Soft Faults Diagnosis in Analog Circuits Using Optimization Inspired by Bat Behavior

Resumo

Open-circuit or short-circuit faults, as well as faults in discrete parameters are the most used models in
the simulation method before testing. As the response of an analog circuit to an input signal is continuous, failures
in any specific circuit element may not characterize all possible component failures. There are three important
features in diagnosing analog circuit faults: faulty component identification, faulty element value determination,
and circuit tolerance restrictions. To solve this problem, a fault diagnosis method is proposed in this work using
a bat-inspired algorithm, where the nonlinear equations of the circuit under test are used to calculate the circuit
parameters. The fault diagnosis is transformed into an optimization problem. The bats represents the values of

faulty components and applied to the transfer functions of accessible nodes. the objective is to minimize the dif-
ference between the responses obtained in the real circuit and the response simulated by the optimization process,

identifying which circuit component has the potential to present the failure. The proposed methodology is capable
of diagnosing simple faults and is proven with the Biquad Tow-Thomas Filter.