Abstract
Microstructural information acquired from image analysis can be used in cell modeling. In order to obtain more precise Solid Oxide Fuel Cell (SOFC) microstructure parameters, an adaptive fuzzy approach is developed for three-phase identification of YSZ/Ni anode Optical Microscopic (OM) images. A new quantum-inspired clique potential Markov random field (MRF) function is proposed to considerate spatial information in fuzzy logic model, where the space distance based weight is introduced to reflect the influence of neighborhood pixels. Simulated images and real SOFC anode OM images are used to compare the effectiveness and practicability of the proposed algorithm with others. Experiment results demonstrate that the proposed methods can accurately separate there-phase of SOFC OM images, which lays the foundation of subsequent microstructural parameters extracting.
Published Version
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