Publication detail

Non-destructive Testing of CIPP Defects Using Machine Learning Approach

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

Original Title

Non-destructive Testing of CIPP Defects Using Machine Learning Approach

Type

article in a collection out of WoS and Scopus

Language

English

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.

Keywords

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

Authors

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

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

Edition number

1

Pages from

33

Pages to

33

Pages count

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"
}