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Research Spending & Results

Award Detail

Awardee:OKLAHOMA STATE UNIVERSITY
Doing Business As Name:Oklahoma State University
PD/PI:
  • Qi Cheng
  • (405) 744-9919
  • qi.cheng@okstate.edu
Award Date:09/08/2009
Estimated Total Award Amount: $ 326,617
Funds Obligated to Date: $ 326,617
  • FY 2009=$326,617
Start Date:09/01/2009
End Date:08/31/2013
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040101 RRA RECOVERY ACT
Award Title or Description:CPS:Small: A Unified Distributed Spatiotemporal Signal Processing Framework for Structural Health Monitoring
Federal Award ID Number:0932297
DUNS ID:049987720
Parent DUNS ID:049987720
Program:CPS-Cyber-Physical Systems
Program Officer:
  • Sylvia Spengler
  • (703) 292-8930
  • sspengle@nsf.gov

Awardee Location

Street:101 WHITEHURST HALL
City:Stillwater
State:OK
ZIP:74078-1011
County:Stillwater
Country:US
Awardee Cong. District:03

Primary Place of Performance

Organization Name:Oklahoma State University
Street:101 WHITEHURST HALL
City:Stillwater
State:OK
ZIP:74078-1011
County:Stillwater
Country:US
Cong. District:03

Abstract at Time of Award

CPS: CPS:Small: A Unified Distributed Spatiotemporal Signal Processing Framework for Structural Health Monitoring This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The objective of this research is to meet the urgent global need for improved safety and reduced maintenance costs of important infrastructures by developing a unified signal processing framework coupling spatiotemporal sensing data with physics-based and data-driven models. The approach is structured along the following thrusts: investigating the feasibility of statistical modeling of dynamic structures to address the spatiotemporal correlation of sensing data; developing efficient distributed damage detection and localization algorithms; investigating network enhancement through strategic sensor placement; addressing optimal sensor collaboration for recursive localized structural state estimation and prediction. Intellectual merit: This innovative unified framework approach has the potential of being more reliable and efficient with better scalability compared to the current state-of-the-art in structural health monitoring. The proposed research is also practical as it allows analysis of real-world data that accounts for structural properties, environmental noise, and loss of integrity over sensors. Probabilistic representation of significant damages allows more informative risk assessment. Broader impacts: The outcome of this project will provide an important step toward safety and reliability albeit increasing complexity in dynamic systems. New models and algorithms developed in this project are generic and can contribute in many other areas and applications that involve distributed recursive state estimation, distributed change detection and data fusion. This project will serve as an excellent educational platform to educate and train the next generation CPS researchers and engineers. Under-represented groups such as female students and Native American students will be supported in this project, at both the graduate and undergraduate levels.

Publications Produced as a Result of this Research

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Wu, T; Cheng, Q "Distributed Estimation over Fading Channels Using One-bit Quantization" IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, v.8, 2009, p.5779. doi:10.1109/TWC.2009.12.09010  View record at Web of Science

Q. Cheng, P. K. Varshney, J. H. Michels and C. M. Belcastro "Distributed Fault Detection with Correlated Decision Fusion" IEEE Trans. Aerospace and Electronic Systems, v.45, 2009, p.1448.

L. Sun, C. Chen and Q. Cheng "Feature Extraction and Pattern Identification for Anemometer Condition Diagnosis" International Journal of Prognostics and Health Management, v.3, 2012, p..

T. Wu and Q. Cheng "Distributed Estimation over Fading Channels Using One-bit Quantization" IEEE Trans. Wireless Communications, v.8, 2009, p.5779.

S. Gutta and Q. Cheng "An Efficient Training Algorithm for SVM-based Binary Classifiers" CiiT International Journal of Artificial Intelligent Systems and Machine Learning, v.3, 2011, p.234.

Q. Cheng, P. K. Varshney, J. H. Michels and C. M. Belcastro "Distributed Fault Detection with Correlated Decision Fusion" IEEE Trans. Aerospace and Electronic Systems, v.45, 2009, p.1448-1465.

L. Sun, C. Chen and Q. Cheng "Feature Extraction and Pattern Identification for Anemometer Condition Diagnosis" International Journal of Prognostics and Health Management, v.3, 2012, p..

Publications Produced as Conference Proceedings

Wu, T;Cheng, Q "One-bit Quantizer Design for Distributed Estimation under the Minimax Criterion" 2010 IEEE 71st Vehicular Technology Conference, v. , 2010, p. View record at Web of Science

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