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    Title: 溫度效應之陀螺儀漂移與補償研究
    Other Titles: A study on the gyro’s null drift and compensation for temperature variations
    Authors: 黃辰宣;Huang, Chen-xuan
    Contributors: 淡江大學航空太空工程學系碩士班
    蕭照焜
    Keywords: 陀螺儀漂移;溫度補償;類神經網絡;gyroscope drift;temperature compensation;artificial neural networks
    Date: 2010
    Issue Date: 2010-09-23 17:50:54 (UTC+8)
    Abstract: 本文探討溫度效應對微機電陀螺儀漂移之影響,同時探討溫度補償之方法及效益。首先研究中利用自製之慣性量測組件執行溫度效應試驗,將慣性量測組件置於溫度控制箱內,控制溫度變化由25oC以每分鐘約0.8度的速度上升至80oC後,再下降至-40oC,最後再回升到25oC,完成一次試驗,在試驗過程中即時的量取溫度及靜態的陀螺儀輸出,以觀察溫度變化時的陀螺儀漂移現象。結果清楚顯示溫度對陀螺儀角速度零輸出電壓之影響。量測信號雜訊的特性在本研究裡也做了詳細的分析與討論。溫度補償分析方面,研究中將實驗數據利用類神經網絡之學習訓練,建立溫度與陀螺儀角速度零輸出電壓關係之類神經網絡及補償法則,最後驗證經由溫度補償後,可有效的提高飛行姿態角計算的精確度與實用性。
    This paper discusses the MEMS gyro’s null drift, due to temperature variations, and the null drift calibration. An experiment to determine the null drift is conducted by using a temperature controlled chamber. The temperature is controlled to start from 25oC, and then increased to 80oC with an incremental rate of 0.8oC/min. After that, the temperature is decreased to -40oC. Finally, the temperature is increased back to 25oC to complete a test cycle. The temperature and null voltage for all axes are recorded. The test results clearly show the temperature influence on the gyro null drift. Noise characteristics of the measured signals are analyzed and discussed in detail in the study. A temperature calibration mechanism is established by using a neural network model. With the temperature calibration, the attitude computation problem due to gyro drifts can be improved significantly.
    Appears in Collections:[航空太空工程學系暨研究所] 學位論文

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