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Märstetten-Dorf, Switzerland

Inaudi D.,Smartec SA
Bridge Maintenance, Safety, Management and Life-Cycle Optimization - Proceedings of the 5th International Conference on Bridge Maintenance, Safety and Management

When designing a Structural Health Monitoring system, one should always focus on the specific requirements of the structure under exam. To achieve an optimal design it is however beneficial to follow a well-defined and proven procedure. The first step in the design process consists in identifying the risks and opportunities associated with the bridge under examination. Examples of risks include the probable degradation mechanism due to ageing (e.g. corrosion or fatigue) or external actions (e.g. seismic, impact or overload). Examples of Opportunities include the existence of reserve capacities due to better material properties, synergic effects and over-design. Risks and opportunities are present in both new and existing structures. The purpose of an SHM system is to identify and quantify them, so that the consequences of risks can be avoided (e.g. a collapse) and the benefits of opportunities can be exploited (e.g. safely extending the lifetime of a bridge). Next, the expected responses to the expected degradations and the effects of the possible opportunities are established and an appropriate Structural Health Monitoring Systems is designed to detect such conditions. Only at this stage, the appropriate sensors are selected. When selecting the best sensors for the specific task, it is often necessary and beneficial to combine different measurement technologies. Once the sensors are installed and verified, data collection can start. If these logical steps are followed and the monitoring data is correctly acquired and managed, data analysis and interpretation will be greatly simplified. This process guarantees that each sensor placed in the structure serves at least one specific purpose and leads to a lean and costeffective system. This paper presents a generalized methodology for designing on optimized Bridge SHM monitoring system and a practical example from a field application: the new I35W Bridge in Minneapolis. © 2010 Taylor & Francis Group, London. Source

Inaudi D.,Smartec SA
Ammonia Plant Safety and Related Facilities

In the case of ammonia, small leaks can be detected by the rapid drop of temperature due to the evaporation of the released liquid ammonia. These local thermal anomalies can be reliably detected by a fiber optic distributed temperature sensing system that is able to detect temperature changes. Source

Laory I.,Ecole Polytechnique Federale de Lausanne | Trinh T.N.,Smartec SA | Posenato D.,Ecole Polytechnique Federale de Lausanne | Smith I.F.C.,Ecole Polytechnique Federale de Lausanne
Journal of Computing in Civil Engineering

Despite the recent advances in sensor technologies and data-acquisition systems, interpreting measurement data for structural monitoring remains a challenge. Furthermore, because of the complexity of the structures, materials used, and uncertain environments, behavioral models are difficult to build accurately. This paper presents novel model-free data-interpretation methodologies that combine moving principal component analysis (MPCA) with each of four regression-analysis methods - robust regression analysis (RRA), multiple linear analysis (MLR), support vector regression (SVR), and random forest (RF) - for damage detection during continuous monitoring of structures. The principal goal is to exploit the advantages of both MPCA and regression-analysis methods. The applicability of these combined methods is evaluated and compared with individual applications of MPCA, RRA, MLR, SVR, and RF through four case studies. Result showed that the combined methods outperformed noncombined methods in terms of damage detectability and time to detection. © 2013 American Society of Civil Engineers. Source

Glisic B.,Princeton University | Inaudi D.,Smartec SA
Structural Health Monitoring

Many bridges worldwide are approaching the end of their lifespan and it is necessary to assess their health condition in order to mitigate risks, prevent disasters, and plan maintenance activities in an optimized manner. Fracture critical bridges are of particular interest since they have only little or no load path redundancy. Structural health monitoring (SHM) has recently emerged as a branch of engineering, which aim is to improve the assessment of structural condition. Distributed optical fiber sensing technology has opened new possibilities in SHM. A distributed deformation sensor (sensing cable) is sensitive at each point of its length to strain changes and cracks. Such a sensor practically monitors a one-dimensional strain field and can be installed over all the length of the monitored structural members, thereby providing with integrity monitoring, i.e. direct detection and characterization (including recognition, localization, and quantification or rating) of local strain changes generated by damage. Integrity monitoring principles are developed and presented in this article. A large scale laboratory test and a real on-site application are briefly presented. © The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav. Source

From many points of view, fibre optic sensors are the ideal transducers for structural monitoring. Being durable, stable and insensitive to external perturbations, they are particularly interesting for the long-term health assessment of civil structures. Many different fibre optic sensor technologies exist and offer a wide range of performances and suitability for different applications. The most widely used sensing techniques include point sensors (Fibre Bragg Gratings and Fabry-Perot interferometers), long-gauge sensors (SOFO) and distributed sensors (Raman and Brillouin scattering sensors). These sensing technologies are now widely used in routine application for health monitoring of structures such as bridges, buildings, monuments, tunnels, dams, dykes, pipelines, landslides and many others. This contribution reviews these systems and technologies and briefly presents some significant application examples. Source

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