Health Diagnosis Method of Power Distribution Equipment Based on Holographic Time-scalar Measurement Data
Bing Chen, Ren Wang, Yang Zhou, Chenhui Peng
Available Online June 2016.
- https://doi.org/10.2991/mecs-17.2017.32How to use a DOI?
- Holographic time-scalar measurement data, Realtime database, Deep integration, State diagnosis, Linear regression, Entropy method
- With the continuous expansion of the distribution network, resulting in a large amount of running data. The integration of Realtime Database and distribution network system make it prossible to record distribution holographic scalar measurement data. This paper studied the deep integration of Realtime Database and distribution network system. On the basis of integration, we studied health diagnosis method of power distribution equipment and we carry out in-depth data mining on the distribution history data and model information. The equipment state diagnosis model and the evaluation system are established by cluster analysis, linear regression algorithm and entropy method, and the equipment fault assessment and early warning analysis are realized. The weak links in distribution network can be found in time to ensure the safe and stable operation of the distribution equipment.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Bing Chen AU - Ren Wang AU - Yang Zhou AU - Chenhui Peng PY - 2016/06 DA - 2016/06 TI - Health Diagnosis Method of Power Distribution Equipment Based on Holographic Time-scalar Measurement Data BT - Proceedings of the 2017 2nd International Conference on Machinery, Electronics and Control Simulation (MECS 2017) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/mecs-17.2017.32 DO - https://doi.org/10.2991/mecs-17.2017.32 ID - Chen2016/06 ER -