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Open AccessArticle

Self-Sensing Nonlinear Ultrasonic Fatigue Crack Detection under Temperature Variation

1
Department of Civil and Environmental Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea
2
Department of Architectural Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(8), 2527; https://doi.org/10.3390/s18082527
Received: 22 June 2018 / Revised: 25 July 2018 / Accepted: 31 July 2018 / Published: 2 August 2018
(This article belongs to the Section Physical Sensors)
This paper proposes a self-sensing nonlinear ultrasonic technique for fatigue crack detection under temperature variations. Fatigue cracks are identified from linear (α) and nonlinear (β) ultrasonic parameters recorded by a self-sensing piezoelectric transducer (PZT). The self-sensing PZT scheme minimizes the data acquisition system’s inherent nonlinearity, which often prevents the identification of fatigue cracks. Also, temperature-dependent false alarms are prevented based on the different behaviors of α and β. The proposed technique was numerically pre-validated with finite element method simulations to confirm the trends of α and β with changing temperature, and then was experimentally validated using an aluminum plate with an artificially induced fatigue crack. These validation tests reveal that fatigue cracks can be detected successfully in realistic conditions of unpredictable temperature and that positive false alarms of 0.12% occur. View Full-Text
Keywords: fatigue crack detection; ultrasonic nonlinearity; self-sensing; linear and nonlinear parameters; temperature variation; structural health monitoring; nondestructive evaluation fatigue crack detection; ultrasonic nonlinearity; self-sensing; linear and nonlinear parameters; temperature variation; structural health monitoring; nondestructive evaluation
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Kim, N.; Jang, K.; An, Y.-K. Self-Sensing Nonlinear Ultrasonic Fatigue Crack Detection under Temperature Variation . Sensors 2018, 18, 2527.

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