Multisensory data fusion technique and its application to welding process monitoring

Zhifen Zhang; Guangrui Wen; Shanben Chen

doi:10.1109/ARSO.2016.7736298

Multisensory data fusion technique and its application to welding process monitoring

Zhifen Zhang
, Guangrui Wen
, Shanben Chen

School of Mechanical Engineering

Shanghai Jiao Tong University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

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.

Original language	English
Title of host publication	2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016
Publisher	IEEE Computer Society
Pages	294-298
Number of pages	5
ISBN (Electronic)	9781509040773
DOIs	https://doi.org/10.1109/ARSO.2016.7736298
State	Published - 4 Nov 2016
Event	2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016 - Shanghai, China Duration: 7 Jul 2016 → 10 Jul 2016

Publication series

Name	Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO
Volume	2016-November
ISSN (Print)	2162-7568
ISSN (Electronic)	2162-7576

Conference

Conference	2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016
Country/Territory	China
City	Shanghai
Period	7/07/16 → 10/07/16

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10.1109/ARSO.2016.7736298

Cite this

Zhang, Z., Wen, G., & Chen, S. (2016). Multisensory data fusion technique and its application to welding process monitoring. In 2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016 (pp. 294-298). Article 7736298 (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO; Vol. 2016-November). IEEE Computer Society. https://doi.org/10.1109/ARSO.2016.7736298

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title = "Multisensory data fusion technique and its application to welding process monitoring",

abstract = "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.",

author = "Zhifen Zhang and Guangrui Wen and Shanben Chen",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016 ; Conference date: 07-07-2016 Through 10-07-2016",

year = "2016",

month = nov,

day = "4",

doi = "10.1109/ARSO.2016.7736298",

language = "英语",

series = "Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO",

publisher = "IEEE Computer Society",

pages = "294--298",

booktitle = "2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016",

}

Zhang, Z , Wen, G & Chen, S 2016, Multisensory data fusion technique and its application to welding process monitoring. in 2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016., 7736298, Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO, vol. 2016-November, IEEE Computer Society, pp. 294-298, 2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016, Shanghai, China, 7/07/16. https://doi.org/10.1109/ARSO.2016.7736298

Multisensory data fusion technique and its application to welding process monitoring. / Zhang, Zhifen ; Wen, Guangrui; Chen, Shanben.
2016 IEEE Workshop on Advanced Robotics and its Social Impacts, IEEE ARSO 2016. IEEE Computer Society, 2016. p. 294-298 7736298 (Proceedings of IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO; Vol. 2016-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

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Multisensory data fusion technique and its application to welding process monitoring

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