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Fault Diagnostic in Analog Circuits Using Particle Swarm Optimization

EasyChair Preprint no. 9593

8 pagesDate: January 19, 2023


The faults in open and short circuits, as well as faults in discrete parameters, are the models of faults more used in the simulation method before the test. As the parameter with analog component is continuous, faults in discret parameters cannot characterize in detail all the possible faults in continuous components that occur in analog circuit. In order to solve this problem, a fault diagnostic method, based on Particle Swarm Optimization algorithm (PSO), is proposed in this paper. The fault diagnostic is transformed in an optimization problem. Particles represent fault components values and are applied to the transfer function of the circuit. The aim is to minimize the difference between the responses obtained by the real circuit and that of the simulated by PSO. This methodology can identify simple continuous faults and its effectiveness is validated using an electronic filter circuit.

Keyphrases: Algoritmo, Circuito Analógico, Diagnóstico de Falhas, Otimização, PSO

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Jalber D. L. Galindo and Nadia Nedjah and Luiza De M. Mourelle},
  title = {Fault Diagnostic in Analog Circuits Using Particle Swarm Optimization},
  howpublished = {EasyChair Preprint no. 9593},

  year = {EasyChair, 2023}}
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