Details

Autor(en) / Beteiligte

• Zhifen Zhang
• Guangrui Wen
• Shanben Chen

Titel

Multisensory data fusion technique and its application to welding process monitoring

Ist Teil von

• 2016 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), 2016, p.294-298

Ort / Verlag

IEEE

Erscheinungsjahr

2016

Quelle

IEEE/IET Electronic Library (IEL)

Beschreibungen/Notizen

• Multiple sensors of various source have been increasingly applied into different civilian situations as well as robotic welding process monitoring. How to take full advantage of these information, more importantly, scientifically fusion multisensory data for the specific application system may be of great challenge. In this paper, different sensing technique used for real-time welding quality monitoring were briefly reviewed and discussed in terms of their ability for implementation of data fusion system. Then, a feature-level data fusion application case of aluminum GTAW condition monitoring will be given with thoroughly discussion. This paper will provide some guidance for implementation of fusion system for process monitoring and defect detection.