Fault diagnosis in yaw drive induction motor for wind turbine
| Autor: | Mourad Mordjaoui, Ammar Medoued, Ali Ouanas, Djamel Sayad, Abdesselam Lebaroud |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Wind power
Renewable Energy Sustainability and the Environment business.industry Computer science 020209 energy 020208 electrical & electronic engineering Maintenance strategy Energy Engineering and Power Technology 02 engineering and technology Fault (power engineering) Turbine Automotive engineering Offshore wind power Reliability (semiconductor) Yaw drive 0202 electrical engineering electronic engineering information engineering business Induction motor |
| Zdroj: | Wind Engineering. 42:576-595 |
| ISSN: | 2048-402X 0309-524X |
| DOI: | 10.1177/0309524x18780379 |
| Popis: | Wind turbines are widely exploited throughout the world. The availability and reliability of offshore wind turbines are asking to impose a constant maintenance strategy. In this work, we propose a method that allows filtering the signal of the frequency inverter that feeds the yaw drive used in wind turbine. The redundant information is eliminated via discrete wavelet transform and empirical modal decomposition. The two types of faults are detected from the envelope of the Hilbert transform. The magnitude imbalance detection is carried out in the time domain. The root mean square values of the envelopes of the three-phase system have a good indicator for the fuzzy system to evaluate the severity of the defect. In the frequency domain, the signature of the broken bar fault is located in the low-frequency bandwidth. The harmonics appeared in the spectrum sensitive in amplitude and frequency to the variation of load. Experimental results have demonstrated the accuracy of the proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|