Suitability of Nondestructive Testing Methods for Structural Health Monitoring of Civil Infrastructures

2008 ◽  
Author(s):  
Sreenivas Alampalli ◽  
Mohammed Ettouney
Keyword(s):  
Structural Health Monitoring ◽  
Nondestructive Testing ◽  
Health Monitoring ◽  
Testing Methods ◽  
Structural Health ◽  
Civil Infrastructures ◽  
Nondestructive Testing Methods

scholarly journals Toward the development of standardized procedures for structural health monitoring

2019 ◽  
Author(s):  
Maria Pina Limongelli
Keyword(s):  
Structural Health Monitoring ◽  
Nondestructive Testing ◽  
Health Monitoring ◽  
Structural Response ◽  
Health Conditions ◽  
Practical Implementation ◽  
Civil Structures ◽  
Structural Health ◽  
The World ◽  
Limited Diffusion

<p>Monitoring of structural health conditions is performed using different methods that range from periodic surveys including nondestructive testing at selected locations, to permanent monitoring using network of sensors continuously recording the structural response. These procedures aim at providing detection of possible faults or deterioration processes in order to optimally manage civil structures and infrastructures over the lifecycle. To date several guidelines have been published by different countries all over the world but protocols to apply SHM are generally not defined nor enforced. This is likely to be of the reasons that stand behind the limited diffusion and implementation of SHM for routine operations of condition assessment. In this paper building the principal aspects of the SHM process are presented and the need of the development of protocols for the different phases of the SHM process, from design to practical implementation and use are outlined.</p>

scholarly journals A Time-Domain Structural Damage Detection Method Based on Improved Multiparticle Swarm Coevolution Optimization Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Shao-Fei Jiang ◽  
Si-Yao Wu ◽  
Li-Qiang Dong
Keyword(s):  
Structural Health Monitoring ◽  
Damage Detection ◽  
Health Monitoring ◽  
Structural Damage ◽  
Damage Threshold ◽  
Optimization Techniques ◽  
Local Optimum ◽  
Structural Health ◽  
Civil Infrastructures ◽  
Standard Particle Swarm Optimization

Optimization techniques have been applied to structural health monitoring and damage detection of civil infrastructures for two decades. The standard particle swarm optimization (PSO) is easy to fall into the local optimum and such deficiency also exists in the multiparticle swarm coevolution optimization (MPSCO). This paper presents an improved MPSCO algorithm (IMPSCO) firstly and then integrates it with Newmark’s algorithm to localize and quantify the structural damage by using the damage threshold proposed. To validate the proposed method, a numerical simulation and an experimental study of a seven-story steel frame were employed finally, and a comparison was made between the proposed method and the genetic algorithm (GA). The results show threefold: (1) the proposed method not only is capable of localization and quantification of damage, but also has good noise-tolerance; (2) the damage location can be accurately detected using the damage threshold proposed in this paper; and (3) compared with the GA, the IMPSCO algorithm is more efficient and accurate for damage detection problems in general. This implies that the proposed method is applicable and effective in the community of damage detection and structural health monitoring.

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’.

Augmented Reality-Based Embedded Sensor Location Recognition and Data Visualization Technique for Concrete Structural Health Monitoring

2013 ◽  
Vol 281 ◽  
pp. 593-596
Author(s):  
Woong Ki Park ◽  
Hyun Uk Kim ◽  
Chang Gil Lee ◽  
Seung Hee Park
Keyword(s):  
Structural Health Monitoring ◽  
Data Visualization ◽  
Health Monitoring ◽  
Construction Projects ◽  
Data Access ◽  
Sensor Location ◽  
Location Recognition ◽  
Structural Health ◽  
Civil Infrastructures ◽  
Monitoring Technique

In recent years, numerous mega-sized and complex civil infrastructures are being constructed all over the world. Therefore, more precise construction and maintenance technologies are required for these complicated construction projects. So a variety of sensors-based structural health monitoring (SHM) techniques have been studied, but these techniques could not manage the sensors efficiently access the database obtained from the sensors. Recently, Quick response (QR) code and AR-based data access technologies have been developed. In this paper, an AR-based concrete curing strength monitoring technique for sensor management and efficient access of the measured data is introduced. It is confirmed that the AR-based concrete curing strength monitoring technique is useful for construction process. In addition, it is concluded that both efficient sensor location recognition and data visualization at anytime, anywhere, and any smart PC devices are promising.

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