A Two-Stage Fault Detection and Classification Scheme for Electrical Pitch Drives in Offshore Wind Farms Using Support Vector Machine
| Autor: | Jagath Sri Lal Senanyaka, Van Khang Huynh, Surya Teja Kandukuri, Kjell G. Robbersmyr |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Electric motor
Wind power business.industry Computer science 020209 energy 020208 electrical & electronic engineering Condition monitoring 02 engineering and technology Fault (power engineering) Turbine Industrial and Manufacturing Engineering Automotive engineering Fault detection and isolation Offshore wind power Control and Systems Engineering 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business Induction motor |
| Zdroj: | IEEE Transactions on Industry Applications. 55:5109-5118 |
| ISSN: | 1939-9367 0093-9994 |
| DOI: | 10.1109/tia.2019.2924866 |
| Popis: | Pitch systems are one of the components with the most frequent failure in wind turbines. This paper presents a two-stage fault detection and classification scheme for electric motor drives in wind turbine pitch systems. The presented approach is suitable for application in offshore wind farms with electric pitch systems driven by induction motors as well as permanent magnet synchronous motors. The adopted strategy utilizes three-phase motor current sensing at the pitch drives for fault detection and only when a fault condition is detected at this stage, features extracted from the current signals are transmitted to a support vector machine classifier located centrally to the wind farm. The proposed method is validated in an in-house setup of the pitch drive. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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