Bayesian probabilistic modeling for damage assessment in a bolted frame

Colin Haynes; Michael Todd

doi:10.1117/12.914635

18 April 2012 Bayesian probabilistic modeling for damage assessment in a bolted frame

Colin Haynes, Michael Todd

Proceedings Volume 8348, Health Monitoring of Structural and Biological Systems 2012; 83480D (2012) https://doi.org/10.1117/12.914635
Event: SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring, 2012, San Diego, California, United States

Abstract

This paper presents the development of a Bayesian framework for optimizing the design of a structural health monitoring (SHM) system. Statistical damage detection techniques are applied to a geometrically-complex, three-story structure with bolted joints. A sparse network of PZT sensor-actuators is bonded to the structure, using ultrasonic guided waves in both pulse-echo and pitch-catch modes to inspect the structure. Receiver operating characteristics are used to quantify the performance of multiple features (or detectors). The detection rate of the system is compared across different types and levels of damage. A Bayesian cost model is implemented to determine the best performing network.

Citation Download Citation

Colin Haynes and Michael Todd "Bayesian probabilistic modeling for damage assessment in a bolted frame", Proc. SPIE 8348, Health Monitoring of Structural and Biological Systems 2012, 83480D (18 April 2012); https://doi.org/10.1117/12.914635

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