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A Decision Aiding System Based on the Choquet Integral Applied to Quality Evaluation of Composite Material Parts

机译:基于Choquet积分的决策系统应用于复合材料零件质量评估

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The purpose of this paper is to develop a decision aiding system for quality evaluation of composite material parts. The application deals with the detection of different regions inside parts. X-ray images of composite material parts are classified by means of three different methods: Haar wavelets, Gabor wavelets and PCA of gradient vectors. The obtained attributes are transformed into similarity maps to be expressed in the same space. Moreover, this representation is more understandable by experts. These similarity maps are then aggregated to obtain a cartography of the part. The aggregation process is based on the 2-additive Choquet integral to take redundancy, complementarity and independence of similarity maps into account. A learning algorithm is also proposed for the Choquet integral parameter estimation based on reference regions pointed by experts. The experiments show the sytem performance.
机译:本文的目的是开发一个决策辅助系统,用于复合材料部件的质量评估。该应用程序涉及在零件内的不同区域的检测。复合材料零件的X射线图像通过三种不同的方法进行分类:哈尔小波,梯度向量的咯咯槌小波和PCA。所获得的属性被转换为在相同空间中表示的相似性图。此外,专家的表现更加易懂。然后聚合这些相似性图以获得该部件的制图。聚合过程基于2 - 添加性Chourquet积分,以考虑相似性映射的冗余,互补性和独立性。还提出了一种基于专家指向的参考区域的Chromet积分参数估计学习算法。实验表明了系统性的性能。

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