應用交叉取樣熵於多跨三維結構之健康診斷評估

Abstract

本研究以多尺度交叉取樣熵分析(Multi-Scale Cross-sample Entropy, MSCE)為基礎，研發可使用在多跨三維結構進行損傷位置判斷之健康診斷系統。透過MSCE的計算，可分析各垂直相鄰樓層間訊號的差異性，並藉此得到每跨的破壞位置，再對其結果以破壞指數呈現。 本研究接著利用七層樓多跨結構模型之數值分析，驗證所提出的結構健康診斷方法，並根據所得結果，可以成功分辨出破壞樓層及該樓層破壞方位。最後，此破壞指數結果可初步評估其破壞跨度的所在位置。本研究驗證此健康診斷方法具有一定的可行性，同時能夠快速且低成本地分析複雜結構的破壞位置，是一個擁有高度潛力的診斷方法。

A structural health monitoring (SHM) system based on multi-scale cross-sample entropy (MSCE) is proposed in this work to detect damage locations in multi-bay three-dimensional structures. The location of damage is evaluated for each bay through MSCE analysis by examining the degree of dissimilarity between the response signals of vertically adjacent floors. Subsequently, the results are quantified by the damage index (DI). The performance of the proposed SHM system was determined by conducting a numerical simulation on a multi-bay seven-story structure. According to the results obtained, the SHM system used in this work can successfully detect the damaged floors and their respective directions for several cases. Furthermore, it provides a preliminary assessment as to which bay has been more severely affected. Thus, the effectiveness and high potential of the SHM system for locating damage in large and complex structures quickly and at low cost is demonstrated.