TY - CHAP
T1 - Basic concepts of neural networks and deep learning and their applications for pipeline damage detection
AU - Razvarz, Sina
AU - Jafari, Raheleh
AU - Gegov, Alexander
PY - 2020/10/2
Y1 - 2020/10/2
N2 - Pipelines have been extensively implemented for the transport of natural gas and liquid petroleum over large distances as they are safe, convenient, and more economical. However, there are several kind of damages that might happen to the pipeline, for instance erosion, breaking, and dent. Thus, if these faults are not correctly refit will cause significant pipeline demolitions which have a tremendous impact on the environment. Deep learning approaches assist operators to recognize the damages in pipelines in the earliest phases so that they can have a good time for discussion on how to solve the problem and gathering information. In this chapter, some types of threats which usually occur in pipelines are introduced. Moreover, early detection of pipeline threats using deep learning methods combined with classification methods are studied for pipeline safety and damage prevention.
AB - Pipelines have been extensively implemented for the transport of natural gas and liquid petroleum over large distances as they are safe, convenient, and more economical. However, there are several kind of damages that might happen to the pipeline, for instance erosion, breaking, and dent. Thus, if these faults are not correctly refit will cause significant pipeline demolitions which have a tremendous impact on the environment. Deep learning approaches assist operators to recognize the damages in pipelines in the earliest phases so that they can have a good time for discussion on how to solve the problem and gathering information. In this chapter, some types of threats which usually occur in pipelines are introduced. Moreover, early detection of pipeline threats using deep learning methods combined with classification methods are studied for pipeline safety and damage prevention.
UR - http://www.scopus.com/inward/record.url?scp=85092036517&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-59246-2_5
DO - 10.1007/978-3-030-59246-2_5
M3 - Chapter (peer-reviewed)
AN - SCOPUS:85092036517
SN - 9783030592455
SN - 9783030592486
T3 - Studies in Systems, Decision and Control
SP - 101
EP - 119
BT - Flow Modelling and Control in Pipeline Systems
PB - Springer
ER -