Photodetectors are indispensable in a multitude of applications, with the detection of surface defects serving as a cornerstone for their production and advancement. To meet the demands of real-time and accurate defect detection, this paper introduces an optimization algorithm based on the GLV-YOLO model tailored for photodetector defect detection in manufacturing settings. The algorithm achieves a reduction in the model complexity and parameter count by incorporating the GhostC3_MSF module. Additionally, it enhances feature extraction capabilities with the integration of the LSKNet_3 attention mechanism. Furthermore, it improves generalization performance through the utilization of the WIoU loss function, which minimizes geometric penalties. The experimental results showed that the proposed algorithm achieved 98.9% accuracy, with 2.1 million parameters and a computational cost of 7.0 GFLOPs. Compared to other methods, our approach outperforms them in both performance and efficiency, fulfilling the real-time and precise defect detection needs of photodetectors.

Traditional photovoltaic-powered forced air-cooling systems face significant challenges in balancing energy efficiency and thermal comfort due to temperature sensitivity, mechanical ventilation energy consumption, and spatial constraints. This study aims to enhance building energy efficiency by integrating a radiant cooling ceiling (RCC) with a phase change material (PCM) thermal storage system, addressing the limitations of traditional photovoltaic-powered cooling systems through optimized material design and dynamic energy management. A ternary PCM mixture (glycerol–alcohol–water) was optimized using differential scanning calorimetry (DSC), demonstrating superior latent heat storage (361.66 J/g) and phase transition temperature (1.91 °C) in the selected “Slushy Ice” formulation. A 3D transient thermal model and experimental validation revealed that the RCC system achieved 57% energy savings under quasi-steady operation, with radiative heat transfer contributing 55% of total cooling capacity. The system dynamically stores cold energy during peak photovoltaic generation and releases it via RCC during low-power periods, resolving the “cooling energy consumption paradox”. Key challenges, including PCM cycling stability and thermal response time mismatches, were identified, with future research directions emphasizing multi-scale simulations and intelligent encapsulation. This work provides a viable pathway for improving building energy efficiency while maintaining thermal comfort and for improving building energy efficiency in temperate zones, with future extensions to arid and tropical climates requiring targeted material and system optimizations.