A SOI-EKF strategy for fault diagnosis in insulation system of marine current turbine
| Autor: | E. Schaeffer, Tianzhen Wang, Liu Lei, Milu Zhang, Haojun Ji |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Engineering business.industry Marine current power 020208 electrical & electronic engineering 02 engineering and technology Fault (power engineering) Turbine Extended Kalman filter 020901 industrial engineering & automation Control theory Insulation system 0202 electrical engineering electronic engineering information engineering RLC circuit Sensitivity (control systems) Observability business |
| Zdroj: | 2016 IEEE 8th International Power Electronics and Motion Control Conference (IPEMC-ECCE Asia). |
| DOI: | 10.1109/ipemc.2016.7512597 |
| Popis: | Marine current power is a new energy source, so it is significant for the fault diagnosis of the marine current turbine, especially the winding insulation system. In this paper, a SOI-EKF strategy was proposed to monitor the health state of the winding insulation system. This strategy includes mainly two parts. At first, a New Branch RLC Model is extracted from Roebel bars of the winding insulation system. The New Branch RLC Model can be used for parameter identification to study the mechanism of fault diagnosis. Meanwhile, observability analysis and sensitivity analysis are studied about the New Branch RLC Model. And then based on the continuous Extended Kalman Filter, an efficient real-time monitoring SOI-EKF method is proposed for the New Branch RLC Model. The SOI-EKF method can obviously reduce the error in the simulation. The SOI-EKF strategy can realize real-time online monitoring for the winding insulation system. Simulation experiments demonstrate the feasibility of the proposed strategy. And some simulation results are compared with the experimental results in this paper. |
| Databáze: | OpenAIRE |
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