【作者】 许同洪；

【导师】 顾平；

【作者基本信息】 苏州大学 ， 纺织材料与纺织品设计， 2011， 博士

【摘要】 FAST测试系统下的力学性能指标对面料的手感与服装超喂缝纫的外观质量具有重要的影响,是服装加工过程中重要的控制指标。过去基于FAST系统下的力学性能指标建立的毛面料手感客观评价式与缝纫质量的预测模型是以二十世纪80年代生产的面料为试样,用实验的方法获得。进入二十世纪90年代以来,随着毛面料的面密度大幅度下降,需要把面料性能设计与超喂缝纫设计联系起来考虑来保证服装加工质量,而目前关于面料的力学性能与超喂缝纫的关系,理论上还不够完善。轻薄型毛面料在我国处于发展期,与国外相比其加工性能尚有差距。为了分析国内外轻薄型羊毛面料加工性能的主要差距及其对服装超喂缝纫质量的影响,给我国轻薄型毛面料的生产及其服装设计提供理论参考与数据支持。本文以国内外轻薄型毛面料为研究对象,在寻找其加工性能主要差异的基础上,进一步研究其力学性能与超喂缝缩率的理论关系,获得超喂缝缩率的预测方法。论文的研究工作主要有两大部分:一是轻薄型毛面料加工性能的主成分分析;二是毛面料超喂缝缩率的预测。轻薄型毛面料加工性能主成分分析分述于第二、第三章和第六章第一节。选择了35只国内外轻薄型毛面料试样(国外20只,国内15只),根据FAST控制图,结合毛产品用途,选择了15个加工性能指标作为评价指标,对其进行了测试与计算,将测试的数据运用主成分分析的方法把15个性能指标通过降维压缩成了7个综合评价指标,根据载荷贡献率的大小分别定义为可成形性主成分、湿膨胀主成分、厚重主成分、松弛回缩率主成分、经向弹性主成分、剪切刚度主成分、表观厚度主成分。通过主成分值计算发现了国内外毛面料差距最大的是可成形性,其次是厚重主成分,国外面料轻薄且可成形性大。为了提高国产面料的产品质量,以可成形性和厚重主成分为改进目标,通过产品设计与工艺管理,试制了5种精纺薄花呢,经测试达到了预期的效果。毛面料超喂缝缩率的预测分述于第四、第五章和第六章第二节。其研究过程为分三步:首先建立毛面料超喂缝缩率预测数学模型。为了简化问题,在研究中作出了简化假设,主要有不考虑缝线对面料的作用力及与面料之间的摩擦作用力;面料的重量忽略不计;面料的弯曲模量是一常量等。在此基础上应用大变形力学方程,引入服装设计参数:面料连结长度比(含义相当于超喂量)、连结长度(相当于针距),建立了面料超喂缝缩率与织物的弯拉模量比(面料弯曲模量与拉伸弹性系数之比)以及面料连接长度、面料连接长度比等之间的数学模型,使面料性能与服装设计联系起来。通过对数学模型的数字解析可知:面料弯拉模量比越大、面料连接长度比越大、面料连接长度越小,超喂缝缩率越小。基于FAST测试系统,分析、推导了面料弯拉模量比的测试计算方法;对弯拉模量比与FAST测试指标可成形性之间的关系作了分析:面料的成形性越大,弯拉模量比越大。由于国内面料试样可成形性小,弯拉模量比小,在超喂缝纫过程中缝缩率大,容易发生起皱;根据服装设计的需要,提出了缝纫可成形性的概念,表征不同面料超喂缝缩率预测的参考指标,泛化了面料可成形性的应用。其次,进一步研究面料连结长度比、连结长度在超喂缝纫加工中的变化。由于在熨烫过程受到热、湿的作用,发生松弛收缩和湿膨胀收缩,以缩水率为尺寸稳定性指标,分析其对面料连结长度,面料连接长度比的影响,从而揭示在超喂加工中湿膨胀率、松弛回缩率对超喂缝缩率的影响;基于经纬向的缩水率分析、推导了斜向缩水率的计算方法,为快速反应提供了基础。最后为了修正模型假设中的误差,提高预测精度,选取了弯拉模量比,面料连结长度,面料连接长度比,长、短面料的湿膨胀率和松弛回缩率等七个指标作为人工神经网络的输入参数,模拟衣袖超喂缝纫,建立了超喂缝缩率的人工神经网络预测模型,并与多元线性回归模型进行了对比,结果显示人工神经网络模型优于多元线性回归模型。综上所述,国内外轻薄型毛面料试样的主成分分析使我们清楚了国内面料的主要差距,为我国轻薄型毛面料加工质量的提高提供了主攻方向与数据支持;建立的超喂缝缩率预测模型及其误差修正方法,不仅能定量分析超喂缝缩率的影响因素,还可以为企业进行质量管理,优化工艺参数提供指导,改进了目前采用实验方法预测缝缩率的缺陷;同时也从理论上揭示了国内外面料加工性能的差距对服装超喂缝纫的影响。更多还原

