Cross-correlation-based algorithm for absolute stress evaluation in steel members using the longitudinal critically refracted wave

Zuohua Li, Jingbo He, Jun Teng and Ying Wang

International Journal of Distributed Sensor Networks, 2018, vol. 14, issue 10, 1550147718803312

Abstract: The absolute stress in the in-service steel members is a critical indicator employed for the evaluation of structural performance. In the field of structural health monitoring, the stress is usually monitored by the stress monitoring system. However, the monitored stress is the relative value, rather than the absolute value. The longitudinal critically refracted wave has shown potential for use in absolute stress measurement. The accurate measurement of the longitudinal critically refracted wave time-of-flight is the core issue with this method. In this study, a cross-correlation-based algorithm is presented for stress evaluation using the longitudinal critically refracted wave. Specifically, a cross-correlation theoretical formula is derived and a five-step framework is proposed for the longitudinal critically refracted wave time-of-flight measurement. Four steel members are employed to investigate the parametric calibration using the longitudinal critically refracted wave to measure the stress. On this basis, the proposed cross-correlation-based algorithm is used to evaluate the stress of a steel member. The results indicate that the cross-correlation-based algorithm can measure the longitudinal critically refracted wave time-of-flight without filtering the noise signal, and the stress measurement results are better than those of the traditional peak value method. The proposed method provides a potential way to measure the absolute stress in practical engineering applications.

Keywords: cross-correlation-based algorithm; longitudinal critically refracted wave; absolute stress measurement; steel members; acoustoelasticity (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:14:y:2018:i:10:p:1550147718803312

DOI: 10.1177/1550147718803312

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