考量結構反應量測為基礎之全域與局部特徵解析

Vibration-based Structural Identification:Global and Local Dynamic Characteristics

詹淳凱(Chun-Kai Chan)

指導教授 ： 羅俊雄

國立臺灣大學/工學院/土木工程學研究所/碩士(2015年)

https://doi.org/10.6342/NTU.2015.01213

摘要

本研究的目的在於分析結構物的反應訊號，經由適當的訊號處理工具識別後，了解結構物之行為與變化甚至是判定破壞的發生，即為結構健康監測之宗旨(Structural health monitoring)。現今健康監測與損壞識別使用大量儀器以獲取結構物全域或局部之反應，但會受限於現地裝設困難以及設備昂貴等限制，舉凡位移計，受到實地裝設限制，無法得知結構物受到地震力之位移反應。
因此本研究使用各種訊號處理及系統識別之方法，透過量測到之反應，獲取其系統之特徵，進而將結構物之全域與局部上的行為進行聯結。本文中使用了：(1) Hilbert transform, (2) wavelet packet transform, (3) principal component analysis, (4) singular spectrum analysis, (5) system identification using multi-variant autogressive model. 在介紹各個訊號處理方法後，將以兩種試體為例進行振動台試驗，來進行驗證，試體分別為一層樓雙跨的鋼筋混凝土構架，以及三層樓的鋼構架，並架設加速度計、位移計以及光學位移量測系統，其中加速度計與位移計可量測到結構全域之行為，而光學量測系統可設置於使用者較關注之細部結構，以獲取其局部行為。由分析結果顯示，本文所提出之方法可以識別出結構物之全域與局部特徵，其中全域特徵包含：波傳效應而引起之相位差、自然頻率與阻尼識別、時變頻率識別，及透過加速度歷時來預測位移歷時。而透過光學量測系統獲取之局部特徵包含：柱子之局部應變、變形曲率以及應力分布識別，進而與全域行為進行關聯。本文中所提出之技術將有助於簡化結構健康檢測之硬體設置，並使分析者能夠獲得更多結構特徵之資訊。

關鍵字

結構健康監測 ； 系統識別 ； 小波包轉換 ； 奇異譜分析 ； 向量自迴歸模型 ； 永久變位

並列摘要

In civil engineering, health monitoring and damage detection are mostly carried out using a dense array of sensors. Typically, most methods require global measurements to extract the properties of structures. However, some sensors such as linear variable differential transformers (LVDTs) cannot be used due to in situ limitation. Thus the global deformation remains unknown. Therefore, it is necessary to develop algorithms to identify the physical features such as permanent deformation for structural health monitoring. In this study, signal processing techniques and nonlinear identification methods are used and applied to the responses of test specimens subjected to different level of earthquake excitations. Both modal-based and signal-based system identification and feature extraction techniques are used to study the nonlinear inelastic response of the test specimens using both input and output response data or output only measurement. From the signal-based feature identification method, which include: (1) enhancement of time-frequency analysis of acceleration responses, (2) Hilbert marginal spectrum, (3) estimation of permanent deformation using directly from acceleration response data, (4) instantaneous phase difference, and (5) damage indices. For the modal-based system identification method, structural system parameters are identified, which include: (1) natural frequency, (2) damping ratio, and (3) modes shape. The extracted features are used to compare with the local information measured from the optical sensors. For the local measurements, some physical features are extracted, which include: (1) strain time history, (2) curvature time history, and (3) stress distribution. Two experiments are used to demonstrate the proposed algorithms: a one-story two-bay reinforce concrete frame and a three-story steel frame under weak and strong seismic excitation. The analysis results show that the identified global features are related to the local features and the proposed methods are capable for system identification and damage detection.

並列關鍵字

structural health monitoring ； seismic response processing ； wavelet packet transform ； singular spectrum analysis ； multivariate autoregressive model ； permanent deformation

參考文獻

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