Robust Spectral Leak Detection of Complex Pipelines Using Filter Diagonalization Method
Title
Robust Spectral Leak Detection of Complex Pipelines Using Filter Diagonalization Method
Subject
Fast Fourier transform (FFT)
Fast Fourier transforms
filter diagonalization method
Filters
health pipeline monitoring
Humans
Leak detection
Lubricating oils
Monitoring
Petroleum
Pipelines
regularization techniques
Robustness
spectral analysis
Spectral analysis
Description
The control and managing of pipelines have been assuming a major importance for all kinds of fluids to be conveyed through. When the fluid is like oil, harmful liquid and/or water for human beings necessity, the monitoring of pipelines becomes extremely fundamental. Based on the reflexion according to fast detecting systems, spectral analysis response is a topic of interest. Among spectral analysis response techniques, fast Fourier transform (FFT) is rated. Different other techniques are utilized, but they are costly and difficult to be used. An interesting technique, used in nuclear magnetic resonance data processing, filter diagonalization method (FDM), for tackling FFT limitations, can be used, by considering the pipeline, especially complex configurations, as a vascular apparatus with arteries, veins, capillaries, etc. The thrombosis, for human vascular apparatus, that might be occur, can be considered as a leakage for the complex pipeline. The research proposes the use of FDM according to two sub techniques called algorithm I and algorithm II. The first algorithm is a direct transformation of FDM application, while the second includes robustness and a regularization technique to solve ill-posed problems that may emerge in processing data. The results are encouraging.
1605-1614
Creator
A. Lay-Ekuakille
G. Vendramin
A. Trotta
Publisher
IEEE Sensors Journal
Date
2009
Type
journalArticle
Collection
Citation
A. Lay-Ekuakille, G. Vendramin, and A. Trotta, “Robust Spectral Leak Detection of Complex Pipelines Using Filter Diagonalization Method,” Lamar University Midstream Center Research, accessed May 14, 2024, https://lumc.omeka.net/items/show/27260.