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Intelligent Real Time Data Interpretation of Rocket Test Data to Identify Sudden Transitions

[+] Author Affiliations
Ajay Mahajan

The University of Akron, Akron, OH

Christopher Oesch

Moog, Buffalo, NY

Fernando Figueroa

NASA, Stennis Space Center, MS

Paper No. DSCC2010-4067, pp. 719-726; 8 pages
doi:10.1115/DSCC2010-4067
From:
  • ASME 2010 Dynamic Systems and Control Conference
  • ASME 2010 Dynamic Systems and Control Conference, Volume 2
  • Cambridge, Massachusetts, USA, September 12–15, 2010
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-4418-2 | eISBN: 978-0-7918-3884-6
  • Copyright © 2010 by ASME

abstract

Integrated Systems Health Monitoring (ISHM) is an implementation of monitoring strategies for complex systems whereby avoiding catastrophic failure, extending life and leading to improved asset management. An ISHM generally encompasses intelligence at many levels and sub-systems including sensors, actuators, devices, etc., but this paper focuses on only smart sensors. Wavelet analysis is used to enhance previous work done in this area. The major advantage provided by adding wavelet analysis is the ability to detect sudden transitions as well as obtaining the frequency content using a much smaller data set then that required by the traditional Fourier transform method. Historically, sudden transitions were detected by visual methods or by offline analysis of the data. The algorithms presented in this paper provide an opportunity to automatically detect sudden transitions as well as many additional data anomalies, and provide improved data-correction and sensor health diagnostic abilities. The developed algorithms have been tested on actual rocket test data provided by NASA’s Stennis Space Center.

Copyright © 2010 by ASME
Topics: Rockets

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