High sensitivity test signatures for unconventional analog circuit test paradigms

Abstract

A method of testing for parametric faults in analog circuits based on a polynomial representation of fault-free function of the circuit is presented. The response of the circuit under test (CUT) is estimated as a polynomial in the root mean square (RMS) magnitude of the applied input voltage at a relevant frequency or DC. The test then classifies the CUT as fault-free or faulty based upon a comparison of the estimated polynomial coefficients with those of the fault-free circuit. The test application needs very little augmentation of the circuit to make it testable as only output parameters are used for classification. The method is validated on an active elliptic filter and is shown to uncover parametric faults causing deviations as small as 5% from nominal values. Fault diagnosis based upon sensitivity of polynomial coefficients at relevant frequencies is discussed. Another type of circuit signatures in the form of probability moments of the output when test input is random noise are also proposed. It is shown that the sensitivity of either signature can be enhanced by a newly proposed nonlinear V-transform. Finally, an adaptive test framework leveraging from these signatures and the transform technique is shown to improve defect level and yield loss.