基于BP神经网络的光电测量系统畸变校正
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Distortion correction for photoelectric measuring system based on BP neural network
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    摘要:

    在大视场光电测量系统中,由于光学系统畸变的影响使得目标在线阵CCD上的成像偏离了理论成像点,导致系统产生测量误差,为了提高测量精度,必须进行畸变校正。根据畸变光学原理,利用BP神经网络对非线性畸变进行良好的逼近,通过对由畸变测量装置获得的数据进行训练建立网络模型,从而建立整个视场畸变校正的数学模型。实验结果表明,当目标物高为200.115 mm时,利用BP神经网络方法,可将畸变误差从校正前的-2.080 mm提高到校正后的-0.104 mm,使得整体检测精度从1.039%提高到0.052%。

    Abstract:

    In the big visual field photoelectric measuring system,distortion produced by optical system makes the image of objects on the linear CCD deviate from the theoretical point and lead to the system measuring error.In the practical measuring system,in order to improve measurement precision,distortion correction is necessary.According to optical theory of distortion and utilizing BP neural network to approach nonlinear distortion,distortion correction mathematic model of whole field was set up through training the distortion measurement data which were measured by distortion detection device.This device has eleven equidistance points of laser goals and is designed based on the basis of distortion mechanism and radical character.The distortion correction method based on BP neural network can realize high precision of correction without knowing the mathematic model.The experiment result shows that the device can reduce error obviously from -2.08 mm to -0.104 mm according to the BP neural network correction when the object height is 200.115 mm,and raise the whole systematic detection precision from 1.039% to 0.052%.

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柏旭光,蔡盛,高峰端,乔彦峰,戴明.基于BP神经网络的光电测量系统畸变校正[J].激光与红外,2010,40(1):79~82
BAI Xu-guang, CAI Sheng, GAO Feng-duan, QIAO Yan-feng, DAI Ming. Distortion correction for photoelectric measuring system based on BP neural network[J]. LASER & INFRARED,2010,40(1):79~82

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