碳纖維複合材料補強工法是當前補強方法的新趨勢,碳纖維複合材料具有:1.具有高抗拉強度,2.質量輕,3.施工容易且需要之週邊設備少,4.運輸與儲存方便,5.剪裁及造型容易且連續性佳等優點,然而修補的成敗與否取決於結構體與補強材料間之黏結強度,應用紅外線影像可評估施工時所產生的黏結不完全、褶皺、氣泡等瑕疵。利用層集多重分類法可以有效進行影像分割,將相近數值分成同一個區域,進而求得缺陷區域與周圍環境區域之溫度差異,再根據ASTM規範D4788-03中利用紅外線溫度記錄法探測橋面分層的試驗方法,判斷該區域是否為缺陷,與本研究所預埋缺陷做比較,在熱源充足情況下所得結果與規範一致。
This paper utilizes the multilayer level set method for identification of surface defects within a material, through the examination of temperature variations within the material. Even though several image processing techniques have been proposed and applied to thermal images for non-destructive detection of surface defects, efficient and accurate detection of locate surface defects from thermal images is difficult. Mumford and Shah proposed to divide an image in a set of homogeneous sub-regions such that the energy contained in the image can reach its minimization. Based on this minimization of the energy, the multilayer level set method implicitly presents the regional boundaries as several nested level lines. By increasing iterations and preselected level values, these lines evolve close to the level boundaries based on the energy minimization. In this paper, we design an experiment in which the artificial defectors are buried behind and near the surface of a structure covered with Carbon Fiber Reinforced Plastic (CFRP). Then, a set of halogen lights are used to heat the structure. A thermal camera with temperature resolution 0.1 degrees Celsius is employed to record the temperature changes. The experimental results show that, according to the predefined level values, the multilayer level set method can successfully detect the regional boundaries of the buried defects by isolating the temperature changes within their neighborhoods from the given infrared thermal images.