【Abstract】 Mechanical properties tested by FAST system that is very important controlling index in apparel process have an important impact on fabric’s handle and appearance quality of apparel overfeed sewing. Based on mechanical properties tested by FAST system, the objective evaluation method for wool fabric handle and sewing quality predicting model have established by experiment method with fabrics produced in 80s of last century. Since 90s, as the decreasing of wool fabric’s unit weight it needed to connect fabric property design with overfeed sewing design to guarantee apparel process quality. And nowadays the theory of relationship between fabric mechanical property and overfeed sewing is still not perfect. Light wool fabric production in our country is still in the development period, and has obvious differences compared with abroad light wool fabric. In order to analyze the main differences of light wool fabric processing properties in home and abroad and their influence on apparel overfeed sewing quality which could supply theory reference and data support to home light wool fabric production and apparel design. This thesis took home and abroad light wool fabrics as research object to research further theoretical relationship between mechanical property and overfeed sewing shrinkage and acquire predicting method of overfeed sewing shrinkage by means of finding processing property main differences. The thesis’s work included two parts: one was principal component analysis of processing properties of home and abroad light wool fabrics; the other predicted overfeeding sewing shrinkage of light wool fabrics.Principal component analysis of processing properties of light wool fabrics was illustrated respectively in chapter two, three and part one of chapter six. It selected thirty-five samples of home and abroad light wool fabrics (Foreign were twenty, home were fifteen). According to FAST controlling drawing, it selected fifteen processing property indexes as evaluation index by combined wool product uses. Through testing and calculating, it compressed fifteen indexes to seven comprehensive evaluation indexes. According to each index contribution rate, it defined respectively such as formability principle component, moisture expansion principal component, thick-weight principal component, relaxation shrinkage principal component, warp tensile elasticity principal component, shearing rigidity principal component, and appearance thickness principal component. Through calculating of principal component value, it could find the biggest difference of home and abroad light wool fabric was formability principal component, and then was fabric thick-weight property. Foreign fabric showed light and had bigger formability. It could take formability and thick-weight property as improved aim in order to enhance of home fabric’s quality. Five worsted fancy fabrics were developed by product design and process management. When testing, the woven fabric had reached expectation effect.Wool fabric overfeed sewing shrinkage was illustrated respectively in chapter four, five and part two of chapter six. Three parts were conducted in this research process. Firstly it built predicting math model of overfeed sewing shrinkage. The research made simplification premise to reduce problem that did‘t consider sewing thread apply force and friction apply force between fabrics, and ignored fabric weight, and took bending modulus as constant and so on. In base of applying big deformation mechanics equation, apparel design parameters that include fabric connection length ratio (overfeeding amount) and connection length (needle distance) were brought. It built math model of between fabric sewing shrinkage and bending–tensile modulus ratio (fabric bending modulus than tensile parameter), and fabric connection length, and fabric connection length ratio to link fabric property and apparel design. Through math analysis of math model, it could get the smaller of overfeeding sewing shrinkage when the fabric bending–tensile modulus ratio and the fabric connection length ratio were bigger, and the connection length was smaller. It derived the method for testing and calculating of fabric bending–tensile modulus ratio based on FAST testing system. It analyzed the relationship between bending–tensile modulus ratio and formability of FAST testing index which indicated that the bigger of formability, the bigger of bending–tensile modulus ratio. Because home fabric has lower formability and bending–tensile modulus, it could cause sewing shrinkage higher and produce crepe easily. The thesis provided the new sewing formability concept as a reference value to represent different fabric’s sewing shrinkage prediction in overfeeding sewing which generalized the application of formability. Secondly it further researched the change of fabric connection length ratio and connection length in overfeeding sewing process. Fabric was caused relaxation shrinkage and moisture expansion shrinkage under the moisture and hot affection. The thesis took water shrinkage as dimensional stability index to analyze its influence on fabric connection length and fabric connection length ratio, which revealed moisture expansion rate and relaxation shrinkage rate would influence overfeeding sewing shrinkage in overfeeding process.It deduced calculating method of oblique shrinkage based on warp and weft shrinkage which supplied the base for fast reaction. Lastly in order to revise error of model premise and raise predicting accuracy, it selected seven indexes such as bending–tensile modulus ratio, fabric connection length, fabric connection length ratio, moisture expansion rate & relaxation shrinkage rate of long and short fabrics, as input parameters of artificial neural network. By simulating arm overfeed sewing it founded predicting model of artificial neural network of overfeeding sewing, and compared with multiple linear regression model. The result showed artificial neural network model had an advantage over multiple linear regression model.Summary, principal component analysis of home and abroad light wool fabric sample made us know clearly the main differences of home light wool fabric which indicted the research direction and supplied data supporting for enhancing process quality of home light wool fabric. The founded predicting model of overfeeding sewing and method of error correction were not only to analyze the influence factors of overfeeding sewing quantitatively, but also could go on company quality management, supply guide for process reference’s optimization, and improve imperfection of predicting sewing shrinkage through experiment method at present. Meanwhile on theoretically it revealed an influence on apparel overfeeding sewing caused by process property differences of home and abroad fabrics.更多还原