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DVOŘÁK, R.; PAZDERA, L.; TOPOLÁŘ, L.; JAKUBKA, L.; PUCHÝŘ, J.
Original Title
Non-destructive Testing of CIPP Defects Using Machine Learning Approach
English Title
Type
Paper in proceedings outside WoS and Scopus
Original Abstract
This paper compares different sensors used for IE proposed testing, namely piezoceramic and microphone sensors. It evaluates their ability to distinguish between defects present in the body of the CIPP via a machine-learning approach using random tree classifiers.
English abstract
Keywords
Retrofitting; Cured-in-Place Pipes; Non-Destructive Testing; Impact-Echo Method; Pipe Defects; Acoustic Parameters; Machine Learning; Classification
Key words in English
Authors
RIV year
2024
Released
11.10.2023
Publisher
Narodni in univerzitetni knjižnici v Ljubljani
Location
Portorož, Slovenia
ISBN
78-961-94088-5-8
Book
28th INTERNATIONAL CONFERENCE ON MATERIALS AND TECHNOLOGY
Edition
1
Pages from
33
Pages to
Pages count
URL
https://mater-tehnol.si/index.php/MatTech/article/view/1022/277
BibTex
@inproceedings{BUT184962, author="Richard {Dvořák} and Luboš {Pazdera} and Libor {Topolář} and Luboš {Jakubka} and Jan {Puchýř}", title="Non-destructive Testing of CIPP Defects Using Machine Learning Approach", booktitle="28th INTERNATIONAL CONFERENCE ON MATERIALS AND TECHNOLOGY", year="2023", series="1", number="1", pages="33--33", publisher="Narodni in univerzitetni knjižnici v Ljubljani", address="Portorož, Slovenia", isbn="78-961-94088-5-8", url="https://mater-tehnol.si/index.php/MatTech/article/view/1022/277" }