棉织物手感评定的人工神经网络应用研究
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摘要
织物手感风格是纤维材料或纤维制品的代表性感官特性,是客观存在的,它是织物与人之间适合程度的度量,即根据人们的感觉就可以评价的特性。近年来,神经网络不仅其本身正在向综合性发展,而且愈来愈与其它领域密切结合起来,几乎涉及到社会的各个领域,市场规模正在迅速扩大。本文就人工神经网络在棉织物手感评定方面的应用进行了研究探讨。
本文通过对十二种纯棉及棉型混纺面料进行测试与实验,研究织物手感感官评价的模式识别和综合评判问题。织物手感的感官性能是根据其在织物手感风格中的地位和作用,经过对特定人群进行调查和专家评审的办法来获得。采用手触摸和目测的方法获得对织物的主观感性认识,并和大脑中已有的记忆比较,分析影响感官评价方法的因素及手感特征与织物风格的关系,建立织物手感感官性能优劣的判定与评价标准。在织物手感的研究中,存在着许多定义不很严格或者说具有模糊性的概念,研究表明棉织物手感主观评定主要以柔软性、弹性、光滑性来评价织物手感的好坏,具有较好的适应性。
同时,织物的不同物理力学性能导致不同的织物手感风格,采用KES-FB测试系统,通过测量织物的物理力学量来评价织物的风格,分析织物的各个物理力学量值对手感的影响,建立人工神经网络预测模型,提出了人工神经网络预测棉织物织物手感的方法,用人工神经网络预测织物手感是依据KES-FB织物风格仪测试系统测得18个物理量,以BP神经网络构建织物手感主、客观评价之间关系的预测模型是可行的,一定程度上比较准确地预测出了织物手感。认为用人工神经网络预测棉织物织物手感将优于其它传统的方法。
Fabric handle is a representative character of materials or products made of various fibers, and it is objective, which can be used to assess the compatibility between fabrics and human beings, that is, subjective judgment is ranked by sense. In recent years, artificial neural network not only develops towards comprehensiveness, but also has been widely used in other aspects, almost covering every fields of the society. Its market scale is rapidly exposing. In the paper the application of artificial neural network on fabric handle assessment is investigated.Twelve kinds of blended and pure cotton fabrics are employed and tested to settle the problem of sensory evaluation of model recognition and comprehensive judgment for fabrics handle. The sensory property of fabrics handle is obtained by surveying among a special crowd and evaluation of experts. The standards of evaluation on fabrics handle rank are established by comparing the subjective recognition of fabrics using hand and eye with the memory stored in brain and analyzing factors affecting sensory evaluation and the relationships between handle feeling and fabric style. In the investigation of fabrics handle, there are many indistinctive or obscure conceptions. The study shows that softness, flexibility, lubricities are effective words in describing the handle feeling of fabrics.Different physical mechanics properties of fabrics endow various fabrics handle style. By evaluating the style of fabrics with KES-FB measuring system and analyzing effects of every physical mechanics factor on fabrics handle, a predictable artificial neural network model is constructed. And the method of predicting handle feeling of cotton fabrics is put forward by artificial neural network. The objective assessment of fabrics handle is based on eighteen physical index of KES-FB. The results prove that it is feasible to establish a predictive model of the connection between the subjective assessment and objective assessment by artificial neural network, and the artificial neural network predictable model can exactly predict the fabric handle to a certain degree. The artificial neural network overmatches traditional methods in predicting cotton fabric handle.
本文通过对十二种纯棉及棉型混纺面料进行测试与实验,研究织物手感感官评价的模式识别和综合评判问题。织物手感的感官性能是根据其在织物手感风格中的地位和作用,经过对特定人群进行调查和专家评审的办法来获得。采用手触摸和目测的方法获得对织物的主观感性认识,并和大脑中已有的记忆比较,分析影响感官评价方法的因素及手感特征与织物风格的关系,建立织物手感感官性能优劣的判定与评价标准。在织物手感的研究中,存在着许多定义不很严格或者说具有模糊性的概念,研究表明棉织物手感主观评定主要以柔软性、弹性、光滑性来评价织物手感的好坏,具有较好的适应性。
同时,织物的不同物理力学性能导致不同的织物手感风格,采用KES-FB测试系统,通过测量织物的物理力学量来评价织物的风格,分析织物的各个物理力学量值对手感的影响,建立人工神经网络预测模型,提出了人工神经网络预测棉织物织物手感的方法,用人工神经网络预测织物手感是依据KES-FB织物风格仪测试系统测得18个物理量,以BP神经网络构建织物手感主、客观评价之间关系的预测模型是可行的,一定程度上比较准确地预测出了织物手感。认为用人工神经网络预测棉织物织物手感将优于其它传统的方法。
Fabric handle is a representative character of materials or products made of various fibers, and it is objective, which can be used to assess the compatibility between fabrics and human beings, that is, subjective judgment is ranked by sense. In recent years, artificial neural network not only develops towards comprehensiveness, but also has been widely used in other aspects, almost covering every fields of the society. Its market scale is rapidly exposing. In the paper the application of artificial neural network on fabric handle assessment is investigated.Twelve kinds of blended and pure cotton fabrics are employed and tested to settle the problem of sensory evaluation of model recognition and comprehensive judgment for fabrics handle. The sensory property of fabrics handle is obtained by surveying among a special crowd and evaluation of experts. The standards of evaluation on fabrics handle rank are established by comparing the subjective recognition of fabrics using hand and eye with the memory stored in brain and analyzing factors affecting sensory evaluation and the relationships between handle feeling and fabric style. In the investigation of fabrics handle, there are many indistinctive or obscure conceptions. The study shows that softness, flexibility, lubricities are effective words in describing the handle feeling of fabrics.Different physical mechanics properties of fabrics endow various fabrics handle style. By evaluating the style of fabrics with KES-FB measuring system and analyzing effects of every physical mechanics factor on fabrics handle, a predictable artificial neural network model is constructed. And the method of predicting handle feeling of cotton fabrics is put forward by artificial neural network. The objective assessment of fabrics handle is based on eighteen physical index of KES-FB. The results prove that it is feasible to establish a predictive model of the connection between the subjective assessment and objective assessment by artificial neural network, and the artificial neural network predictable model can exactly predict the fabric handle to a certain degree. The artificial neural network overmatches traditional methods in predicting cotton fabric handle.
