By Topic

Wavelet Analysis for the Detection of Parametric and Catastrophic Faults in Mixed-Signal Circuits

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Spyronasios, A.D. ; Dept. of Electr. & Comput. Eng., Aristotle Univ. of Thessaloniki, Thessaloniki, Greece ; Dimopoulos, M.G. ; Hatzopoulos, A.A.

Methods for testing both parametric and catastrophic faults in analog and mixed-signal circuits are presented. They are based on the wavelet transform (WT) of the measured signal, be it supply current (IPS) or output voltage (VOUT) waveform. The tolerance limit, which affects fault detectability, for the good or reference circuit is set by statistical processing data obtained from a set of fault-free circuits. In the wavelet analysis, two test metrics, one based on a discrimination factor using normalized Euclidean distances and the other utilizing Mahalanobis distances, are introduced. Both metrics rely on wavelet energy computation. Simulation results from the application of the proposed test methods in testing known analog and mixed-signal circuit benchmarks are given. In addition, experimental results from testing actual circuits and from production line testing of a commercial electronic circuit are presented. These results show the effectiveness of the proposed test methods employing the two test metrics against three other test methods, namely, a test method based on the root-mean-square value of the measured signal, a test method utilizing the harmonic magnitude components of the measured signal spectrum, and a method based on the WT of the measured signal.

Published in:

Instrumentation and Measurement, IEEE Transactions on  (Volume:60 ,  Issue: 6 )