Proceedings of the 2016 International Conference on Computer Science and Electronic Technology

Research of Electrical Equipment State Identification Based on K-means Clustering Algorithm

Authors
Liting Lei, Hui Xu, Rongrong Fan
Corresponding Author
Liting Lei
Available Online August 2016.
DOI
https://doi.org/10.2991/cset-16.2016.46How to use a DOI?
Keywords
Electrical equipment, on-line monitoring, current signal, clustering algorithm, state recognition
Abstract
For the current heavy manual monitoring work and frequent failure of electrical equipment, an online monitoring scheme for equipment state based on current sensor, WIFI communication module and embedded development board is designed. K-means clustering algorithm is used to analyze the current data set collected from different working status of the equipment, and the corresponding characteristic value is obtained. And then the automatic identification of the equipment working status is realized. The experimental results show that this method can quickly recognize the equipment operation status with high accuracy, and working stability.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2016 International Conference on Computer Science and Electronic Technology
Part of series
Advances in Computer Science Research
Publication Date
August 2016
ISBN
978-94-6252-213-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/cset-16.2016.46How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Liting Lei
AU  - Hui Xu
AU  - Rongrong Fan
PY  - 2016/08
DA  - 2016/08
TI  - Research of Electrical Equipment State Identification Based on K-means Clustering Algorithm
BT  - 2016 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/cset-16.2016.46
DO  - https://doi.org/10.2991/cset-16.2016.46
ID  - Lei2016/08
ER  -