Analog Circuit Faulty Parameter Identification Based on Two-Objective Evolutionary Algorithm

Faulty parameter identification is vital to prediction of remaining useful life of circuit under test (CUT). Based on the transfer function, we use measured faulty response to deduce the possible faulty parameters. It is known that the measured response of the CUT is the function of the analog param...

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Bibliographic Details
Published in:IEEE transactions on instrumentation and measurement 2021, Vol.70, p.1-11
Main Author: Yang, Chenglin
Format: Article
Language:English
Subjects:
Analog circuits
Circuit faults
Deduction
Deviation
Evolutionary algorithms
Fault diagnosis
genetic algorithm (GA)
Genetic algorithms
Mathematical model
Optimization
Parameter estimation
Parameter identification
Parameter modification
Sociology
Statistics
Transfer functions
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Summary:Faulty parameter identification is vital to prediction of remaining useful life of circuit under test (CUT). Based on the transfer function, we use measured faulty response to deduce the possible faulty parameters. It is known that the measured response of the CUT is the function of the analog parameters. Usually, the number of independent response is much less than that of the analog component. The underdetermined equations have infinite solutions. In other words, there are lots of combinations of analog parameters that can generate the same faulty response. Hence, it is more valuable to deduce the possible faulty parameter range than to estimate a single faulty parameter. The deduction is accomplished by using a modified two-objective genetic algorithm. The individual that minimizes the deviation, viz., difference between the simulated and measured faulty responses, gives the possible faulty parameter. Finding the possible faulty parameter range equals to finding the minimal and maximal faulty parameters that can zero the deviation. Hence, we have to simultaneously minimize (and maximize) the faulty parameters and minimize the deviation. It is transformed into a two-objective optimization problem. We use Pareto dominated method to minimize and maximize the faulty parameter. The effectiveness of the proposed method is examined by using filter circuit examples.
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2020.3034125