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Fault Modeling of Analog Circuits Using System Identification Automated Model Generation Approaches from SPICE level Descriptions

Xia, Likun and Faroop, M. Umer and Hussin, Fawnizu Azmadi and Malik, Aamir Saeed (2012) Fault Modeling of Analog Circuits Using System Identification Automated Model Generation Approaches from SPICE level Descriptions. Advanced Science Letters . ISSN 1936-6612

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Abstract

Fault modeling and simulation (FMAS) of analog circuits is considered to be time consuming and expensive as compared to digital circuits. FMAS of analog circuits is heavily dependent on transistor level (TL) circuits and slow speed of TL fault simulation (TLFS) increase overall testing cost. Therefore, Automated Model Generation (AMG) techniques are employed to model nonlinear faults in analog circuits and achieve speed up in simulation. In this paper, we model faults of an operational amplifier (opamp) circuit using System Identification (SI) based AMG techniques: nonlinear autoregressive with exogenous input (NLARX) and hammerstein-wiener (H-W) techniques from SPICE transistor level descriptions. To investigate performance of AMGs for nonlinear behavior of faults, several nonlinear functions are employed such as sigmoid network, wavelet network, and tree partition etc. A comparison of simulation speeds of TLFS and AMGs is also provided. Simulation results show that more accurate and efficient AMGs should be considered for the modeling of nonlinear behavior of analog faulty circuits and achieve speedup in simulations.

Item Type:Article
Impact Factor:1.253
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments / MOR / COE:Centre of Excellence > Center for Intelligent Signal and Imaging Research
Departments > Electrical & Electronic Engineering
Research Institutes > Institute for Health Analytics
ID Code:8437
Deposited By: Dr. L Xia
Deposited On:22 Nov 2012 02:56
Last Modified:19 Jan 2017 08:21

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