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磁光成像自适应卡尔曼滤波焊缝跟踪算法

Seam tracking algorithm based on magneto-optical imaging and self-adaptive Kalmanfiltering

  • 摘要: 焊缝跟踪是保证焊接质量的前提.针对0~0.05 mm的微间隙焊缝,研究一种色噪声环境下应用卡尔曼滤波实现焊缝跟踪的方法.通过对焊件施加磁场,利用法拉第磁旋光原理构成磁光传感器并获取焊缝磁光图像,提取焊缝中心位置构成状态向量,建立基于焊缝中心位置的系统状态方程与测量方程.针对系统过程噪声为色噪声,使用Sage自适应卡尔曼滤波,采用新息序列估计过程噪声协方差矩阵,准确预测焊缝中心位置.结果表明,根据自适应卡尔曼滤波方法能够有效提高焊缝跟踪精度.

     

    Abstract: Accurate seam tracking is a prerequisite for laser welding with good quality. A seam tracking method based on Kalman filtering with colored noises is proposed to predict the seam deviationsin micro butt joint whose width is less than 0.05 mm. In the experiment, the weldments were magnetized by usingan excitation magnetic field. Meanwhile, a magneto-optical sensor based on the principle of Faraday magneto effect was applied to acquire the magneto-optical image of the weld joint. By analyzing the magneto-optical images of weld joint, the joint center position was extracted and defined as the state vector. Then the state equation and the measurement equation based on the weld joint center position were established. Considering that the system process noise was colored noise, the Sage adaptive filtering was used to lessen the noise influence.The innovation series was used to estimate the process noise variance matrix, and the weld joint position could be predicted accurately. Experimental results show that seam tracking accuracy can be improved effectively with self-adaptive Kalman filtering method.

     

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