Fiber Optic Sensors for On-Line, Real Time Power Transformer Health Monitoring
MetadataShow full item record
High voltage power transformer is one of the most important and expensive components in today's power transmission and distribution systems. Any overlooked critical fault generated inside a power transformer may lead to a transformer catastrophic failure which could not only cause a disruption to the power system but also significant equipment damage. Accurate and prompt information on the health state of a transformer is thus the critical prerequisite for an asset manager to make a vital decision on a transformer with suspicious conditions. Partial discharge (PD) is not only a precursor of insulation degradation, but also a primary factor to accelerate the deterioration of the insulation system in a transformer. Monitoring of PD activities and the concentration of PD generated combustible gases dissolved in the transformer oil has been proven to be an effective procedure for transformer health state estimation. However current commercially available sensors can only be installed outside of transformers and offer indirect or delayed information. This research is aimed to investigate and develop several sensor techniques for transformer health monitoring. The first work is an optical fiber extrinsic Fabry-Perot interferometric sensor for PD detection. By filling SF6 into the sensor air cavity of the extrinsic Fabry-Perot interferometer sensor, the last potential obstacle that prevents this kind of sensors from being installed inside transformers has been removed. The proposed acoustic sensor multiplexing system is stable and more economical than the other sensor multiplexing methods that usually require the use of a tunable laser or filters. Two dissolved gas analysis (DGA) methods for dissolved hydrogen or acetylene measurement are also proposed and demonstrated. The dissolved hydrogen detection is based on hydrogen induced fiber loss and the dissolved acetylene detection is by direct oil transmission measurement.
- Doctoral Dissertations