Detail publikace

Test Frequency Selection using Particle Swarm Optimization

Originální název

Test Frequency Selection using Particle Swarm Optimization

Anglický název

Test Frequency Selection using Particle Swarm Optimization

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

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"
}