Application of Element Distribution and Topography Information Fusion Method Based on NSST in Contact Surface Microscopic Analysis
Li Wenhua1, Zhao Peidong1, Zhao Zhengyuan2, Pan Ruzheng1, Hu Kangsheng1
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Jointly Constructed by Hebei University of Technology Tianjin 300130 China; 2. Shenyang Railway Signal Co. Ltd Shenyang 110000 China
Abstract：Aiming at the problem that it is difficult to evaluate the contact surface completely when observing a single-modal image, in order to effectively deploy all relevant information from multiple modalities into a single-modal image, the paper proposes a non-subsampled shearlet transform (NSST) fusion method of element distribution and topography information. For the analysis of the element distribution on the contact surface recorded by scanning electron microscope & X-ray energy dispersive spectrometer (SEM&EDS) and the surface microtopography information recorded by 3D non-contact analysis system. First, with the help of whale optimization algorithm (WOA), the registration method based on B-spline is adopted. Next, a new weighted energy fusion rule is applied to achieve the fusion of multi-mode images with different resolutions. Finally, different element distributions are delineated from the fused contact images. Through the fusion results, the material transfer and microstructure of the contact were analyzed, and the element distribution on the contact surface was studied. It lays a foundation for analyzing the structure change of contact surface, analyzing and locating the surface fouling film and calculating the contact resistance accurately.
李文华, 赵培董, 赵正元, 潘如政, 胡康生. 基于非下采样剪切波变换的元素分布与形貌信息融合方法在触头表面微观分析上的应用[J]. 电工技术学报, 2022, 37(13): 3331-3340.
Li Wenhua, Zhao Peidong, Zhao Zhengyuan, Pan Ruzheng, Hu Kangsheng. Application of Element Distribution and Topography Information Fusion Method Based on NSST in Contact Surface Microscopic Analysis. Transactions of China Electrotechnical Society, 2022, 37(13): 3331-3340.
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2022, Vol. 37 
