Infrared short-circuit detection for electrolytic copper refining
- R.M. Jia, X.L. Ma, W.Q. He
- Corresponding Author
- R.M. Jia
Available Online November 2016.
- https://doi.org/10.2991/aest-16.2016.113How to use a DOI?
- infrared images; short-circuit fault; copper electrolytic; pixel ordering PCA; SVM.
- This paper proposes an automatic detection method for short-circuit fault that based on the thermal radiation principle of infrared image. During copper electrolytic refining, short circuits between cathode and anode plates will lower the production efficiency. It is necessary to detect short circuits timely to reduce the electricity loss. Firstly, the positive and negative samples were collected that came from the infrared images segmentation of the electrolytic tank images. Then, pixel ordering PCA feature extraction algorithm is proposed to obtain the samples feature. Finally, SVM classifier is used to recognize the short circuits. Experiment results prove that the recognition rate based on proposed method is better than other algorithms, and this method has been applied in the electrolytic copper factory.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - R.M. Jia AU - X.L. Ma AU - W.Q. He PY - 2016/11 DA - 2016/11 TI - Infrared short-circuit detection for electrolytic copper refining BT - 2016 International Conference on Advanced Electronic Science and Technology (AEST 2016) PB - Atlantis Press UR - https://doi.org/10.2991/aest-16.2016.113 DO - https://doi.org/10.2991/aest-16.2016.113 ID - Jia2016/11 ER -