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An analog circuit fault diagnosis method using improved sparrow search algorithm and support vector machine.

Guohua Wang1, Yiwei Tu1, Jing Nie1

  • 1School of Instrumentation and Optoelectronic Engineering, Beihang University, Beijing 100191, China.

The Review of Scientific Instruments
|May 14, 2024
PubMed
Summary

This study introduces an improved Sparrow Search Algorithm (ISSA) for enhanced analog circuit fault diagnosis. The ISSA-SVM model significantly boosts diagnostic accuracy compared to standard methods.

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Area of Science:

  • Electrical Engineering
  • Artificial Intelligence
  • Circuit Analysis

Background:

  • Analog circuit fault diagnosis faces challenges due to component tolerances and nonlinearity.
  • Existing methods may lack accuracy and robustness in identifying soft faults.

Purpose of the Study:

  • To develop an optimized soft fault diagnosis method for analog circuits.
  • To enhance the performance of the Sparrow Search Algorithm (SSA) for improved Support Vector Machine (SVM) parameter optimization.

Main Methods:

  • An improved Sparrow Search Algorithm (ISSA) was developed by addressing SSA deficiencies through four optimization strategies.
  • ISSA was benchmarked against other swarm intelligence algorithms using 23 functions, demonstrating superior convergence speed, accuracy, and robustness.
  • The optimized ISSA was employed to tune SVM parameters, creating the ISSA-SVM fault diagnosis model.

Main Results:

  • ISSA exhibited faster convergence, higher accuracy, and better robustness in optimization experiments.
  • The ISSA-SVM model achieved a correct fault diagnosis rate of 98.15% in Sallen-key test circuit experiments.
  • This represents an improvement over the standard SSA-SVM model, which had a diagnosis rate of 97.41%.

Conclusions:

  • The optimized ISSA-SVM model provides an effective approach for analog circuit soft fault diagnosis.
  • The proposed method demonstrates enhanced diagnostic accuracy and robustness.
  • This research contributes to more reliable fault detection in analog electronic systems.