Abstract: Welding automation is a crucial way towards “digitalization” and “intelligentization” of welding technology in 21st century.Welding automation can be realized with the premise of automatic, fast and accurate tracking the welding seam. Before the emergence of automatic welding technology, conventional welding operations were manually conducted. However, there are certain insufficiencies of manual monitoring and tracking of welding. On one hand, the harsh environment of welding work will do harm to the health of workers. On the other hand, the welding quality cannot be guaranteed under the long-term labor intensity brought by track and monitor welding process. The modern welding seam tracking technology is gradually getting rid of artificial interference, turning to sensors, computer processing and automatic welding process by actuators. Sensor is regard as the “sensory organ” of the weld tracking system, and the system completely relies on sensors to perceive the external welding environment and determine the relative position of welding torch and seam. meanwhile, welding environment is often accompanied with various noise, spatter, high-frequency radiation and so forth, which will obviously affect the signal acquisition and even cause an error of judgment on the position of welding seam. Hence, for the sake of acquiring satisfactory data, it has become an urgent need for welding seam tracking technology to employ appropriate welding sensing approach and process the acquired signals accurately and quickly. Generally, welding seam tracking sensors can be classified into direct sensors (arc sensors) and indirect sensors. In recent years, certain development have been made for both types of sensors. For instance, the application of magnetic-control arc sensors provides a new research direction for welding seam tracking, and indirect vision sensors are stepping their way to miniaturization and simplification. moreover, the emergence of multi-sensor information fusion technology creates a possibility to overcome the insufficiency in accuracy of single sensor. Besides, the signal processing technology can boost the signal-to-noise ratio, which paves the way for obtaining accurate information of seam position. The electrical signal filtering technology is changing gradually from a simple hardware filter to a software filter and combined filtering method. Concerning image processing technology, the anti-interference ability of image has been improved, yet further research should be conducted on the accuracy, real-time performance and reliability of welding seam identification. In this article, we systematically introduce the sensing approaches applied in seam tracking process, and put emphasis on the detailed classification and characteristics of the mainstream arc sensors and visual sensors. Additionally, we summarize the development status of crucial arc sensing signal filtering technology and essential visual sensing image processing technology. Finally, we point out the future directions of welding seam tracking.
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