DOAJ Open Access 2026

Performance Defect Identification in Switching Power Supplies Based on Multi-Strategy-Enhanced Dung Beetle Optimizer

Zibo Yang Jiale Guo Rui Li Guoqing An Kai Zhang +2 lainnya

Abstrak

To address the limited defect-detection capability of existing performance testing methods for switching power supplies under varying operating conditions, this paper proposes a defect identification approach based on an enhanced Dung Beetle Optimizer. The algorithm integrates multi-strategy improvements—including piecewise chaotic mapping, Lévy flight perturbation, hybrid sine–cosine updating, and an alert sparrow mechanism—to refine the initial population generation, position update rules, and late-stage exploration. These enhancements strengthen its spatial search ability and computational performance. The experimental results show that the method accurately identifies the predefined defect intervals with a precision of 94.79%, covering 91.3% of the operating conditions. Comparisons with existing mainstream methods confirm the superior performance, effectiveness, and feasibility of the proposed method.

Topik & Kata Kunci

Applied mathematics. Quantitative methods Mathematics Electronic computers. Computer science

Penulis (7)

Zibo Yang

Jiale Guo

Rui Li

Guoqing An

Kai Zhang

Jiawei Liu

Long Zhang

Format Sitasi

APA MLA BibTeX

Yang, Z., Guo, J., Li, R., An, G., Zhang, K., Liu, J. et al. (2026). Performance Defect Identification in Switching Power Supplies Based on Multi-Strategy-Enhanced Dung Beetle Optimizer. https://doi.org/10.3390/mca31010012

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Informasi Jurnal

Tahun Terbit: 2026
Sumber Database: DOAJ
DOI: 10.3390/mca31010012
Akses: Open Access ✓