Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)

The Study of Control Strategy for Bolt Tightening Robot on Power Transmission Lines

Authors
Liqiang ZHONG, Shaosheng FAN, Ruoyun LI, Di YANG
Corresponding Author
Liqiang ZHONG
Available Online July 2017.
DOI
https://doi.org/10.2991/eia-17.2017.64How to use a DOI?
Keywords
sensor fusion; kalman filter; least square method; interest area; infrared detection; torque coefficient control
Abstract

A new control strategy and its real-time implementation were presented for a power transmission line bolt tightening robot. In order to overcome the influence of the wind, a prediction algorithm of multi-sensor information fusion optimal Kalman filter is adopted to predict the trajectory of the camera. The trajectory of the bolt uses a least squares method based on the interest area. Torque coefficient control method was presented to assure the conformity of the pre-tightening force of different screw threads. Experimental results show that the proposed boltÿaligning and tightening strategy can achieve the work timely and have highÿefficiency.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
Series
Advances in Intelligent Systems Research
Publication Date
July 2017
ISBN
10.2991/eia-17.2017.64
ISSN
1951-6851
DOI
https://doi.org/10.2991/eia-17.2017.64How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Liqiang ZHONG
AU  - Shaosheng FAN
AU  - Ruoyun LI
AU  - Di YANG
PY  - 2017/07
DA  - 2017/07
TI  - The Study of Control Strategy for Bolt Tightening Robot on Power Transmission Lines
BT  - Proceedings of the 2017 International Conference on Electronic Industry and Automation (EIA 2017)
PB  - Atlantis Press
SP  - 294
EP  - 300
SN  - 1951-6851
UR  - https://doi.org/10.2991/eia-17.2017.64
DO  - https://doi.org/10.2991/eia-17.2017.64
ID  - ZHONG2017/07
ER  -