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Book
Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures
Authors: ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

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Abstract

In the past, when elements in sructures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools.

Keywords

Medicine --- structural health monitoring --- jointless bridge --- high-speed railway --- bearing --- expansion device --- displacement analysis --- structural reliability estimation --- modal identification --- finite element model updating --- cyber-physical systems --- crowdsourcing --- temperature effects --- time-lag effect --- Fourier series expansion --- box-girder bridges --- structural engineering --- overall deformation monitoring --- perspective transformation --- edge detection --- close-range photogrammetry --- railway embankment --- condition assessment --- ground penetrating radar --- multi-attribute utility theory --- laser scanner --- line scanner --- structure monitoring --- deformation --- dynamic measurements --- scan-to-BIM --- point cloud --- HBIM --- FEM --- Rhinoceros --- terrestrial laser scanner (TLS) --- ground-based real aperture radar (GB-RAR) --- vibration frequency --- spectral analysis --- displacement --- structural health monitoring (SHM) --- vibration-based damage detection --- system identification --- subspace system identification (SSI) --- tie rod --- natural frequencies --- mode shapes --- root-mean-square error (RMSE) --- environmental monitoring --- long-range mapping --- MMS --- sub-millimetric EDM geodetic techniques --- damage detection --- damage localization --- hybrid approach --- neural network --- timber bridges --- stress-laminated timber decks --- monitoring --- humidity-temperature sensors --- wood moisture content --- multi-phase models --- finite element method --- moving load identification --- strain influence line --- load transverse distribution --- strain integral coefficient --- identification error --- n/a


Book
Innovative Methods and Materials in Structural Health Monitoring of Civil Infrastructures
Authors: ---
Year: 2021 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute

Loading...
Export citation

Choose an application

Bookmark

Abstract

In the past, when elements in sructures were composed of perishable materials, such as wood, the maintenance of houses, bridges, etc., was considered of vital importance for their safe use and to preserve their efficiency. With the advent of materials such as reinforced concrete and steel, given their relatively long useful life, periodic and constant maintenance has often been considered a secondary concern. When it was realized that even for structures fabricated with these materials that the useful life has an end and that it was being approached, planning maintenance became an important and non-negligible aspect. Thus, the concept of structural health monitoring (SHM) was introduced, designed, and implemented as a multidisciplinary method. Computational mechanics, static and dynamic analysis of structures, electronics, sensors, and, recently, the Internet of Things (IoT) and artificial intelligence (AI) are required, but it is also important to consider new materials, especially those with intrinsic self-diagnosis characteristics, and to use measurement and survey methods typical of modern geomatics, such as satellite surveys and highly sophisticated laser tools.

Keywords

structural health monitoring --- jointless bridge --- high-speed railway --- bearing --- expansion device --- displacement analysis --- structural reliability estimation --- modal identification --- finite element model updating --- cyber-physical systems --- crowdsourcing --- temperature effects --- time-lag effect --- Fourier series expansion --- box-girder bridges --- structural engineering --- overall deformation monitoring --- perspective transformation --- edge detection --- close-range photogrammetry --- railway embankment --- condition assessment --- ground penetrating radar --- multi-attribute utility theory --- laser scanner --- line scanner --- structure monitoring --- deformation --- dynamic measurements --- scan-to-BIM --- point cloud --- HBIM --- FEM --- Rhinoceros --- terrestrial laser scanner (TLS) --- ground-based real aperture radar (GB-RAR) --- vibration frequency --- spectral analysis --- displacement --- structural health monitoring (SHM) --- vibration-based damage detection --- system identification --- subspace system identification (SSI) --- tie rod --- natural frequencies --- mode shapes --- root-mean-square error (RMSE) --- environmental monitoring --- long-range mapping --- MMS --- sub-millimetric EDM geodetic techniques --- damage detection --- damage localization --- hybrid approach --- neural network --- timber bridges --- stress-laminated timber decks --- monitoring --- humidity-temperature sensors --- wood moisture content --- multi-phase models --- finite element method --- moving load identification --- strain influence line --- load transverse distribution --- strain integral coefficient --- identification error --- n/a

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