Using neural networks as pipeline defect classifiers

Nik Ahmad Akram; Niusha Shafiabady; Dino Isa

doi:10.1109/ICITCS.2013.6717894

Using neural networks as pipeline defect classifiers

Nik Ahmad Akram, Niusha Shafiabady, Dino Isa

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

Abstract

In this paper we discuss an approach to classify different level of defects on a pipeline. The proposed techniques implemented on a lab scale experimental rig and tested using real-time signal. The signal is acquired using Long Range Ultrasonic Transducer (LRUT) then classified using Neural Network (NN). The Neural Network was able to classify the different signal of different level of defects.

Original language	English
Title of host publication	2013 International Conference on IT Convergence and Security, ICITCS 2013
Publisher	IEEE Computer Society
Pages	1–4
Number of pages	4
Volume	1
ISBN (Print)	9781479928453
DOIs	https://doi.org/10.1109/ICITCS.2013.6717894
Publication status	Published - 2013
Externally published	Yes
Event	2013 3rd International Conference on IT Convergence and Security, ICITCS 2013 - Macau, China Duration: 16 Dec 2013 → 18 Dec 2013

Publication series

Name	2013 International Conference on IT Convergence and Security, ICITCS 2013

Conference

Conference	2013 3rd International Conference on IT Convergence and Security, ICITCS 2013
Country/Territory	China
City	Macau
Period	16/12/13 → 18/12/13

Access to Document

10.1109/ICITCS.2013.6717894

Cite this

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title = "Using neural networks as pipeline defect classifiers",

abstract = "In this paper we discuss an approach to classify different level of defects on a pipeline. The proposed techniques implemented on a lab scale experimental rig and tested using real-time signal. The signal is acquired using Long Range Ultrasonic Transducer (LRUT) then classified using Neural Network (NN). The Neural Network was able to classify the different signal of different level of defects.",

keywords = "Machine learning, Neural network, Pipeline defect detection",

author = "Akram, {Nik Ahmad} and Niusha Shafiabady and Dino Isa",

year = "2013",

doi = "10.1109/ICITCS.2013.6717894",

language = "English",

isbn = "9781479928453",

volume = "1",

series = "2013 International Conference on IT Convergence and Security, ICITCS 2013",

publisher = "IEEE Computer Society",

pages = "1–4",

booktitle = "2013 International Conference on IT Convergence and Security, ICITCS 2013",

address = "United States",

note = "2013 3rd International Conference on IT Convergence and Security, ICITCS 2013 ; Conference date: 16-12-2013 Through 18-12-2013",

}

Akram, NA, Shafiabady, N & Isa, D 2013, Using neural networks as pipeline defect classifiers. in 2013 International Conference on IT Convergence and Security, ICITCS 2013. vol. 1, 6717894, 2013 International Conference on IT Convergence and Security, ICITCS 2013, IEEE Computer Society, pp. 1–4, 2013 3rd International Conference on IT Convergence and Security, ICITCS 2013, Macau, China, 16/12/13. https://doi.org/10.1109/ICITCS.2013.6717894

Using neural networks as pipeline defect classifiers. / Akram, Nik Ahmad; Shafiabady, Niusha; Isa, Dino.
2013 International Conference on IT Convergence and Security, ICITCS 2013. Vol. 1 IEEE Computer Society, 2013. p. 1–4 6717894 (2013 International Conference on IT Convergence and Security, ICITCS 2013).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper published in Proceedings › peer-review

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AB - In this paper we discuss an approach to classify different level of defects on a pipeline. The proposed techniques implemented on a lab scale experimental rig and tested using real-time signal. The signal is acquired using Long Range Ultrasonic Transducer (LRUT) then classified using Neural Network (NN). The Neural Network was able to classify the different signal of different level of defects.

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DO - 10.1109/ICITCS.2013.6717894

M3 - Conference Paper published in Proceedings

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T3 - 2013 International Conference on IT Convergence and Security, ICITCS 2013

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BT - 2013 International Conference on IT Convergence and Security, ICITCS 2013

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Y2 - 16 December 2013 through 18 December 2013

ER -

Using neural networks as pipeline defect classifiers

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