Structural health monitoring is extensively used in new and old structures. During the process of monitoring, a large amount of data is generated. The selection of the appropriate methodology for the analysis of these data constitutes a major problem for maintenance personnel. Therefore, the purpose of this study is to programme data according to the curvature mode and wavelet transform theory to achieve automatic identification of structural damage and explore its applicability. First, the damage model is established with finite element software, and the applicability of the theory is verified by analysing the wavelet coefficients before and after structural damage. Thereafter, a programme is written to achieve the automatic output of the structural damage location based on the finite element results and basic theory. Data fitting is then performed to estimate the degree of structural damage. To evaluate the effects of the practical application of the programme, experimental verification is conducted. The experimental results demonstrate that the programme can automatically output the damage location and avoid the occurrence of calculation errors.

中文翻译：

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基于曲率模态和小波分析理论的结构损伤智能识别

结构健康监测已广泛用于新旧结构中。在监视过程中，会生成大量数据。选择适当的方法来分析这些数据是维护人员的主要问题。因此，本研究的目的是根据曲率模式和小波变换理论对数据进行编程，以实现结构损伤的自动识别并探讨其适用性。首先，利用有限元软件建立损伤模型，通过分析结构损伤前后的小波系数，验证了该理论的适用性。此后，根据有限元结果和基本理论，编写程序以实现结构损伤位置的自动输出。然后进行数据拟合以估计结构破坏的程度。为了评估该程序的实际应用效果，进行了实验验证。实验结果表明，该程序可以自动输出损伤位置，避免了计算错误的发生。