A preprocessor for analog circuit fault diagnosis based on Prony's method

被引：5

作者：

El-Yazeed, MFA ^{[1
]}

Mohsen, AAK

机构：

[1] Cairo Univ, Elect & Commun Dept, Giza, Egypt

[2] Cairo Univ, Dept Engn Math & Phys, Giza 1221, Egypt

来源：

AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS | 2003年 / 57卷 / 01期

关键词：

fault diagnosis; Prony's method; neural networks; analog circuits;

D O I：

10.1078/1434-8411-54100136

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The paper presents a new technique for analog circuit fault diagnosis. The circuit under test is simulated both at fault free and different faulty conditions using PSPICE software. The AC response to a set of sinusoidal input frequencies is calculated at selected test nodes. Prony's method is then utilized as a preprocessor to extract an optimal set of features representing nodal voltage waveforms. The resultant features are used to train a back-propagation neural network to identify circuit faults. The potential of the algorithm is demonstrated by a second order active circuit example.

引用

页码：16 / 22

页数：7

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