Development of an autonomous continuous monitoring system for mechanical damage detection.

TL;DRAbstract

The primary objective of damage identification is to ascertain the existence of damage within a mechanical system. This study applies the Sequential Probability Ratio Test (SPRT) to examine if damage is present or not. In the original formulation of the SPRT, the distribution of data is assumed Gaussian and thresholds for monitoring are set focusing on the center mass properties of the distribution. Decision-making for damage identification is, however, often sensitive to the tails of the distribution and the tails may not necessarily be governed by Gaussian characteristics. By modeling the tails using the technique of Extreme Value Statistics (EVS), the thresholds for the SPRT may be set more accurately avoiding the unnecessary normality assumption. The proposed combination of the SPRT and the EVS is demonstrated using experimental data collected from a three-story frame structure with bolted connections. The primary goal of structural health monitoring is simply to identify from meas

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