Abstract

Noise and interference in sensor measurements degrade the quality of data and have a negative impact on the performance of structural damage diagnosis systems. In this paper, a novel adaptive measurement screening approach is presented to automatically select the most informative measurements and use them intelligently for structural damage estimation. The method is implemented efficiently in a sequential Monte Carlo (SMC) setting using particle filtering. The noise suppression and improved damage estimation capability of the proposed method is demonstrated by an application to the problem of estimating progressive fatigue damage in an aluminum compact-tension (CT) sample using noisy PZT sensor measurements.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Volume7981
DOIs
StatePublished - 2011
EventSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011 - San Diego, CA, United States
Duration: Mar 7 2011Mar 10 2011

Other

OtherSensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011
CountryUnited States
CitySan Diego, CA
Period3/7/113/10/11

Fingerprint

Damage
damage
Sequential Monte Carlo
Noise Suppression
Sensor
Particle Filtering
Fatigue Damage
sensors
Sensors
Fatigue damage
Aluminum
Screening
estimating
screening
Interference
retarding
aluminum
interference

Keywords

  • adaptive measurement selection
  • noise suppression
  • progressive damage diagnosis
  • sequential Monte Carlo
  • structural health monitoring

ASJC Scopus subject areas

  • Applied Mathematics
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics

Cite this

Zhou, W., Kovvali, N., Papandreou-Suppappola, A., Chattopadhyay, A., & Peralta, P. (2011). Adaptive measurement selection for progressive damage estimation. In Proceedings of SPIE - The International Society for Optical Engineering (Vol. 7981). [798127] https://doi.org/10.1117/12.882029

Adaptive measurement selection for progressive damage estimation. / Zhou, Wenfan; Kovvali, Narayan; Papandreou-Suppappola, Antonia; Chattopadhyay, Aditi; Peralta, Pedro.

Proceedings of SPIE - The International Society for Optical Engineering. Vol. 7981 2011. 798127.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhou, W, Kovvali, N, Papandreou-Suppappola, A, Chattopadhyay, A & Peralta, P 2011, Adaptive measurement selection for progressive damage estimation. in Proceedings of SPIE - The International Society for Optical Engineering. vol. 7981, 798127, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2011, San Diego, CA, United States, 3/7/11. https://doi.org/10.1117/12.882029
Zhou W, Kovvali N, Papandreou-Suppappola A, Chattopadhyay A, Peralta P. Adaptive measurement selection for progressive damage estimation. In Proceedings of SPIE - The International Society for Optical Engineering. Vol. 7981. 2011. 798127 https://doi.org/10.1117/12.882029
Zhou, Wenfan ; Kovvali, Narayan ; Papandreou-Suppappola, Antonia ; Chattopadhyay, Aditi ; Peralta, Pedro. / Adaptive measurement selection for progressive damage estimation. Proceedings of SPIE - The International Society for Optical Engineering. Vol. 7981 2011.
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