Detection of Eyebolt Faults Using a Random Forest Ensemble Model Based on Multiple High-Frequency Electromagnetic Parameters
H. V. H. Silva Filho,
R.G. M. dos Santos,
Douglas C. P. Barbosa
et al.
Abstract:This paper presents an eyebolt structural fault detection system, based on the analysis of multiple electromagnetic parameters through a random forest classifier trained by both measurements and high-fidelity simulated signals. The proposed methodology is completely noninvasive and does not require the disassembly of the electrical infrastructure, allowing the live-line working. The obtained results show that the proposed multi-parameter strategy achieves high accuracy and increases the system's capability of … Show more
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