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Carbonation depth estimation system for concrete structures using neuro-fuzzy theory

机译:基于神经模糊理论的混凝土结构碳化深度估算系统

摘要

The present invention relates to a method of estimating the carbonation depth of a concrete structure using neuropurge theory, and more particularly, water binder ratio, concrete compressive strength, crack width, concrete surface chloride ion concentration, which are factors of compound degradation by using neuropurge theory, The present invention relates to a method for estimating the carbonation depth of concrete structures using neurofuzzy theory, which allows users to quickly and accurately estimate the carbonation depth by reflecting the influence of chloride ion diffusion coefficient, surface aging condition and time. A preferred embodiment of the present invention is (a) purging the input variables by using the water binding material ratio of the concrete structure, concrete compressive strength, crack width, concrete surface chloride ion concentration, chloride ion diffusion coefficient, surface aging condition, and time as input variables. Anger; (b) generating fuzzy rules for the number of all possible cases based on each input variable fuzzy in step (a); (c) calculating and normalizing the degree of membership of the fuzzy rule; (d) outputting a normalized fuzzy rule; (e) estimating the carbonation depth of the concrete structure by de-fuzzying the normalized fuzzy rule.
机译:本发明涉及一种使用神经吹扫理论来估计混凝土结构碳化深度的方法,更具体地,涉及使用神经吹扫法来降解复合物的因素-水结合率,混凝土抗压强度,裂缝宽度,混凝土表面氯离子浓度。理论,本发明涉及一种使用神经模糊理论估计混凝土结构碳化深度的方法,该方法允许用户通过反映氯离子扩散系数,表面老化条件和时间的影响来快速而准确地估计碳化深度。本发明的一个优选实施例是:(a)通过使用混凝土结构的水结合材料比例,混凝土抗压强度,裂缝宽度,混凝土表面氯离子浓度,氯离子扩散系数,表面老化条件和时间作为输入变量。愤怒; (b)基于步骤(a)中的每个输入变量模糊,为所有可能情况的数量生成模糊规则; (c)计算和规范模糊规则的隶属度; (d)输出归一化的模糊规则; (e)通过对标准化的模糊规则进行模糊化处理,估算混凝土结构的碳化深度。

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