The Signal Processing of Wharf Structure Health Monitoring Based on Wavelet Analysis

Xiao-bo Wang (), Jue-long Li, Jian-chun Xing and Li-qiang Xie
Additional contact information
Xiao-bo Wang: PLA University of Science and Technology
Jue-long Li: PLA University of Science and Technology
Jian-chun Xing: PLA University of Science and Technology
Li-qiang Xie: PLA University of Science and Technology

A chapter in Proceedings of 20th International Conference on Industrial Engineering and Engineering Management, 2013, pp 71-82 from Springer

Abstract: Abstract The importance of harbor wharf determines that we must grasp its health state in real time. First of all, this paper analyzes various harbor wharf damage forms, and builds its structure health monitoring system, then it points out the importance of signal processing in structural health monitoring. Wavelet analysis, as a new tool to data processing, with its advantages now is widely used in many fields. In this paper, the application of wavelet analysis in the harbor wharf structure is introduced, including signal denoising, signal compression and damage identification. Finally, this paper puts forward the research direction of wavelet analysis in structural health monitoring.

Keywords: Harbor wharf; Signal processing; Structure health monitoring; Wavelet analysis (search for similar items in EconPapers)
Date: 2013
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:978-3-642-40072-8_7

Ordering information: This item can be ordered from
http://www.springer.com/9783642400728

DOI: 10.1007/978-3-642-40072-8_7

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 ().