Paper
16 June 1998 Information processing for aerospace structural health monitoring
Peter F. Lichtenwalner, Edward V. White, Erwin W. Baumann
Author Affiliations +
Abstract
Structural health monitoring (SHM) technology provides a means to significantly reduce life cycle of aerospace vehicles by eliminating unnecessary inspections, minimizing inspection complexity, and providing accurate diagnostics and prognostics to support vehicle life extension. In order to accomplish this, a comprehensive SHM system will need to acquire data from a wide variety of diverse sensors including strain gages, accelerometers, acoustic emission sensors, crack growth gages, corrosion sensors, and piezoelectric transducers. Significant amounts of computer processing will then be required to convert this raw sensor data into meaningful information which indicates both the diagnostics of the current structural integrity as well as the prognostics necessary for planning and managing the future health of the structure in a cost effective manner. This paper provides a description of the key types of information processing technologies required in an effective SHM system. These include artificial intelligence techniques such as neural networks, expert systems, and fuzzy logic for nonlinear modeling, pattern recognition, and complex decision making; signal processing techniques such as Fourier and wavelet transforms for spectral analysis and feature extraction; statistical algorithms for optimal detection, estimation, prediction, and fusion; and a wide variety of other algorithms for data analysis and visualization. The intent of this paper is to provide an overview of the role of information processing for SHM, discuss various technologies which can contribute to accomplishing this role, and present some example applications of information processing for SHM implemented at the Boeing Company.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter F. Lichtenwalner, Edward V. White, and Erwin W. Baumann "Information processing for aerospace structural health monitoring", Proc. SPIE 3326, Smart Structures and Materials 1998: Industrial and Commercial Applications of Smart Structures Technologies, (16 June 1998); https://doi.org/10.1117/12.310656
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CITATIONS
Cited by 7 scholarly publications.
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KEYWORDS
Structural health monitoring

Data processing

Sensors

Neural networks

Data modeling

Diagnostics

Filtering (signal processing)

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