Coupling sensing hardware with data interrogation software for structural health monitoring [electronic resource].
- Published
- Washington, D.C. : United States. Dept. of Energy, 2004.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy - Physical Description
- 12 unnumbered pages : digital, PDF file
- Additional Creators
- Los Alamos National Laboratory, United States. Department of Energy, and United States. Department of Energy. Office of Scientific and Technical Information
Access Online
- Restrictions on Access
- Free-to-read Unrestricted online access
- Summary
- The process of implementing a damage detection strategy for aerospace, civil and mechanical engineering infrastructure is referred to as structural health monitoring (SHM). The authors approach is to address the SIAM problem in the context of a statistical pattern recognition paradigm. In this paradigm, the process can be broken down into four parts: (1) Operational Evaluation, (2) Data Acquisition and Cleansing, (3) Feature Extraction and Data Compression, and (4) Statistical Model Development for Feature Discrimination. These processes must be implemented through hardware or software and, in general, some combination of these two approaches will be used. This paper will discuss each portion of the SHM process with particular emphasis on the coupling of a general purpose data interrogation software package for structural health monitoring (DIAMOND 11) with a modular wireless sensing and processing platform that is being jointly developed with Motorola Labs. More specifically, this paper will address the need to take an integrated hardware/software approach to developing SHM solutions.
- Report Numbers
- E 1.99:la-ur-04-7997
la-ur-04-7997 - Subject(s)
- Other Subject(s)
- Note
- Published through SciTech Connect.
01/01/2004.
"la-ur-04-7997"
Submitted to: Proceedings of the XI DINAME, Ouro Preto- MG-Brazil, 28th February - 4th March, 2005.
Farrar, C. R. (Charles R.); Allen, D. W. (David W.); Ball, S. (Steven); Masquelier, Michael P.; Park, G. H. (Gyu Hae).
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