Formation of hysteretic curve similarity indicators based on shape descriptors

Abstract

To develop comprehensive similarity indicators for assessing the fitting degree of hysteretic curves shape descriptors, widely used in image feature extraction, are introduced. A specific process is proposed to delineate the formation of indicators based on these descriptors, enabling the calculation of curve similarity between numerical simulation and experimental data. Following this process, an indicator is devised based on shape context. First, the similarities of the hysteretic loops in the numerical simulation curve are calculated. Subsequently, the weighted sum of these similarities is calculated to derive the similarity of the entire curve. To verify the effectiveness of the indicator, the Bouc-Wen model is utilized to conduct a numerical simulation study. Five parameters of the model are adjusted, resulting in the formation of 51 numerical simulation curves. Similarities of the curve, along with errors in the force peak point, energy dissipation, and stiffness, are calculated. The results show that the absolute values of Spearman’s correlation coefficients between similarity and errors all exceed 0.78, which has a strong correlation, thus verifying the feasibility of the indicator and the effectiveness of the process for forming the indicators.

Keywords

hysteretic curve / shape descriptor / shape context / Bouc-Wen model / curve similarity