Machine learning applications in health monitoring of renewable energy systems
Rapidly evolving renewable energy generation technologies and the ever-increasing scale
of renewable energy installations are driving the need for more accurate, faster, and smarter …
of renewable energy installations are driving the need for more accurate, faster, and smarter …
[HTML][HTML] Machine learning for advanced characterisation of silicon photovoltaics: A comprehensive review of techniques and applications
Accurate and efficient characterisation techniques are essential to ensure the optimal
performance and reliability of photovoltaic devices, especially given the large number of …
performance and reliability of photovoltaic devices, especially given the large number of …
Data-driven femtosecond optical soliton excitations and parameters discovery of the high-order NLSE using the PINN
Y Fang, GZ Wu, YY Wang, CQ Dai - Nonlinear Dynamics, 2021 - Springer
We use the physics-informed neural network to solve a variety of femtosecond optical soliton
solutions of the high-order nonlinear Schrödinger equation, including one-soliton solution …
solutions of the high-order nonlinear Schrödinger equation, including one-soliton solution …
Towards more reliable photovoltaic energy conversion systems: A weakly-supervised learning perspective on anomaly detection
With the increasing popularity of photovoltaic (PV) systems, both academia and industry
have been paying growing attention to fault prediction and health management. Although …
have been paying growing attention to fault prediction and health management. Although …
PVEL-AD: A large-scale open-world dataset for photovoltaic cell anomaly detection
The anomaly detection in photovoltaic (PV) cell electroluminescence (EL) image is of great
significance for the vision-based fault diagnosis. Many researchers are committed to solving …
significance for the vision-based fault diagnosis. Many researchers are committed to solving …
Toward secure distributed data storage with error locating in blockchain enabled edge computing
The technique of Internet of things (IoT) connects the distributed devices via the network that
can realize smart applications, such as intelligent transportation, intelligent manufacturing …
can realize smart applications, such as intelligent transportation, intelligent manufacturing …
Photovoltaic cell defect classification based on integration of residual-inception network and spatial pyramid pooling in electroluminescence images
Electroluminescence (EL) imaging provides high spatial resolution and better identifies
micro-defects for inspection of photovoltaic (PV) modules. However, the analysis of EL …
micro-defects for inspection of photovoltaic (PV) modules. However, the analysis of EL …
[HTML][HTML] A benchmark dataset for defect detection and classification in electroluminescence images of PV modules using semantic segmentation
Electroluminescence (EL) images enable defect detection in solar photovoltaic (PV)
modules that are otherwise invisible to the naked eye, much the same way an x-ray enables …
modules that are otherwise invisible to the naked eye, much the same way an x-ray enables …
A photovoltaic surface defect detection method for building based on deep learning
Y Cao, D Pang, Y Yan, Y Jiang, C Tian - Journal of Building Engineering, 2023 - Elsevier
The inspection and diagnosis of building engineering involve health monitoring of buildings
and related facilities, and the utilization of renewable energy, such as solar energy, is crucial …
and related facilities, and the utilization of renewable energy, such as solar energy, is crucial …
SNCF-Net: Scale-aware neighborhood correlation feature network for hotspot defect detection of photovoltaic farms
The photovoltaic hotspot defect detection is challenging due to the features vanishing as the
network deepens and the poor feature discrimination ability under complex background …
network deepens and the poor feature discrimination ability under complex background …