Adaptive Multiple Fault Detection and Alarm Processing for Loop System With Probabilistic Network

Abstract

This paper presents the fault detection and alarm processing in loop system with fault detection system (FDS). FDS consists of adaptive architecture with probabilistic neural network (PNN). Training PNN uses the primary/backup information of protective devices to create the training sets. However, when network topology changes, adaptation capability becomes important in neural network applications. PNN can be retained and estimated effectively. With a looped system, computer simulations were conducted to show the effectiveness of the proposed system, and PNN's adapt network topology changes.