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基于模糊语义模型的陶瓷智能评估系统的研究

The Study of Intelligent Sensory Evaluation System for Ceramic Based on Fuzzy Semantics Model

【作者】 宁小平

【导师】 肖绚;

【作者基本信息】 景德镇陶瓷学院 , 机械设计及理论, 2008, 硕士

【摘要】 陶瓷在日常生活中无处不在,人们在购买时不仅要求价格适中,更要求质量可靠,使其具有较高的性价比。而目前,我国陶瓷行业仍然采用手感和目测等方法进行质量评估,其评估结果往往是不可靠的。因此建立一套完整的、可靠的陶瓷质量评估系统已成为一项迫切的工作和研究内容。感观评估是通过人的视觉、嗅觉、味觉、触觉、听觉所获信号的评估技术,目前已广泛应用于食品、化妆品、纺织、化学、包装、汽车等行业中,并已成为研究的新热点。在这种情况下,我们将感观评估技术引入到陶瓷行业中,建立起一套完整的陶瓷智能感观评估平台。本文结合陶瓷行业自身特点,运用灰色理论、模糊语义、D-S证据理论、多元统计分析、遗传算法等理论和方法,以MATLAB和SPSS等应用软件为工具,建立了一个适用于陶瓷行业的感观评估系统。该系统主要由感观评估、客观评估、感观客观之间联系三部分组成。在感观评估部分,首先,我们建立了一个数据标准化模型,并且通过实例验证了我们所建模型的有效性;其次,通过设计调查问卷表对普通消费者的评估数据进行收集,用统计学中的因子分析方法对收集来的数据进行筛选,选用K-均值聚类方法对筛选后的数据进行聚类分析;由于专家和普通消费者之间对评估词汇的定义和理解有所差异,很容易造成专家与普通消费者评估之间的冲突,因此,最后采用遗传算法建立模型,解决了专家评估与普通消费者评估之间的冲突问题。客观评估部分,结合核函数和主成分分析法对仪器测量的客观数据进行核主成分压缩,并通过灰色聚类方法对压缩后的数据进行聚类分析。此陶瓷感观评估体系已用于景德镇陶瓷企业,效果明显。

【Abstract】 We can see domestic ceramic anywhere in daily life, when buying them people not only ask the advisable price but also ask the high quality, make it have good cost performance. But nowadays in our country handle and visual measurement are still adopted as the method of ceramics quality evaluation, the result sometimes is unreliable. So it is necessary to establish a dependable quality evaluation system for ceramic. Sensory evaluation is an evaluation which process signal attained by seeing、smell、taste、feeling、hearing. Now, it is widely used in the field of food industry、cosmetic industry、textile industry、chemical industry、packaging industry、automobile industry and so on. In such a case the technology of sensory evaluation was imported to the ceramic industry, we have established an intelligent sensory evaluation system for ceramic.This paper established an intelligent sensory evaluation system for ceramic with the software MATLAB and SPSS based on Grey System Theory、Fuzzy Semantics、D-S evident theory、Multivariate Statistical Analysis and Genetic Algorithm. The system is made up of sensory evaluation, objective evaluation and the contact between sensory evaluation and objective evaluation.In the part of sensory evaluation, first of all, a ceramic model of sensory data standardization was established and the validity was validated by a case; then, we collect evaluation date from ordinary customer by design principles of consumer questionnaire; next, we built a data filtration process by factorial analysis; also we propose a fuzzy c-mean clustering method; due to experts and ordinary consumers’ difference to evaluation vocabulary’ define and understanding which is likely to result in conflict between evaluation experts and ordinary consumers, finally we established a model to resolve it by genetic algorithm. In the part of objective evaluation, by combining the kernel function and principal component with it, we reduce the date which is measured by apparatus, while processing date with clustering analysis we propose a gray clustering method. The sensory evaluation is applied to ceramic companies in jingdezhen and the effect is distinct.

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