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2012 | OriginalPaper | Chapter

14. Rapid Structural Condition Assessment Using Transmissibility with Quantified Confidence for Decision Making

Authors : Zhu Mao, Michael Todd

Published in: Topics in Model Validation and Uncertainty Quantification, Volume 4

Publisher: Springer New York

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Abstract

The motivation of this paper is to achieve a rapid condition assessment and identification for aero-space structures. For such a circumstance, transmissibility is a good vibration-domain feature for damage detection and localization, highlighting the sensitivity of the relative dynamics between any two interest points on the structure to many forms of damage (such as connection losses). With a quantified uncertainty model of transmissibility available, test results may be compared to baseline (undamaged) statistics, and statistical significance under certain confidence level may be found. Receiver operating characteristic curves suggest the optimized threshold of detection that balances detections and false alarms. In this paper, three such models are presented, and the aforementioned statistical identifications are validated through a plate structure with a single-edge clamped boundary condition. The benchmark test results show very good consistency with the model prediction and the robustness to different noise contamination situations.

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Literature
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go back to reference Mao Z, Todd MD (2011) A model of uncertainty quantification in the estimation of noise-contaminated transmissibility measurements for system identification. In: Proceedings of 29th society of experimental mechanics (SEM) international modal analysis conference (IMAC – XXIX), Jacksonville Mao Z, Todd MD (2011) A model of uncertainty quantification in the estimation of noise-contaminated transmissibility measurements for system identification. In: Proceedings of 29th society of experimental mechanics (SEM) international modal analysis conference (IMAC – XXIX), Jacksonville
Metadata
Title
Rapid Structural Condition Assessment Using Transmissibility with Quantified Confidence for Decision Making
Authors
Zhu Mao
Michael Todd
Copyright Year
2012
Publisher
Springer New York
DOI
https://doi.org/10.1007/978-1-4614-2431-4_14