The Faults Diagnostic Analysis for Analog Circuit Based on FA-TM-ELM

Abstract

Developing fault detection is very important for improving the equipment reliability and saving energy consumption. As compared with neural networks, extreme learning machine (ELM) is based on statistical learning theory, which has advantages of better classification ability and generalization performance. This paper presents a novel approach for fault detection and diagnosis based on Firefly-Chaos Algorithm and Extreme Learning Machine. The experiment result indicates this proposed method is effective for Analog Circuit fault detection and diagnosis and the model generalization ability is favorable.