Wavelet-Based Feature Extraction in Fault Diagnosis for Biquad High-Pass Filter Circuit

Yuehai Wang,Yongzheng Yan,Qinyong Wang

doi:10.1155/2016/5682847

Abstract

Fault diagnosis for analog circuit has become a prominent factor in improving the reliability of integrated circuit due to its irreplaceability in modern integrated circuits. In fact fault diagnosis based on intelligent algorithms has become a popular research topic as efficient feature extraction and selection are a critical and intricate task in analog fault diagnosis. Further, it is extremely important to propose some general guidelines for the optimal feature extraction and selection. In this paper, based on wavelet analysis, we will study the problems of mother wavelets selection, number of decomposition levels, and candidate coefficients selection by using a four-op-amp biquad filter circuit. After conducting several comparative experiments, some general guidelines for feature extraction for this type of analog circuits fault diagnosis are derived.

Highlights

Due to development of modern integrated circuit technology, many new electronic circuits have been created with greater complexity and with basic circuit elements being inaccessibly embedded within circuit chips
In order to solve these problems on a biquad high-pass filter circuit, we investigate the criteria of the selection of mother wavelet as well as the various feature construction methods in both decomposition level and wavelet parameters selection by implementing three different groups of comparative experiments
Our aim is to examine the efficiency of various feature extraction approaches with different wavelet mother selection, decomposing level, and coefficients selection

Summary

Introduction

Due to development of modern integrated circuit technology, many new electronic circuits have been created with greater complexity and with basic circuit elements being inaccessibly embedded within circuit chips. Fault detection and diagnostic techniques have been of interest to many researchers in circuits and systems, especially in system reliabilities. Despite the dominant role of digital and microprocessor in modern integrated circuits, analog circuits are very important in many electronic devices [1, 2]. Large electronic systems are usually implemented by digital techniques, quite often they interface with external world through analog devices such as sensors for inputs, AD/DA converters for signal processing, and actuators for outputs [3]. The objective of analog circuit fault diagnosis is to determine the fault types, components, and parameters once the abnormal circuit response is detected when we know the topology of circuit, stimulus signal, and response data of the circuit. The intelligent diagnosing approaches based on various pattern recognition (PR) techniques have attracted much attention and a number of promising developments have emerged

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Conclusion