Digital Testing of Analogue Circuits

Abstract

This thesis presents the new parametric fault detection (PFD) approach for analog circuits testing. It combines different approaches to enhance the PFD, based on the proper selection of classified frequency-bands with different amplitude weights for fault controllability and the proper selection of test-points for fault observability. The analog test generator (ATG) that stimulates parametric faults in the analog circuit under test (ACUT) generates a test waveform that sweeps on an applicable frequency-band with amplitude weights instead of sweeping the whole frequency-band. The test response is compacted on each applicable frequency-band for digital signature generation. The summation of unwanted samples from other unwanted frequency-bands are avoided for efficient PFD, based on the digital signature curve (DSC) that plots the digital signatures versus each component variation. In addition, the hybrid between the advantage of the MATLAB and the PSPICE simulation is exploited to developed better worst-case analysis (WCA). The presented simulation results, applied to different analog benchmark circuits, show the significant improvement in the PFD compared to other previously published works, in terms of the classified frequency-band and the required number of test-points. In addition, it is found that the best selection of a test waveform is the sweeping-frequency of a sinusoidal waveform with different amplitude weights.

Key words: Digital testing of analog circuits; testing of analog circuits; classification of frequency-bands; fault detection for parametric faults; selection of test-points