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Damage Detection and Monitoring in Buried Steel Pipelines.

Davide Di Nardo Di Maio

Damage Detection and Monitoring in Buried Steel Pipelines.

Rel. Rosario Ceravolo, Gaetano Miraglia, Erica Lenticchia, Marco Civera. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Civile, 2021

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Pipeline structures are the most convenient and fastest means of transport and supply of fuels and fluids in general. Therefore, their correct and continuous functioning is of vital economic and social importance. Nowadays, the most widely used Pipeline Integrity Management techniques involve fairly invasive monitoring methods as resorting to Pipeline Inspection Gauge devices. The need to temporarily stop the lines and non-targeted inspections define the poor efficiency of the current monitoring techniques of Steel Pipelines which require the research of new investigation methods. Looking at these premises, a Structural Health Monitoring approach for Damage Identification would seem the most suitable to fulfil the task of studying the health status of Pipelines, such as the Vibration Based Investigation which is one of the common methods used in the field of civil engineering monitoring. The problem of these type of monitoring approaches is that they have been studied and widely used on structures such as bridges or towers, but they have not found a well-defined application in the field of Pipeline Monitoring. In recent years, the concepts of information theory and more specifically spectral entropy measures have been increasingly investigated and applied in SHM. Among the numerous existing forms of entropy, the intention of this work, which is the natural consequence of the studies carried out by Ceravolo et al. and transposed in publications [15] and [33], is to investigate a method founded on the use of Wiener Entropy as the damage-sensitive feature for the Buried Steel Pipelines Damage Identification. [15] Ceravolo, Lenticchia & Miraglia, Elsevier Ltd (2019). Spectral entropy of acceleration data for damage detection in masonry buildings affected by seismic sequences. [33] Ceravolo, Civera, Lenticchia, Miraglia & Surace, Elsevier Ltd (2020). Damage Detection and Localisation in Buried Pipelinies using Entropy in Information Theory.

Relators: Rosario Ceravolo, Gaetano Miraglia, Erica Lenticchia, Marco Civera
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 109
Corso di laurea: Corso di laurea magistrale in Ingegneria Civile
Classe di laurea: New organization > Master science > LM-23 - CIVIL ENGINEERING
Aziende collaboratrici: Politecnico di Torino
URI: http://webthesis.biblio.polito.it/id/eprint/19440
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