Enhancing Civil Infrastructure Resilience with Structural Health Monitoring

2018 ◽  
Author(s):  
Yunfeng Zhang ◽  
Bilal Ayyub ◽  
Hongwei Huang
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Civil Infrastructure ◽  
Structural Health ◽  
Infrastructure Resilience

scholarly journals Application of Machine Learning with Impedance Based Techniques for Structural Health Monitoring of Civil Infrastructure

2019 ◽  
Vol 8 (6S4) ◽  
pp. 1139-1148
Keyword(s):  
Machine Learning ◽  
Signal Processing ◽  
Structural Health Monitoring ◽  
Damage Detection ◽  
Soft Computing ◽  
Health Monitoring ◽  
Multiple Cracks ◽  
Civil Infrastructure ◽  
Structural Health ◽  
Soft Computing Techniques

Increased attentiveness on the environmental and effects of aging, deterioration and extreme events on civil infrastructure has created the need for more advanced damage detection tools and structural health monitoring (SHM). Today, these tasks are performed by signal processing, visual inspection techniques along with traditional well known impedance based health monitoring EMI technique. New research areas have been explored that improves damage detection at incipient stage and when the damage is substantial. Addressing these issues at early age prevents catastrophe situation for the safety of human lives. To improve the existing damage detection newly developed techniques in conjugation with EMI innovative new sensors, signal processing and soft computing techniques are discussed in details this paper. The advanced techniques (soft computing, signal processing, visual based, embedded IOT) are employed as a global method in prediction, to identify, locate, optimize, the damage area and deterioration. The amount and severity, multiple cracks on civil infrastructure like concrete and RC structures (beams and bridges) using above techniques along with EMI technique and use of PZT transducer. In addition to survey advanced innovative signal processing, machine learning techniques civil infrastructure connected to IOT that can make infrastructure smart and increases its efficiency that is aimed at socioeconomic, environmental and sustainable development.

scholarly journals Recent Progress of Fiber-Optic Sensors for the Structural Health Monitoring of Civil Infrastructure

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4517
Author(s):  
Tiange Wu ◽  
Guowei Liu ◽  
Shenggui Fu ◽  
Fei Xing
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Electromagnetic Interference ◽  
Fiber Optic ◽  
Materials Science ◽  
Fiber Optic Sensors ◽  
Civil Infrastructure ◽  
Basic Principles ◽  
Structural Health ◽  
Sensing Systems

In recent years, with the development of materials science and architectural art, ensuring the safety of modern buildings is the top priority while they are developing toward higher, lighter, and more unique trends. Structural health monitoring (SHM) is currently an extremely effective and vital safeguard measure. Because of the fiber-optic sensor’s (FOS) inherent distinctive advantages (such as small size, lightweight, immunity to electromagnetic interference (EMI) and corrosion, and embedding capability), a significant number of innovative sensing systems have been exploited in the civil engineering for SHM used in projects (including buildings, bridges, tunnels, etc.). The purpose of this review article is devoted to presenting a summary of the basic principles of various fiber-optic sensors, classification and principles of FOS, typical and functional fiber-optic sensors (FOSs), and the practical application status of the FOS technology in SHM of civil infrastructure.

Environmental testing of wireless sensor system for structural health monitoring of civil infrastructure

2006 ◽  
Author(s):  
Michael P. Fuchs ◽  
Kerop D. Janoyan ◽  
Edward S. Sazonov ◽  
Vidya Krishnamurthy ◽  
Ratan Jha ◽  
...  
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Sensor System ◽  
Wireless Sensor ◽  
Civil Infrastructure ◽  
Environmental Testing ◽  
Structural Health

The Modal Identification of Structure Using Distributed ERA and EFDD Methods

2010 ◽  
Vol 163-167 ◽  
pp. 2532-2536
Author(s):  
Ying Lei ◽  
Zhi Lu Lai
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Large Volume ◽  
Modal Identification ◽  
Modal Parameters ◽  
Identification Algorithm ◽  
Civil Infrastructure ◽  
Complicated Structure ◽  
Data Set ◽  
Structural Health

Structural health monitoring (SHM) is an emerging field in civil engineering, offering the potential for continuous and periodic assessment of the safety and integrity of civil infrastructure. In this paper, a distributed computing strategy for modal identification of structure is proposed, which is suitable for the problem of solving large volume of data set in structural health monitoring. Numerical example of distribute computing the modal properties of truss illustrates the distributed out-put only modal identification algorithm based on NExT / ERA techniques and EFDD. This strategy can also be applied to other complicated structure to determine modal parameters.

Structural health monitoring of civil infrastructure

2006 ◽  
Vol 365 (1851) ◽  
pp. 589-622 ◽  
Author(s):  
J.M.W Brownjohn
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Communication Systems ◽  
State Of The Art ◽  
Civil Infrastructure ◽  
Structural Health ◽  
Civil Infrastructures ◽  
Economic Operation ◽  
History Of ◽  
Computer Based

Structural health monitoring (SHM) is a term increasingly used in the last decade to describe a range of systems implemented on full-scale civil infrastructures and whose purposes are to assist and inform operators about continued ‘fitness for purpose’ of structures under gradual or sudden changes to their state, to learn about either or both of the load and response mechanisms. Arguably, various forms of SHM have been employed in civil infrastructure for at least half a century, but it is only in the last decade or two that computer-based systems are being designed for the purpose of assisting owners/operators of ageing infrastructure with timely information for their continued safe and economic operation. This paper describes the motivations for and recent history of SHM applications to various forms of civil infrastructure and provides case studies on specific types of structure. It ends with a discussion of the present state-of-the-art and future developments in terms of instrumentation, data acquisition, communication systems and data mining and presentation procedures for diagnosis of infrastructural ‘health’.

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