
Proceedings Paper
Optimal sensor placement strategy and sensor design for high-quality system monitoringFormat | Member Price | Non-Member Price |
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Paper Abstract
This paper presents a systematic investigation of the effect of sensor placement on the measurement data quality and subsequently, on the effectiveness of machine system health monitoring. First, signal propagation process from the defect location to the sensor was analyzed. Numerical simulations using finite element modeling was then conducted to determine the signal strength at several representative sensor locations. The analytical and numerical results showed that placing sensors closer to the component being monitored resulted in higher signal-to-noise ratio, thus improving the data quality. Using meso-sized piezoceramic chips, the obtained results were then experimentally evaluated. Comparisons with a set of commercial vibration sensors verified the developed sensor placement strategy. The presented study quantitatively justified why placing sensors closer to the machine being monitored is of critical importance to ensuring high quality data, and confirmed that the customized shock wave sensing approach can achieve comparable result for vibration measurement, but with a much less space requirement.
Paper Details
Date Published: 29 July 2004
PDF: 10 pages
Proc. SPIE 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (29 July 2004); doi: 10.1117/12.539976
Published in SPIE Proceedings Vol. 5391:
Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
Shih-Chi Liu, Editor(s)
PDF: 10 pages
Proc. SPIE 5391, Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems, (29 July 2004); doi: 10.1117/12.539976
Show Author Affiliations
Robert X. Gao, Univ. of Massachusetts/Amherst (United States)
Changting Wang, GE Gobal Research Ctr. (United States)
Changting Wang, GE Gobal Research Ctr. (United States)
Shuang Wen Sheng, Univ. of Massachusetts/Amherst (United States)
Published in SPIE Proceedings Vol. 5391:
Smart Structures and Materials 2004: Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems
Shih-Chi Liu, Editor(s)
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