High voltage power fault-detection and analysis system: design and implementation

This paper investigates the design and implementation of an enhanced fault detection system in the high voltage (HV) power system. We introduce some typical signals which are important for the fault detection in the HV power system and describe three mathematical techniques for the data analysis: auto-correlation to analyze the degree of the raw input signal's distortion, FFT to extract the information of the error signals in the frequency domain, and granule to classify the error signals. By implementation of those algorithms, we can not only realize the fault tolerance and fault detection but also indicate the fault severity. The simulation of those mathematical techniques is presented using the examples of the practical pole voltage and phase current signals in the HV power system.