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Outlier Analysis of Nonlinear Solitary Waves for Health Monitoring Applications

HODA JALALI, BOWEN ZHENG, AMIR NASROLLAHI, PIERVINCENZO RIZZO

Abstract


Structural health monitoring methods based on highly nonlinear solitary waves are emerging as a potential cost-effective technique to monitor or inspect a variety of structures. In the present study, the use of outlier analysis in the form of a discordancy test was investigated to enhance the damage detection capability of an HNSWs-based monitoring system. An experiment was conducted to detect simulated defects in a thick steel plate. HNSWs features were extracted and fed to a univariate analysis that compared the testing data to a set of baseline data. The results show that the outlier analysis improves the HNSWs ability to detect damage.


DOI
10.12783/shm2019/32370

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