色噪声下卡尔曼滤波磁光成像焊缝跟踪算法

Kalman filtering algorithm with colored noise for seam tracking based on magneto-optical imaging

焊缝跟踪是保证激光焊接质量的前提,在激光焊接过程中,精确地识别和跟踪焊缝非常重要。以紧密对接平板激光焊为试验对象,研究一种色噪声环境下应用卡尔曼滤波最优状态估计对焊缝偏差进行预测的方法。使用磁光传感器摄取焊缝磁光图像并提取焊缝位置参数,建立基于焊缝位置参数的系统测量方程和状态方程。应用扩展状态向量的方法建立色噪声环境下的卡尔曼滤波算法,对焊缝位置进行最优状态估计,得到均方差极小值情况下的焊缝偏差预测最优值,减小系统噪声对焊缝位置识别的影响。试验结果表明所提方法可以显著提高焊缝跟踪的准确性。

Seam tracking is prerequisite for laser welding quality. It is very important to accurately detect weld position and track the weld path in laser welding process. For micro butt-joint laser welding of two low carbon steel plates,an approach is investigated to estimate the seam offset by using the Kalman filtering optimal state estimation under the colored noise environment. A magneto-optical sensor based on the principle of Faraday magneto effect is applied to acquire the magneto-optical images of welds. The weld position parameters can be extracted by using image processing techniques. The state-equation based on the weld position parameters and the measurement-equation for the weld position is established. A Kalman filtering algorithm under colored noise environment is developed by augmenting the state vectors to obtain the optimal seam offset prediction under the condition of minimum mean square error through the optimal state estimation of weld position. This algorithm can reduce the system noises interference influence.Experiment results show that the accuracy of seam tracking can be improved significantly by Kalman filtering algorithm.