This paper proposes a method for transformer fault detection system based on GSM network, through the current transformer, voltage sensor information, the known fault information attribute conditions, and the feedback...This paper proposes a method for transformer fault detection system based on GSM network, through the current transformer, voltage sensor information, the known fault information attribute conditions, and the feedback weighted coefficient through the adaptive feed forward, that can obtain high fault information attributes, thus filtering interference factors and timely get fault information properties. It solves the traditional transformer can only judge general fault and fault real-time alarm by GSM network, the system also can measure the transformer oil temperature and oil temperature alarm in super high temperature, to detect the power transformer operation parameters, and the fault running state （over-current, over-voltage, under-voltage, warning）. The actual test system show that, diagnosis ability of fault signal separation ability and small signal identification increases 17%. also meet the requirements of real-time.展开更多
文摘This paper proposes a method for transformer fault detection system based on GSM network, through the current transformer, voltage sensor information, the known fault information attribute conditions, and the feedback weighted coefficient through the adaptive feed forward, that can obtain high fault information attributes, thus filtering interference factors and timely get fault information properties. It solves the traditional transformer can only judge general fault and fault real-time alarm by GSM network, the system also can measure the transformer oil temperature and oil temperature alarm in super high temperature, to detect the power transformer operation parameters, and the fault running state （over-current, over-voltage, under-voltage, warning）. The actual test system show that, diagnosis ability of fault signal separation ability and small signal identification increases 17%. also meet the requirements of real-time.
