Civil structures suffer deterioration either for years of service, deficiency due to environmental factors or damages caused by factors such as earthquakes, winds, impact loads, and cyclical loads. When a structure ages, it is necessary to know its state of health and make a decision of maintenance or replacement. When a structure such as a bridge or building is subjected to destructive environmental forces, determining its state of health becomes a priority since its recovery is urgently required to function normally. Structural Health Monitoring (SHM) is a technology that aims to prevent the collapse of structures and loss of human life through early diagnosis of the health status of a structure. There are a large number of damage detection methods that can be classified into (1) non-destructive testing methods, (2) dynamic characteristics-based damage detection methods, (3) dynamic response-based, (4) multi-scale damage detection method and (5) damage detection methods with consideration of uncertainties. In this work, it is implemented synchrosqueezed wavelet transform (SWT), which can be classified as a methods based on the dynamic response. To validate the robustness of the method it is identified first, the natural frequencies of the Benchmark Phase I without damage, which consists of a steel structure of 4-story [Formula: see text] bay 3D steel frame structure subjected to ambient vibrations. Subsequently, some damage patterns are validated according to IASC-ASCE SHM Task Group. The results obtained in the identification of natural frequencies are compared with those reported in literature. SWT was efficient, presenting a minimum error of 0.12[Formula: see text] and a maximum of 3.06[Formula: see text] in the identification of natural frequencies about the AISCE-ASCE group model. SWT overcomes some other damage detection methods, which are deficient in the identification of closely spaced frequencies, commonly present in many civil structures due to symmetric geometry or similar physical properties in different directions.

中文翻译：

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在 IASC-ASCE 基准阶段 I 上使用同步压缩小波变换进行结构健康监测

土木结构在使用多年、环境因素造成的缺陷或地震、风、冲击载荷和周期性载荷等因素造成的损坏时都会遭受损坏。当结构老化时，有必要了解其健康状况并做出维护或更换的决定。当桥梁或建筑物等结构受到破坏性环境力时，确定其健康状态成为当务之急，因为迫切需要恢复其正常运行。结构健康监测 (SHM) 是一项旨在通过对结构的健康状况进行早期诊断来防止结构倒塌和人员伤亡的技术。损伤检测方法有很多，可分为（1）无损检测方法，(2)基于动态特性的损伤检测方法，(3)基于动态响应的损伤检测方法，(4)多尺度损伤检测方法和(5)考虑不确定性的损伤检测方法。在这项工作中，它实现了同步压缩小波变换（SWT），它可以归类为基于动态响应的方法。为了验证方法的稳健性，首先确定了基准阶段 I 的固有频率，没有损坏，它由 4 层钢结构 [公式：见文本] 隔间 3D 钢框架结构经受环境振动。随后，根据 IASC-ASCE SHM 任务组验证了一些损坏模式。将在识别固有频率中获得的结果与文献中报道的结果进行比较。SWT 是有效的，最小误差为 0。AISCE-ASCE群模型固有频率识别中的12[公式：见正文]，最大值为3.06[公式：见正文]。SWT 克服了其他一些损伤检测方法，这些方法在识别紧密间隔的频率方面存在缺陷，由于对称几何或不同方向的相似物理特性，这些方法通常存在于许多土木结构中。