Lin Tzu-Kang, Chien Yi-Hsiu
Department of Civil Engineering, National Chiao Tung University, Hsinchu 30010, Taiwan.
Entropy (Basel). 2019 Jan 9;21(1):41. doi: 10.3390/e21010041.
The aim of this study was to develop an entropy-based structural health monitoring system for solving the problem of unstable entropy values observed when multiscale cross-sample entropy (MSCE) is employed to assess damage in real structures. Composite MSCE was utilized to enhance the reliability of entropy values on every scale. Additionally, the first mode of a structure was extracted using ensemble empirical mode decomposition to conduct entropy analysis and evaluate the accuracy of damage assessment. A seven-story model was created to validate the efficiency of the proposed method and the damage index. Subsequently, an experiment was conducted on a seven-story steel benchmark structure including 15 damaged cases to compare the numerical and experimental models. A confusion matrix was applied to classify the results and evaluate the performance over three indices: accuracy, precision, and recall. The results revealed the feasibility of the modified structural health monitoring system and demonstrated its potential in the field of long-term monitoring.
本研究的目的是开发一种基于熵的结构健康监测系统，以解决在使用多尺度交叉样本熵（MSCE）评估实际结构损伤时观察到的熵值不稳定问题。采用复合MSCE来提高各尺度上熵值的可靠性。此外，利用总体经验模态分解提取结构的一阶模态，进行熵分析并评估损伤评估的准确性。创建了一个七层模型来验证所提方法和损伤指标的有效性。随后，在一个包括15个损伤案例的七层钢基准结构上进行了实验，以比较数值模型和实验模型。应用混淆矩阵对结果进行分类，并在准确性、精确性和召回率三个指标上评估性能。结果揭示了改进后的结构健康监测系统的可行性，并证明了其在长期监测领域的潜力。
