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Increasing the reliability of wind turbines using condition monitoring of semiconductor devices: a review
The majority of electrical failures in wind turbines occur in the generator‐side semiconductor devices. This is due to temperature swings affecting the layers of insulated‐gate bipolar transistors in different ways; these effects are aggravated by the variation of wind speed. The implementation of accurate on‐line condition monitoring mainly relies on on‐line tracking of the temperature variation of components. The maximum temperature stress is observed at the junction terminal of the devices, which cannot be easily measured. Additionally, it is difficult to track the exact dynamic of temperature due to the slow response of sensors. Thus, several methods have been presented in the technical literature to estimate the junction temperature of the semiconductor devices. Each method has merits and disadvantages in terms of accuracy and complexity, as failure mechanisms have their own effects on the variation of junction temperature and some or all of the electrical parameters. Therefore, detection algorithms have to determine the root cause of the temperature variation. This study comparatively reviews the condition monitoring methods presented so far and gives directions on the future steps that should be addressed by research in this area.
- University of Birmingham United Kingdom
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).34 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
