Sensor fusion and damage classification in composite materials

Wenfan Zhou; Whitney D. Reynolds; Albert Moncada; Narayan Kovvali; Aditi Chattopadhyay; Antonia Papandreou-Suppappola; Douglas Cochran

doi:10.1117/12.776608

3 April 2008 Sensor fusion and damage classification in composite materials

Wenfan Zhou, Whitney D. Reynolds, Albert Moncada, Narayan Kovvali, Aditi Chattopadhyay, Antonia Papandreou-Suppappola, Douglas Cochran

Author Affiliations +

Proceedings Volume 6926, Modeling, Signal Processing, and Control for Smart Structures 2008; 69260N (2008) https://doi.org/10.1117/12.776608
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2008, San Diego, California, United States

Abstract

We describe a statistical method for the classification of damage in complex structures. Our approach is based on a Bayesian framework using hidden Markov models (HMMs) to model time-frequency features extracted from structural data. We also propose two different methods for sensor fusion to combine information from multiple distributed sensors such that the overall classification performance is increased. The proposed approaches are applied to the classification and localization of delamination in a laminated composite plate. Results using both discrete and continuous observation density HMMs, together with the sensor fusion, are presented and discussed.

Citation Download Citation

Wenfan Zhou, Whitney D. Reynolds, Albert Moncada, Narayan Kovvali, Aditi Chattopadhyay, Antonia Papandreou-Suppappola, and Douglas Cochran "Sensor fusion and damage classification in composite materials", Proc. SPIE 6926, Modeling, Signal Processing, and Control for Smart Structures 2008, 69260N (3 April 2008); https://doi.org/10.1117/12.776608

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