Intelligent Fault Detection and Identification Approach for Analog Electronic Circuits Based on Fuzzy Logic Classifier

Ahmed R Nasser,Amjad J Humaidi,Ammar K Al-Mhdawi,Ahmad Taher Azar,Ibraheem Kasim Ibraheem

doi:10.3390/electronics10232888

Abstract

Analog electronic circuits play an essential role in many industrial applications and control systems. The traditional way of diagnosing failures in such circuits can be an inaccurate and time-consuming process; therefore, it can affect the industrial outcome negatively. In this paper, an intelligent fault diagnosis and identification approach for analog electronic circuits is proposed and investigated. The proposed method relies on a simple statistical analysis approach of the frequency response of the analog circuit and a simple rule-based fuzzy logic classification model to detect and identify the faulty component in the circuit. The proposed approach is tested and evaluated using a commonly used low-pass filter circuit. The test result of the presented approach shows that it can identify the fault and detect the faulty component in the circuit with an average of 98% F-score accuracy. The proposed approach shows comparable performance to more intricate related works.

Highlights

A fault is an abnormal state at the system level or device and is considered an error that can result in undesirable effects
An intelligent fault diagnosis approach for analog electronic circuits is presented in this paper
The circuit frequency response for each fault class is obtained via circuit simuation using Multisim software and statistically analyzed to generate the input membership functions for a Sugeno fuzzy logic classifier

Summary

Introduction

A fault is an abnormal state at the system level or device and is considered an error that can result in undesirable effects. Due to the complexity of electronic circuits, finding the fault manually by measuring each circuit’s components is an ineffective and time-consuming process. In digital systems, finding the fault is a simple process, due to the well-defined nature of the components in these circuits [3]. Fuzzy logic is a rule-based approach that requires less data for generating fuzzy rules based on an expert’s experience or knowledge in a specific domain. Fuzzy logic classifiers use a simple linguistic rule-based approach that can be used to classify the system conditions and specify the faulty component based on a set of rules generated from the system behaviors when it usually operates and when a specific component in the system fails [6]

Objectives

Results

Conclusion