引文
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[3] Peirce, F.T. The Handle of Cloth as a Measurable Quantity. J.Text. Inst. 1930, 21: 377-416.
[4] 张义同,织物力学研究的新进展,力学进展,2003,2:217-225
[5] 严灏景、赵书经,织物风格的客观评定,纺织学报,1984,5(4):45-47
[6] 张瑞林,人工神经网络在纺织中的应用研究,博士学位论文,浙江大学,2001
[7] Brand R H. Measurement of fabric aesthetics: Analysis of aesthetic components. Textile Research Journal, 1964, 34: 791
[8] Hofflnan R M. Measuring the aesthetic appeal of textile. Textile Research Journal, 1965, 35: 428
[9] 松尾达树,关于风格的研究(第4报),纤维机械学会志,1972,25(1/2):9-18
[10] 川端季雄,风合评价的标准化解析.(第2版).大阪:纤维机械学会,1980,1-85
[11] 川端等.KN101,KN201,KN301等风格值的计算式[J].纤维机械学会志,1980.2:164-168
[12] 李栋高,丝绸材料学,北京:中国纺织出版社,1994:252—531
[13] 杨旭红、王华杰,棉毛型大豆蛋白纤维织物的风格研究,纺织学报,2002,23(4):20-21
[14] Sueo Kawabata, The standardization and analysis of hand evaluateon, 1980
[15] 川端季雄著,北京毛纺织研究所译:衣料风格测试仪,1982.3-12
[16] Postle R, Kawabata S, Niwa M. Wool fabric and clothing objective measurement technology. Proceedings of the International Wool Textiles Research Conference, 1985, 3: 51-56
[17] Postle R. Fabric objective measurement. Part Ⅱ: Product development and implementation. Textile Asia, 1989, 20(10): 59-62
[18] Fabric Assurance by Simple Testing. Instruction Manual(R). CSIRO Division of Wool Technology, 1990.
[19] 严灏景、潘宁,织物风格的客观评价的模式识别方法,纺织学报,1984,5(12):27—30
[20] 潘宁,织物触觉风格的客观评价—感觉的定量化研究,博士论文,华东纺织工学院,1985
[21] S. Kawabata, M. Niwa. Objective evaluation of the quality of ladies' garments, Intentional Journal of Clothing Science and Technology, 1992. 4(5): 34-44
[22] P. Potluri, I. Porat and J. Atkinson, Low-stress fabric testing for Process control in garment assembly Application of robotics, Int. J. Clothing Sci. Technol. 1996, 8: 12-23
[23] Cusick, G. E. The Dependence of Fabric Drape on Bending and Shear Stiffness. J. Text. Inst. 1965,56(11):596-606
[24] 蒋蕙钧,典型真丝绸的风格特征分析,苏州丝绸工学院学报,1994,14(4):51-61
[25] 李庆、李茂松,涤纶仿麻织物风格特征的评定,丝绸技术,1998,6(3)1—7
[26] 刘侃,用模糊聚类分析法评价服装加工性能,西安工程科技学院学报,2002,16(2):116—120
[27] 罗纪华、马艺华、黄海珍等,苎麻织物服用性能的模糊综合评定,北京纺织,2001,22(5):45—47
[28] M. Niwa, M. Nakanishi, M. Ayada, et al. Optimum silhouette design for ladies' garments based on the mechanical properties of fabrics. TRJ. 1998. 69(8): 578-588
[29] 李一东,双绉类织物舒适性能影响因素的分析,丝绸,1996,10(4):35-36
[30] 李湘露,丁淑敏,宗亚宁等,仿真织物悬垂性影响因素的多元回归分析,郑州纺织工学院学报,1999,10(3):5—8
[31] 梅兴波,顾伯洪.BP神经网络方法预测织物拉伸性能.东华大学学报(自然科学版) [J].2001,(3):64-67
[32] 日下部,生活衣服简易实验法,东京:家政教育社,1996,66-70
[33] 酒井、柳、冈村等,被服科学实验,东京:三共出版株式会社,1982,51-55
[34] 杨栋梁,织物手感及其评价方法(二),印染,1997,23(5):28-30
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