Abstract
The abnormal rise in contact temperature in switchgear may lead to overheating or even explosion. It is necessary to monitor the rise in real contact temperature to ensure the safety and stability of switchgear. The accurate measurement of real contact temperature is still a problem, and the continuous state of switchgear cannot be assessed accurately by the temperature monitor. In this paper, a particular installation scheme of temperature sensor is put forward and a calculation algorithm for temperature rise of tulip contacts by the measured temperature of bus bar in real time based on artificial neural network (ANN) is established. An electromagnetic-thermal-fluid coupled simulation model for 10-kV/4000-A switchgears was built, and the thermal characteristic was studied taking the influential factors such as load current, ambient temperature, and contact resistance into consideration. The effectiveness of simulation model is discussed by the comparison to temperature rise experiment. Then, an ANN with three layers of structure is established to calculate the temperature of tulip contacts. The sensitivity and accuracy of network are calculated and verified. The results of this paper may provide a novel method for the monitor of switchgear temperature and assess continuous condition of high-current switchgear.
| Original language | English |
|---|---|
| Article number | 8573846 |
| Pages (from-to) | 279-287 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Components, Packaging and Manufacturing Technology |
| Volume | 9 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Feb 2019 |
| Externally published | Yes |
Keywords
- Artificial neural network (ANN)
- contact resistance
- high-current switchgear
- temperature rise experiment
- thermal field simulation