Nondestructive testing (NDT) technique has emerged as a valuable tool for detecting damage and evaluating the overall structural condition, leading to enhanced safety and optimized maintenance of large-scale structures. The acoustic emission (AE) approach is one of the powerful NDT techniques that can be suitable for damage detection due to its high sensitivity to localized damage. In this paper, an improved method based on empirical mode decomposition (EMD) and Shannon entropy (E) is proposed to localize the structural damage using AE sensors without considering any manual feature extraction of standalone AE parameters. EMD is first applied to eliminate the noise from the measured AE data and extract the key AE components, and then the E value of each AE component is estimated and used to identify the potential location of a crack in structural elements. The proposed method is validated using a suite of experimental studies and AE data obtained from a full-scale concrete dam located in Ontario, Canada. The results show the capability of the proposed method for identifying the approximate location of the damages and prove that the proposed method can be suitable for robust damage or crack localization.

无损检测（NDT）技术已成为一种用于检测损坏和评估整体结构状况的有价值的工具，从而提高了安全性并优化了大型结构的维护。声发射（AE）方法是强大的NDT技术之一，由于其对局部损伤的高度敏感性，因此可以适合于损伤检测。本文提出了一种基于经验模态分解（EMD）和香农熵（E）的改进方法来定位使用AE传感器的结构损伤，而无需考虑任何独立的AE参数的手动特征提取。首先应用EMD来消除测得的AE数据中的噪声并提取关键的AE成分，然后提取E估计每个AE组件的值，并将其用于识别结构元素中裂纹的潜在位置。提议的方法已通过一套实验研究和从位于加拿大安大略省的一座大型混凝土大坝中获得的AE数据进行了验证。结果表明，该方法能够识别损伤的大致位置，并证明该方法适用于鲁棒性损伤或裂纹局部化。