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Monitoring System of an Industrial Steel Tower Structure
https://orcid.org/http://orcid.org/0000-0002-9482-8540
Structural Health Monitoring (SHM) systems of civil engineering structures aim to assess and ensure the safety of structures and people. This paper describes a real-world application of an SHM system in an industrial steel tower structure. This is a high steel structure, containing several mechanical equipment with different loads, which operate at various frequencies. The monitoring approach includes a computer modeling of the structure, primarily used to define the sensor network. The sensors were mounted at predetermined locations designed to continuously measure vibrations and deformations at critical points. The sensor network consists of an array of sensors and a gateway. The sensors include strain gauges and triaxial accelerometers, as well as other weather sensors. Data are acquired both from time series of values observed at regular intervals and from structurally relevant measured values, called events, where specific data are collected. Machine learning is used in the development of statistical models for feature discrimination. A visualization user interface is provided to access all data through a user friendly and accessible tool. The paper presents the main results obtained so far, with the primary assessment of the structural health conditions.
Monitoring System of an Industrial Steel Tower Structure
https://orcid.org/http://orcid.org/0000-0002-9482-8540
Structural Health Monitoring (SHM) systems of civil engineering structures aim to assess and ensure the safety of structures and people. This paper describes a real-world application of an SHM system in an industrial steel tower structure. This is a high steel structure, containing several mechanical equipment with different loads, which operate at various frequencies. The monitoring approach includes a computer modeling of the structure, primarily used to define the sensor network. The sensors were mounted at predetermined locations designed to continuously measure vibrations and deformations at critical points. The sensor network consists of an array of sensors and a gateway. The sensors include strain gauges and triaxial accelerometers, as well as other weather sensors. Data are acquired both from time series of values observed at regular intervals and from structurally relevant measured values, called events, where specific data are collected. Machine learning is used in the development of statistical models for feature discrimination. A visualization user interface is provided to access all data through a user friendly and accessible tool. The paper presents the main results obtained so far, with the primary assessment of the structural health conditions.
Monitoring System of an Industrial Steel Tower Structure
https://orcid.org/http://orcid.org/0000-0002-9482-8540
Structural Health Monitoring (SHM) systems of civil engineering structures aim to assess and ensure the safety of structures and people. This paper describes a real-world application of an SHM system in an industrial steel tower structure. This is a high steel structure, containing several mechanical equipment with different loads, which operate at various frequencies. The monitoring approach includes a computer modeling of the structure, primarily used to define the sensor network. The sensors were mounted at predetermined locations designed to continuously measure vibrations and deformations at critical points. The sensor network consists of an array of sensors and a gateway. The sensors include strain gauges and triaxial accelerometers, as well as other weather sensors. Data are acquired both from time series of values observed at regular intervals and from structurally relevant measured values, called events, where specific data are collected. Machine learning is used in the development of statistical models for feature discrimination. A visualization user interface is provided to access all data through a user friendly and accessible tool. The paper presents the main results obtained so far, with the primary assessment of the structural health conditions.
Monitoring System of an Industrial Steel Tower Structure
Lecture Notes in Civil Engineering
Rainieri, Carlo (Herausgeber:in) / Fabbrocino, Giovanni (Herausgeber:in) / Caterino, Nicola (Herausgeber:in) / Ceroni, Francesca (Herausgeber:in) / Notarangelo, Matilde A. (Herausgeber:in) / Zeferino, João (Autor:in) / Gonçalves, Eduardo (Autor:in) / Carapito, Paulo (Autor:in) / Santos, Filipe (Autor:in)
International Workshop on Civil Structural Health Monitoring ; 2021 ; Naples, Italy
25.08.2021
8 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
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