紅外線熱影像檢測為一能快速且大範圍檢測材料內部缺陷之方法，故近年來已被廣泛應用於非破壞性檢測。
本文主要的研究目的為發展將紅外線灰階熱影像轉換成溫度場之方法，能在儲存電腦上之即時熱影像後，將電腦熱影像轉換成全面積溫度場。在實際量測上，即能達到快速取得全面積溫度值之功效。本研究共提出兩種轉換方法。轉換方法一為訊號轉換原理法，其分析過程分成兩大部分，第一部分先利用輻射理論與紅外線影像儀訊號轉換原理，模擬影像儀熱影像灰階值與溫度值之對應，並與實際結果比較，驗證其正確性。第二部分則分析傳輸至電腦上之熱影像與影像儀之熱影像，兩者灰階值的關係，得出一修正方法，以期將電腦熱影像透過修正之後，能近似於影像儀熱影像，結合上述兩個部分，便可以將電腦熱影像轉換成全面積溫度場。轉換方法二則為曲線擬合法，直接分析電腦熱影像灰階值與溫度值之關係，透過曲線擬合等方法，得出電腦熱影像灰階值與溫度值之最佳關係式，即可將電腦熱影像轉換成溫度場。而透過此兩種轉換方法求得之溫度值，與影像儀實際紀錄下之溫度值，在本研究設定之最大量測範圍內，其平均誤差皆在0.9%以下。
接著以逐步加熱法為基礎，建立一量測系統，實際檢測具有內部缺陷之鋁材及鐵材。由於本研究採用之紅外線影像儀，其自動儲存全面積溫度值功能之最快速率為3秒1張，而鐵材與鋁材為具有高傳導係數之材料，故加熱後其表面溫度變化相當快，因此相較於影像儀自動存檔功能，採用本研究提出之方法便能較精準繪出待測試件上各點之溫度變化曲線，對於熱量抵達缺陷平面之時間判斷能有較高之準確度。

Infrared thermography is a method that can detect the defect inside materials in wide range rapidly, so it is applied to non-destructive testing widely recent years.
In this research, the major purpose is to develop the method of converting the infrared gray thermal image into temperature field. It would convert computer’s thermal image into the whole area of temperature after save the real-time thermal image on the computer, so it can acquire the whole area of temperature rapidly in the practical measurement. We put forward two methods of conversion. Method one is signal conversion principle method, and it’s analytical process has two part, In part one, we use the theory of radiation and the principle of infrared camera’s signal conversion to simulate the relation between the gray level of infrared camera’s thermal image and temperature, and compare to the practical result to verify the correctness of simulation. Part two is to analysis the gray level’s relation between the infrared camera’s thermal image and the computer’s thermal image, and gets a method of modification, so we could modify the computer’s thermal image and let it similar to infrared camera’s thermal image. Combine two parts we mention, it can convert the computer’s thermal image into the whole area of temperature. Method two is curve fitting method, it analysis the relation between the gray level of computer’s thermal image and temperature directly, and find the best relationship between he gray level of computer’s thermal image and temperature by using curve fitting so that we can use the relationship to convert computer’s thermal image into temperature field. And in the widest measuring range we set, the average error between the temperature by using this two methods and the temperature record by infrared camera is under 0.9%.
Establishing a measurement system based on step heating and to detect the iron plate and the aluminum plate with defect inside. The fastest rate to save the whole area of temperature field automatically in the infrared camera we use is one frame in three seconds, and iron and aluminum both are the material with high conductivity so that the surface’s temperature would vary rapidly after heating, so use the method this research put forward can plot the curve of temperature variation more accurate compare to infrared camera’s auto save function, and it also can judgment the time that heat arrive the plane of defect accurately.

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