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安徽大学 电气工程与自动化学院
收稿日期:2012-12-24,
修回日期:2013-03-06,
网络出版日期:2013-06-20,
纸质出版日期:2013-06-15
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赵吉文 黄彪 王荔枝 吴红标. 基于图像求逆相位相关算法检测电机转子位置[J]. 光学精密工程, 2013,21(6): 1613-1620
ZHAO Ji-wen HUANG Biao WANG Li-zhi WU Hong-biao. Detection of motor rotor position based on image reversible phase-correlation algorithm[J]. Editorial Office of Optics and Precision Engineering, 2013,21(6): 1613-1620
赵吉文 黄彪 王荔枝 吴红标. 基于图像求逆相位相关算法检测电机转子位置[J]. 光学精密工程, 2013,21(6): 1613-1620 DOI: 10.3788/OPE.20132106.1613.
ZHAO Ji-wen HUANG Biao WANG Li-zhi WU Hong-biao. Detection of motor rotor position based on image reversible phase-correlation algorithm[J]. Editorial Office of Optics and Precision Engineering, 2013,21(6): 1613-1620 DOI: 10.3788/OPE.20132106.1613.
提出了一种基于图像测量技术的电机转子位置检测方法。利用高速面阵CCD相机连续拍摄转动状态的电机转子的端面图像帧序列,然后对采集的相邻两幅灰度图像进行极坐标变换和相位相关运算,得出转子的旋转角度值。由于所拍摄端面图像的纹理信息与相位相关运算的准确性有关,故对图像的纹理信息进行了逆行重构,以得出可使运算准确的图像,保证检测的准确性。为了提高检测效率,采用自适应方法完成图像的极坐标变换,即根据测量精度的要求确定图像的采样范围,从而减少了运算量。实验结果显示,运算结果的准确率为100%,并且测量可适应一定范围内的光照强弱变化。与直接进行极坐标变换的运算相比,运算耗时降低了50%以上,结果为电机转子的位置检测提供了可靠保障。
A detecting method for motor rotor position was proposed based on image measurement technique. Firstly
the image of motor rotor was taken by a high-speed area CCD ceaselessly when the motor was rotating; then every two collected adjacent images were converted from a Descartes coordinate to a polar coordinate; finally
these images in the polar coordinate were calculated by phase-correlation algorithm
and the rotation angle was obtained according to the position of the phase-correlation peak. As the texture information of calculated image was related to the accuracy of phase-correlation
the calculated image was reconstructed to obtain an image to assure the right calculated result for implementing exact detection. Meanwhile
detection efficiency was required to increase
so the adaptive method was used in polar transformation
namely
only part of the pixels in the image was sampled according to the need of measurement precision. Experimental results show that the measurement accuracy of the proposed method is 100% and this measurement can be achieved in the environment with some different illumination intensities. Moreover
the calculating time can be reduced by over 50% as compared with that using polar transformation directly. The proposed method provides a reliable way for the detection of motor rotors.
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