Abstract
High-strength bolts often served as critical prestressed connection components in large structures. If the bolt’s tension loss remains undetected, it may pose a significant threat to structural safety. This article presents a novel smart washer sensor, featuring a unique sensitivity-enhanced structure that significantly improves the measurement accuracy. The sensor consists of three vertically stacked ring-shape parts. The middle part has concave shapes on its top and bottom surfaces, which tightly contacts with the convex surfaces of the bottom and top parts of the sensor. When subjected to compression force from the bolt, the top and bottom parts will transfer a large amount of horizontal expansion force to the middle part through their contact surfaces, leading to the circumferential elongation of the middle part. This deformation is measured by fiber Bragg grating strain gauges. Comprehensive theoretical and numerical simulation research are conducted to examine how the sensor’s design parameters affect the important performance metrics of the sensors, such as sensitivity, measurement range, and linearity. It was found that due to the existence of friction force on the contact surfaces between the middle and the top/bottom parts, the sensor will behave slight differently during loading and unloading processes. To address this issue, a piecewise model is proposed, which greatly improves the accuracy of the bolt’s tension measurement during both loading and unloading processes. Finally, a prototype washer sensor with measurement range of 600 kN is designed, fabricated and tested. The experimental results demonstrate that the sensor can very accurately measure the bolt’s tension force, achieving a mean absolute error of only around 3 kN. The above results of theoretical analysis, numerical simulation, and experiments validate that the novel sensitivity-enhanced structure proposed herein endow the washer sensor with excellent characteristics of small dimension, large measurement range, and high measurement accuracy.
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