and real-time assessment of diversified engineering structures such as bridges, buildings, tunnels, pipelines, wind turbines, railway infrastructure, and geotechnical structures. The purpose of this review article is devoted to presenting a summary of the basic principles of various optical fiber sensors, innovation in sensing and computational methodologies, development of novel optical fiber sensors, and the practical application status of the optical fiber sensing technology in structural health monitoring (SHM) of civil infrastructure.

scholarly journals Towards airborne laser Doppler vibrometry for structural health monitoring of large and curved structures

2021 ◽  
Vol 63 (5) ◽  
pp. 280-282
Author(s):  
M Schewe ◽  
M A A Ismail ◽  
C Rembe
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Laser Doppler Vibrometer ◽  
Laser Doppler ◽  
Laser Doppler Vibrometry ◽  
Structural Health ◽  
Curved Structures ◽  
Sensing Technology ◽  
Reflective Mirror ◽  
Historic Structures

Laser Doppler vibrometry is an important sensing technology for many structural health monitoring (SHM) methods, such as modal analysis. However, when it comes to large civil structures, for example historic structures and bridges, the applicability of laser Doppler vibrometry is significantly constrained by inaccessible remote surfaces. Some of these surfaces are fully inaccessible to a ground-mounted laser Doppler vibrometer (LDV), while others are partially inaccessible, and measurements are only possible for low incident angles. Consequently, LDV measurements are either impossible or have a weak signal strength. In this study, the concept of constructing an airborne LDV for SHM is explored, including the examination of a recently developed mechanism, the partially airborne LDV, comprising a reflective mirror attached to a drone. Preliminary proof of concept laboratory tests have been successfully conducted using two different set-ups and drone models.

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