دورية أكاديمية

Effect of Signal Features and Model Variables on Energy-Traced Arrival Time Picking of Acoustic Signals Used for Structural Damage Detection.

التفاصيل البيبلوغرافية
العنوان: Effect of Signal Features and Model Variables on Energy-Traced Arrival Time Picking of Acoustic Signals Used for Structural Damage Detection.
المؤلفون: Tayfur, Sena1 sena.tayfur@ege.edu.tr
المصدر: Sakarya University Journal of Science (SAUJS) / Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi. Apr2024, Vol. 28 Issue 2, p249-258. 10p.
مصطلحات موضوعية: STRUCTURAL health monitoring, AKAIKE information criterion, ACOUSTIC wave propagation, CRACKING of concrete, ACOUSTIC emission, SIGNALS & signaling, SIGNAL-to-noise ratio
مستخلص: To monitor damage developments in structures, various structural health monitoring methods based on different principles are used. The common aspect of elastic wavebased methods is to place appropriate sensors on the structure, to detect acoustic wave propagation and to analyze these signals the sensors transformed. The arrival time of these recorded signals to the sensors is the most significant parameter used to determine critical information such as the time and location of the damage. Therefore, the accurate calculation of the arrival time affects the accuracy of the damage detection. In this study, effects of the signal-to-noise ratio (SNR), sampling frequency, length of the signal, and length of the focal window on determining the arrival time of the signals to the sensors were investigated. For this purpose, an energy-traced arrival time picking approach (Akaike Information Criterion, AIC), which is the frequently used method in the literature, has been applied to a typical acoustic signal originated from a concrete cracking. The results of the study suggest the necessity of noise elimination, the optimum level of data logging and the ratios of focal window lengths for accurate time of arrival detection in the field monitoring of the structures using acoustic methods. [ABSTRACT FROM AUTHOR]
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قاعدة البيانات: Business Source Index
الوصف
تدمد:13014048
DOI:10.16984/saufenbilder.1226036