Uncertain texture features fusion based method for performance condition evaluation of complex electromechanical systems. (June 2021) - Wang, Rongxi
Abstract: Accurate performance condition evaluation has a pivotal role in maintaining the operating reliability and preventing damage to complex electromechanical systems (CESs), which is still a challenging task. The uncertain features fusion inspired method is developed by utilizing the data-graph conversion, texture analysis, and improved evidence fusion. Unlike the conventional continuous time-series analysis-based methods, the 2D color-spectrums related to the performance conditions are constructed without information losing, and texture features of spectrums are extracted and fused to realize evaluation. The effectiveness of the proposed method is verified by actual evaluation applications. Moreover, the proposed method provides a new idea for large-scale high-dimensional data processing, decision making, uncertainty handling, and other engineering applications. Highlights: A texture based method for performance condition evaluation is proposed. Monitoring data is converted into 2-D color spectrum without information losing. Texture features based on self-similarity and dissimilarity are extracted. Non-parametric features fusion was proposed to handle with uncertain information.