This document proposes a fault detection scheme for a 5 bus system using artificial neural networks (ANN) and adaptive neuro-fuzzy inference systems (ANFIS). The scheme involves using discrete wavelet transform (DWT) to preprocess current and voltage measurements and extract statistical features. These features are then input into three ANNs/ANFIS models for fault classification, identification of fault phase, and detection of fault location. Simulation results on the 5 bus system demonstrate the effectiveness of the proposed scheme in accurately detecting fault type, phase and location in a fast and robust manner compared to previous methods.