Internal Discharge Location and Identification for Power Transformers Based on Multi-Sensor Fusion
To solve the problem of senor information fusion in power equipment condition monitoring,a sensor fusion array is constructed with several monitoring sensors for power transformers,i.e.,dissolved gas in oil,UHF and fiber optic ultrasound,and the identification strategy of transformer internal discharge is proposed in this paper.Firstly,the arrival time estimation is used to realize the discharge location by acoustic signal.Secondly,a novel feature fusion algorithm based on the multi-sensor is established,and the KNN(K nearest neighbor)algorithm is used to identify internal discharge in transformers.The experimental results show that the average error of discharge location is 45.1 mm,and the identification accuracy of discharge type reaches 90.6％.The multi-sensor fusion sensing strategy and system constructed in this paper could realize the accurate discharge location and pattern recognition in transformers with good application and promotion value.
transformerdissolved gas in oilpartial dischargemulti-sensor fusiondischarge locationpattern recognition
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