Publication detail

Test Frequency Selection using Particle Swarm Optimization

KINCL, Z. KOLKA, Z.

Original Title

Test Frequency Selection using Particle Swarm Optimization

English Title

Test Frequency Selection using Particle Swarm Optimization

Type

journal article - other

Language

en

Original Abstract

The paper deals with the problem of test frequency selection for multi-frequency parametric fault diagnosis of analog linear circuits. An appropriate set of test frequencies is determined by minimizing the conditionality of the sensitivity matrix based on the system of fault equations using a global stochastic optimization. A novel method based on the Particle Swarm Optimization, which provides more accurate results and improves the convergence rate, is described. The paper provides several practical examples of its application to test frequency selection for active RC filters. A comparison of the results obtained by the proposed method and by the Genetic Algorithm is also presented.

English abstract

The paper deals with the problem of test frequency selection for multi-frequency parametric fault diagnosis of analog linear circuits. An appropriate set of test frequencies is determined by minimizing the conditionality of the sensitivity matrix based on the system of fault equations using a global stochastic optimization. A novel method based on the Particle Swarm Optimization, which provides more accurate results and improves the convergence rate, is described. The paper provides several practical examples of its application to test frequency selection for active RC filters. A comparison of the results obtained by the proposed method and by the Genetic Algorithm is also presented.

Keywords

fault diagnosis, frequency set selection, GA, PSO, test index measure.

RIV year

2013

Released

31.12.2013

Publisher

VSB–Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science

Location

Ostrava

Pages from

1

Pages to

7

Pages count

7

BibTex


@article{BUT102673,
  author="Zdeněk {Kincl} and Zdeněk {Kolka}",
  title="Test Frequency Selection using Particle Swarm Optimization",
  annote="The paper deals with the problem of test frequency selection for multi-frequency parametric fault diagnosis of analog linear circuits. An appropriate set of test frequencies is determined by minimizing the conditionality of the sensitivity matrix based on the system of fault equations using a global stochastic optimization. A novel method based on the Particle Swarm Optimization, which provides more accurate results and improves the convergence rate, is described. The paper provides several practical examples of its application to test frequency selection for active RC filters.  A comparison of the results obtained by the proposed method and by the Genetic Algorithm is also presented.",
  address="VSB–Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science",
  chapter="102673",
  institution="VSB–Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science",
  number="5",
  volume="11",
  year="2013",
  month="december",
  pages="1--7",
  publisher="VSB–Technical University of Ostrava, Faculty of Electrical Engineering and Computer Science",
  type="journal article - other"
}