Advanced Wigner Method for Fault Detection and Diagnosis System

Do Van Tuan (), Sang Jin Cho () and Ui Pil Chong ()
Additional contact information
Do Van Tuan: University of Ulsan, School of Computer Engineering and Information Technology
Sang Jin Cho: University of Ulsan, School of Computer Engineering and Information Technology
Ui Pil Chong: University of Ulsan, School of Computer Engineering and Information Technology

A chapter in Modeling, Simulation and Optimization of Complex Processes, 2008, pp 587-603 from Springer

Abstract: Abstract An advanced Wigner method for time-frequency analysis based on the Wigner distribution and short-time Fourier transformation (STFT) methods is used to examine the acoustic emission signals detected during the operation of pipelines in the power plants. The acoustic emission signals, which depend on the behavior of materials deforming under stress, will be changed when pipelines crack or leak. Based on the unusual characteristics of the signals in frequency domain and some features in time domain, cracking or leaking problems can be detected. Our proposed method, a combination of advanced Wigner distribution and Wavelet transformation methods, is proposed for a fault detection and diagnosis system in the power plants. The results of our proposed method are compared with the advanced Wigner distribution and STFT methods.

Keywords: Acoustic Emission; Fault Detection; Acoustic Emission Signal; High Frequency Component; Diagnosis System (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-540-79409-7_44

Ordering information: This item can be ordered from
http://www.springer.com/9783540794097

DOI: 10.1007/978-3-540-79409-7_44

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().