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Structural Damage Detection Using Time Domain Periodogram Analysis

机译：使用时域周期图分析的结构损伤检测

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Before the advent of computers, scientists used time domain periodogram analysis (TDPA) for analysis of phenomena described by time-dependent parameters. Famous examples of this approach include investigations of periodicities in Sun activity, analysis of annual rings of trees and deposits of clays in large lakes, both of which are indicators of climate variations. These periodicities found by TDPA were later confirmed using modern Fourier transform-based methods. Since the advent of the computer era and the fast Fourier transform, TDPA has been almost completely abandoned. In this work, we develop a computer-based TDPA algorithm and demonstrate its' utility for determining the existence (Level 1) of structural damage. First, the TDPA is compared to a frequency domain periodogram analysis for synthetic signals with well-defined statistical properties. This comparison elucidates the features of the TDPA algorithm. Next, a damage existence 'feature' is identified from the TDPA and is shown to be a reliable indicator of the existence of structural damage. This is demonstrated using simulated and actual experimental data.
机译：在计算机出现之前，科学家们使用时域周期图分析（TDPA）来分析由时变参数描述的现象。这种方法的著名例子包括对太阳活动周期性的调查，对年轮的分析以及大湖中粘土的沉积，这两者都是气候变化的指标。 TDPA发现的这些周期性后来使用基于现代傅立叶变换的方法得到了证实。自计算机时代问世和快速傅立叶变换以来，TDPA几乎已被完全废弃。在这项工作中，我们开发了一种基于计算机的TDPA算法，并演示了其在确定结构损伤的存在（级别1）方面的效用。首先，对于具有明确定义的统计特性的合成信号，将TDPA与频域周期图分析进行比较。此比较阐明了TDPA算法的功能。接下来，从TDPA中识别出损害存在的“特征”，并被证明是存在结构损害的可靠指标。使用模拟和实际实验数据证明了这一点。

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