前言
磨损是一个企业形象的代表，不同的职业精神的表现。企业要生存，就必须参与市场竞争，就必须创造一个良好的企业形象。穿已成为现代企业竞争迈向国际化的一个不可缺少的一部分。在中国，在星级宾馆，大型百货公司，超级市场，大型，中型的塑造在同一时间内的企业和机构，越来越多的形象，人们的穿着的变化和消费观念和重点企业集团专业团体的不断扩大，正在建设中国服装这个巨大的市场。有媒体报道说，中国的劳动妇女的现行做法，有3.5亿，占47％的员工。通过对职业的就业预测，在我国男性和女性为7万人，因此，穿一个庞大的市场是世界上任何国家都无法比拟。然而，据有关部门统计，在我国，有一个妇女企业一定水平超过3 700人，都已经安装了超过25,000女性，而真正有规模，实力，穿在了非常专业生产小型企业。
服装面料和配件的选择和在发展的一个重大课题使用的磨损。由于磨损功能多样性的，相反的选择和材料的使用提出了新的要求。穿不同环境，不同的场合，职能的具体要求，不同的职能，往往会选择服装材料，如阻燃，压力，伪装，防酸，防碱，防油，防水，防紫外线辐射等功能性面料。织物风格，而物种多样性的垫层和服装质量控制粘附选择带来了更多的更高的要求。此外，在服装中国服装企业的面料大多依靠经验或通过反复试验，按匹配大量由于这些进程，以高度的主观结果，效力不足，不能满足现代的发展要求制衣业。所以，穿，以适应发展的要求，探讨穿衬保税布料，以及对穿着的服装企业质量预测的新方法，以进一步提高生产质量和效率，提供了一个有意义的参考工作。
粘合衬布的磨损作用
过去20年里，衬了较大的粘接技术。服装粘合衬所称的“骨架”和“骨干职业服装生产”不可替代的重要作用。粘合衬穿衣服的应用主要取决于织物的形状和特点。在产品质量，粘合衬一般应达到以下效果：
观念和安全型
穿它们的形状有具体要求，通过衬布，以实现它的形状和安全的要求。特别是，穿T恤在增加，弹性和刚性衬砌，使衣物直饱满。折叠在身体和穿衣服袖口对比等，可以折叠更大的刚度，更明确的界线。
提高强度
磨损的衣领，口袋衣服，袖口，腰带和其他地方必须保持一个稳定的形状和刚度一定程度。这一点，在薄型织物的服装更为突出。作为对比使用，因此许多层防护服，面料是不是由于过度拉伸，变形，可洗可穿的衣服。
增加学位
穿厚衣服的前增加和鲨鱼套筒零件，如生成一个慷慨的丰挺的结果。
冲击磨损衬布保税布料，以及一般参数质量
衬布保税面料和服装面料质量，粘合衬，粘合工艺参数，如各种因素的影响。参考，FZ/64008-2000热GB/T11389-11402热熔粘合衬布织标准的技术要求和有关资料，兼容性研究粘合衬布一般包括以下参数：参数
面料：织物密度，组织上，饱满油度，厚度，织物纱线线密度和捻系数;
粘合衬参数：布底的厚度，布衬饱满，颗粒大小的树脂，涂层重量，捻度衬布系数;
焊接工艺参数：粘接温度，焊接压力，焊接时间;
与织物复合粘合衬粘合后的性能参数：剥离强度，干洗尺寸变化，洗涤剂洗涤性能大小的变化（包括洗涤和干洗），胶渗流面积，悬垂性，综合运用价值手感值，游离甲醛含量。
穿新方法预测焊接质量
衣服，以改善国内时装业的内在质量和在国外，近年来，从科学和服装面料，粘合衬和技术人员后粘接工艺和质量开始的相互关系与粘合衬的合理性和粘附质量预测服装面料进行了一系列研究。研究人员已经成功地建立了复合物粘附在实验测量织物力学性能的基础上快速，后处理和悬垂性的预测模型，然后根据卡拉OK场所的织物评价系统来确定服装和衬的{zj0}组分配程序的不同部分。然而，由于忽视了基本结构，并衬的粘接质量，设计织物结构特性，不能按照对衬布，以确定该程序的理想结合组的性能。由于配套配件表面磨损特性，以满足中国服装高品质，自动化装配本文线生产的发展趋势，根据{zx1}的研究在国内和国外，从面料和衬里的基本素质结构预测焊接方法的探讨。
方式
人工神经网络进行数据分析人工神经网络是一种新型的智能技术，可以模拟人类的生物神经系统的具体情况，研究和推理，在许多方面比传统的技术回归方法更强大的预测能力，已广泛应用于各个领域，并显示良好的前景。在服装加工，人工神经网络的研究人员应用了很多服装的研究和实验，研究和实践证明，许多复杂的问题，人工神经网络在衬布保税布料，以及预测的质量，性能预测织物服装接缝处理和目标等级评估取得了良好效果。在有关研究成果，根据我国的磨损程度垫层匹配，可以使用人工神经网络结构下设立和衬布的结构性能，以及粘接条件预测商品的质量水平综合后模型，因此，在服装生产企业能够更迅速地穿了一个特别理想的衬织物的选择。
衬布保税面料和质量取决于面料，衬布和紧迫的条件，以及许多其他因素，研究人员采取了大量的服装面料和衬布的结构性能方差分析，方差分析测试结果表明，有重大影响面料和衬布的结构性能以及影响到粘接复合材料后，在质量分级的主要因素，都会对性能参数的结构产生重大影响的条件相结合，是在分散的反映，散点图显示，在键化合物，综合处理价值手感值，肥美的布，厚度增加，但随着在纱捻系数的增加，减少织物面料的质量和材料等级;与衬布的综合运用价值手感值，肥美的布和厚度的增加，但与量的树脂，树脂粒度和衬纱捻系数增加。随着热压温度，时间，压力之间的相互依存关系，是不可能孤立焊接时间，温度和债券上的每个选项的压力后，货物的质量综合分级的影响。由于多种因素造成的影响之间复杂的相互作用的焊接质量，焊接质量的传统方法是难以作出进一步具体的预测。由于它与人工结构系统故障非线性神经网络预测，容忍和应急能力，台湾的服装研究人员利用3 BP网络结构，这3名输入层，输出层和隐藏层。作为网络的输入值的13个参数的面料和衬布的结构性能，分级后的产值质量为网络已成功地在面料和衬布的结构性能的粘合剂粘合后复合物进行了质量等级预报。人工神经网络残留的分析表明，人工神经网络模型可以根据面料和衬布的结构性能有效地级约束力的最终预测的质量。
知识库中相应的知识库
方式和机器学习是人类思维的计算机自动获取知识的模拟过程，以解决人工智能的一个比较复杂的方法问题。在工程，人工智能问题的实践已经越来越复杂。通过机器学习数据库和信息系统，自动成为一个知识基础，压缩，可以完成复杂的问题自动解决。服装行业科技人员研究和实践表明，该方法能够使用成形性能粘合后复合的知识基础，以便更好地分析和预测。斯洛文尼亚马里博尔大学学者
的使用方法的知识基础，利用机器学习，回归树RETIS包，以表达形式的知识预测后粘附复杂的成形性能和成功之间的关系，根据具体的参数分析对在羊毛大衣附着性能预测复合物形成用织物的结构特性。同时，研究表明，在学习，研究数据库，以增加更多的样品机，能适应更多种类的知识配件粘附表面质量的分析和预测，研究和应用领域也将显示出广阔的空间。
在服装生产，以获得所需的形状轮廓服装，面料和类型和粘合衬质量必须进行协调，并了解后之间关系的参数之间复杂的相互作用的粘附性能的影响需要大量专门知识和资料。知识的学习技术，产生的样本可以学习任何必要的规则和关系，特别是外地机，简化了过程，我们建议后，复杂的一种新方法的分析性能童装的面料和粘合衬粘合关系和性能预测。结束语
穿
代表公司和个人形象，因而穿它要实现外型美观的要求，而且也wq符合要求的工作活动。粘合衬大大提高，如安全职能的磨损类型和强度，使用。随着磨损的发展和磨损的织物种类越来越多，不断提高服装衬布的匹配程度，提gx率成为重要的课题。
