基于卡尔曼滤波的焊缝检测技术研究

提出一种基于卡尔曼滤波技术的电弧焊焊缝检测新方法。利用视觉传感器获取弧焊区熔池图像,并抽取图像质心作为描述焊缝位置的特征矢量,建立图像质心状态方程和测量方程。在有色噪声模型的基础上,应用卡尔曼滤波对图像质心位置和质心位移进行状态估计,得到最小均方差条件下的焊缝位置最佳预测值,从而减小过程噪声和测量噪声引起的焊缝位置测量偏差,实现弧焊过程中焊缝位置的精确检测。计算机仿真及实际焊接试验结果验证了该方法的有效性。

STUDY ON THE WELD DETECTION USING KALMAN FILTERING

The application of Kalman filtering for the weld detection in the arc welding process is presented. A Kalman filter is applied for processing the arc weld pool images from a visual sensor to recursively compute the solution to the weld position equations which are established based on an estimation of the position and displacement of the centroid of the weld pool images. This centroid whose characteristic corresponds with the weld position is extracted as the weld measurement eigenvector. The evolution of the weld position data from the weld pool images can be described through a state equation and a measurement equation of the image centroid. Based on a color noise model, the advantages of Kalman filtering over least squares approaches is taken to estimate the weld feature location on the image plane at the next sampling time and reduce the weld measurement error caused by the process and sensor noises. Computer simulations and actual welding experiments are demonstrated the effectiveness of the proposed algorithm in the presence of weld pool image noise and are tested the ro- business of weld position detection.