Accurate rotation identification of flexural structures using long-gauge fiber optical sensors

Abstract

The rotation of beam and column components is a key parameter in structural health monitoring (SHM), which providing analysis of bending deformation, evaluation of structural stability, and overall structural performance. Conventional sensors directly measuring rotation are typically designed assuming linear behavior. It becomes challenging to achieve precise and rapid measurements of small deformations while accurately measuring significant large deformations. This study obtained experimental and analytical studies to identify the rotation response of flexural structures using long-gauge fiber optical sensor array. Rotation is determined through two mechanisms: the plane section assumption, utilizing strain distributions on the compression and tension sides, and the sectional fiber model (SFM)-based neutral axis identification. In order to discuss the applicability of these two mechanisms from elastic to plastic state, four identification methods are proposed: Method 1 uses strain distribution on the concrete surface to identify rotation, Method 2 uses strain on steel bars, and Methods 3 and 4 use SFM-based neutral axis identification with strain measured on the compression side concrete surface and tension side steel reinforcements, respectively. Laboratory tests of beams and columns as well as field tests were shown. First, a comparison of the rotation identification accuracy among the four methods was conducted using a reinforced concrete (RC) beam test in the elastic state. Results showed good agreement between the rotations identified by all four methods and those directly measured by the tilt meter. And then, the accuracy of rotation identification in crack state and inelastic state was discussed by using a RC column test. The results indicate that, following the occurrence of cracks in concrete surface, neither Method 1 nor Method 2 can accurately identify the rotation. This is attributed to the fact that cracks disrupt the correspondence between the strain on the tension side and the compression side. Meanwhile, Methods 3 and 4 maintain a good rotational identification accuracy even after cracks happened. Moreover, when the steel reinforcement undergoes yielding and the concrete column enters the inelastic state, the rotation results identified by Methods 3 and 4 still match with the directly measured rotations. This underscores the effectiveness of the SFM-based rotational identification under large deformation conditions. Furthermore, experimental results indicate that with the increase in deformations, slip occurred in the sensing units near the column base in the sensor array on the tension side. This shows that the sensing units installed on the steel reinforcement (Method 4) are more suitable for calculating rotations during the large deformation state compared to the sensing units positioned on the concrete surface (Method 3). At last, two case studies involving the monitoring of an actual bridge grid and a bridge column were investigated to assess the effectiveness of dynamic rotation identifications. The performance evaluation results for various rotation angle measurement sensors demonstrate that long-gauge fiber optical sensors can be used for rotation identification, ensuring the stability of dynamic rotation identification.