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Abstract: 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 robustness of weld position detection.
Key words: Weld
detection Kalman filter State estimation Weld pool image
CLC No: TM206.3
国家自然科学基金(60375012)、广东省自然科学基金(020176)和韩国21世纪创新项目基金资助项目.
Received 30411, received in revised form 20030909
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