A Neural Network System for Fault Prediction in Pipelines by Acoustic Emission Techniques-Reference-Cited by-同舟云学术

A Neural Network System for Fault Prediction in Pipelines by Acoustic Emission Techniques

Published:2021-06-08 Issue:3-4 Volume:32 Page:132-146
ISSN:0934-9847
Container-title:Research in Nondestructive Evaluation
language:en
Short-container-title:Research in Nondestructive Evaluation

Author:

Noseda Francesco¹^ORCID,Ribeiro Marnet Luiza²^ORCID,Carlim Carlos²^ORCID,Rennó Costa Luiz²^ORCID,de Moura Junior Natanael²^ORCID,Pereira Calôba Luiz²^ORCID,Soares Sérgio Damasceno³^ORCID,Clarke Thomas⁴^ORCID,Callegari Jacques Ricardo⁴

Affiliation:

1. Applied Mathematics Department, IM-UFRJ, Rio de Janeiro, Brazil

2. Signal Processing Laboratory, COPPE-UFRJ, Rio de Janeiro, Brazil

3. Petrobras Research Center, CENPES-PETROBRAS, Rio de Janeiro, Brazil

4. Physical Metallurgy Laboratory, DEMET-UFRGS, Porto Alegre, Brazil

Funder

PETROBRAS CENPES

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Mechanics of Materials,Condensed Matter Physics,General Materials Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/09349847.2021.1930305

Reference19 articles.

1. Signal and model-based fault detection for aircraft systems

2. Comparative analysis of neural network and regression based condition monitoring approaches for wind turbine fault detection

3. Fault detection and other time series opportunities in the petroleum industry

4. A. Khodabakhsh, I. Ari, and M. Bakir, ArXiv:1705.04583 (2017).

5. Pipeline Incident 20 Year Trends, PHMSA, https://www.phmsa.dot.gov/data-and-statistics/pipeline/pipeline-incident-20-year-trends (accessed 2018)

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Leak State Detection and Size Identification for Fluid Pipelines with a Novel Acoustic Emission Intensity Index and Random Forest;Sensors;2023-11-10

2. Prediction of Water Leakage in Pipeline Networks Using Graph Convolutional Network Method;Applied Sciences;2023-06-22

3. Quantitative Investigation of Acoustic Emission Waveform Parameters from Crack Opening in a Rail Section Using Clustering Algorithms and Advanced Signal Processing;Sensors;2022-11-09

4. Fault prediction algorithm for offshore wind energy conversion system based on machine learning;2021 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS);2021-12-05