Impedance-based structural health monitoring and statistical method for threshold-level determination applied to 2024-T3 aluminum panels under varying temperature

Abstract

The impedance-based structural health monitoring method has become a promising and attractive tool for damage identification and is considered a nondestructive evaluation technique. However, conventional impedance-based structural health monitoring studies have mainly focused on structural damage identification but not so much on statistical modeling approaches in order to determine a threshold for the decision making of the damage detection system. In this study, the impedance-based structural health monitoring technique is used in a damage detection problem considering temperature variation effects. For this aim, three aluminum 2024-T3 plates were instrumented with small lead zirconate titanate patches close to their borders, and damage was introduced in the central position of the plates, with temperature ranging from −10°C to 60°C. This article proposes a method to statistically determine a threshold for damage detection purposes using concepts of statistical process control, as well as confidence intervals and normality tests in order to obtain a diagnosis with a previously determined confidence level. Thus, this work presents a sensitivity evaluation of the impedance-based structural health monitoring technique as applied to aluminum plates under varying temperature. With the technique proposed, damage threshold levels are determined so that lead zirconate titanate patches placed approximately 280 mm from the damage inserted were able to detect saw cuts of approximately 7 mm long, with 95% confidence intervals inside the temperature range considered.