本文使用高速攝影機做為數據收集系統，以收集運轉中系統的振動訊息。原系統之數據收集的方式，是將每張影像圖的特定點周圍的一個區域內之所有像素上的灰階值作累加，當作該影像之瞬間數據。攝影機所拍攝的一序列影像圖可以轉換成一組時間序列的時變數據。經由使用快速疊代型率波器移除時變數據串中的趨勢線後，再利用傅立葉正弦頻譜產生器求取其頻譜。本文的主題是比較灰階值累加區域為正方形或三角形區域，而且計算法是平均值法和數據偏差值兩種不同方式，以得到四種灰階值數據。本文分析結果顯示：使用三角型區域的灰階平均值計算法最為可靠，而正方形區域的灰階平均值計算法略差。但四種計算法都沒有完美的表現，所以應該互補之。四種計算法都顯示，捕捉輸入主倍頻和大樓振動主倍頻的能力，會隨著焦距和距離之差異的增加而劣化。本文並討論直昇機振動數據收集之應用，物理主頻和倍頻的捕捉能力並無因聚焦略為不良而有損傷，但折疊頻的捕捉能力則因聚焦不良而明顯下降。這些實驗數據同時也顯示，即使在高速攝影機鏡頭失焦嚴重時，只要能對最重要的輸入主頻之捕捉，還是可以透過頻譜數據互補的方式圓滿成任務。

From an image frame taken from a high speed camera, this study sums up all the gray levels within a square or a triangle and subsequently calculating the mean and sample deviation so that 4 types of data are obtained. The original system sums all the gray levels of pixels within a square as the vibration signal of the image frame and then obtains a time series. After removing the trend, the gray level value is accumulated to be a time series and evaluate the Fourier sine spectrum. The data evaluation shows that the mean within a triangular region is the best method and the mean within a square is the worst one. Since no one is perfect, one has better to consider resulting spectra of these four methods of evaluating data simultaneously. This study also applies this data acquisition system to examine the vibration signal of a small electronic remote control helicopter in operation. By slightly deteriorating the focusing, the capability of capturing the fundamental and physical harmonics via any method of calculating the gray level data is not affected. On the other hand, the system can not reflect the aliased mode as the focusing is not perfect. These experimental data also show that, even in high-speed camera lens out of focus serious, the image data acquisition system can be an effectively complementary tool to most current data acquisition systems in practical applications.

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