A Dilation and Erosion-Based Clustering Approach for Fault Diagnosis of Photovoltaic Arrays

Advanced impedance mismatch technique for detecting faults in photovoltaic systems

“…Innovative approaches, such as 2D CNN for fault classification under harsh conditions, 15 and the application of the Teager Kaiser Energy Operator for fault detection, have demonstrated potential but also face challenges in practical application and scalability. [16][17][18] Liu et al 19 introduce a novel clustering method based on dilation and erosion theory, with enhanced fault diagnosis in PV arrays without the need for predetermining fault types. Research efforts have often been fragmented, focusing on specific fault types through methodologies, like, fuzzy logic, 20 neural networks, [21][22][23][24][25] and machine learning 26 leaving a void for a comprehensive fault detection and localization solution.…”

Morphological Texture Description For Hyperspectral Images: Pattern Spectrum

“…It has been widely known mostly for its elementary operators, e.g., erosion-dilation and opening-closing pairs, or segmentation tools, e.g., watershed and skeletonization. While they are useful and can be found at the core of many image processing and analysis solutions [1,2,3], MM also provides a set of tools capable of dealing with textures such as granulometry or, its derivative form, pattern spectrum [4].…”