New digital testing for parametric fault detection in analog circuits using classified frequency-bands and efficient test-point selection
This paper presents a new parametric fault detection (PFD) approach for testing of linear analog circuits. It combines classified frequency-bands with amplitude weighting for fault controllability and test-points selection for fault observability. The test waveform sweeps on an applicable frequency-...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-06-01
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| Series: | Ain Shams Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2090447920302276 |
| Summary: | This paper presents a new parametric fault detection (PFD) approach for testing of linear analog circuits. It combines classified frequency-bands with amplitude weighting for fault controllability and test-points selection for fault observability. The test waveform sweeps on an applicable frequency-band instead of the whole band to stimulate parametric faults. The number of required samples is reduced, and the summation of samples from undesired bands is avoided. The test response is compacted for each band generating digital signature. The digital signature curve (DSC) is plotted for each component. A hybrid between MATLAB and PSPICE simulation is used to develop accurate worst case analysis (WCA). The relation between the classified DSC and the accurate WCA results in the enhanced PFD. It is found that the weighted sweeping-sinusoidal waveform is the best selection. The presented approach is applied to different linear analog benchmark circuits and shows the significant PFD improvement compared to previously published works. |
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| ISSN: | 2090-4479 |