A Bionic Visual Perception Optimization Method Adapted to Multiple Signal Intensities Within GIS
Year: 2025
Type: article
Abstract: Bionic visual perception technology captures optical signals from gas insulated metal enclosed switchgear (GIS) partial discharge by mimicking the biological visual system, achieving real-time detection and recognition of partial discharge phenomena under complex electromagnetic environments. However, existing technologies often consider only a single spectrum and do not account for differentiated thresholds for various discharge phenomena, affecting imaging accuracy. This paper proposes a multi-spectral bionic visual perception optimization method for GIS. First, a multi-spectral bionic visual perception framework is constructed. Second, an optimization problem is formulated to maximize the average imaging accuracy of all GIS discharge phenomena. Next, a two-stage event-driven deep Q-network (DQN) optimization method is proposed, learning the optimal light intensity change threshold through two-stage closed-loop feedback, including offline and online learning. Finally, the superior performance of the proposed method is validated through simulations.
Author: Jie Huang
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4407955304