Detail publikace

Non-destructive Testing of CIPP Defects Using Machine Learning Approach

DVOŘÁK, R. PAZDERA, L. TOPOLÁŘ, L. JAKUBKA, L. PUCHÝŘ, J.

Originální název

Non-destructive Testing of CIPP Defects Using Machine Learning Approach

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Retrofitting; Cured-in-Place Pipes; Non-Destructive Testing; Impact-Echo Method; Pipe Defects; Acoustic Parameters; Machine Learning; Classification

Autoři

DVOŘÁK, R.; PAZDERA, L.; TOPOLÁŘ, L.; JAKUBKA, L.; PUCHÝŘ, J.

Vydáno

11. 10. 2023

Nakladatel

Narodni in univerzitetni knjižnici v Ljubljani

Místo

Portorož, Slovenia

ISBN

78-961-94088-5-8

Kniha

28th INTERNATIONAL CONFERENCE ON MATERIALS AND TECHNOLOGY

Edice

1

Číslo edice

1

Strany od

33

Strany do

33

Strany počet

1

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"
}