服装面料和复杂的过程形成粘连衬布，由于织物的性能测试结果和衬布之间以及各种因素的结合条件，复杂的作用和相互影响，利用方差统计分析的传统方法判别分析和难以粘结后完成综合质量定量评价的项目。人工神经网络和知识基础，技术解决结果，以及对我们的分析和预测研究的特点，强大的功能后，复杂的非线性问题，胶粘剂质量提供了有效的分析方法和工具。这种智能出国留学的途径及成衣业的做法取得良好的效果。可以想像，这些方法和在中国的服装生产中推广应用新技术，服装设计，可以作为依据的粘附物后，预测结果的科学素质，迅速地选择衬布，服装面料和衬布的选择，兼容性和技术的效率会大幅改善，将进一步推动中国的服装不断发展。
Wear interlining bonded fabric and the quality of prediction methods
Foreword
wear are representative of a corporate image, the performance of different occupational spirit. Enterprises to survive, it is necessary to participate in market competition, it is necessary to create a good corporate image. Wear has become a modern enterprise to compete towards the internationalization of an indispensable part. In China, the star-rated hotels, large department stores, supermarkets, large and medium-sized enterprise groups and focus on shaping the image of a growing number of enterprises and institutions, at the same time as people dress the concept of change and consumption of groups of professionals continues to expand, is building Chinas enterprises have more than 3 700 men and women both have installed more than 25,000, while the real has size, strength, wear has specialized in the production of very small enterprises.
wear fabrics and accessories are the choice and use of wear in the development of a major topic. Due to wear functional diversity, the opposite choice and use of materials put new demands. To wear a different environment, the specific requirements of different occasions, functions, different functions will often choose clothing materials, such as flame-retardant, pressure, camouflage, anti-acid, anti-alkali, anti-oil, waterproof, anti-ultraviolet radiation, etc. functional fabrics. Fabric style, while the diversity of species to the choice of underlayment and apparel quality control adhesion brings more higher requirements. In addition, Chinas garment enterprises in costume with lining mostly rely on experience or through a large number of repeated experiments Pressing matching, as a result of these processes with a highly subjective, the lack of effectiveness, can not meet the development requirements of the modern garment industry. So wear in order to adapt to the requirements of the development to explore the wear interlining bonded fabric and the quality of the new method of prediction for wear clothing enterprises to further enhance the production quality and efficiency to provide a meaningful reference work.
Fusible Interlining cloth in the role of wear
the past two decades, interlining adhesive technology by big margins. Apparel Fusible Interlining as of occupational clothing production has an important role irreplaceable. Fusible Interlining wear clothing application depends mainly on the shape and fabric characteristics. In quality, Fusible Interlining general should achieve the following effects:
stereotypes and security type
wear their shapes have specific requirements, the general through the interlining to achieve its shape and the security-based requirements. In particular, wear T-shirt before the increase, with the flexibility and stiffness lining, making the clothing straight plump. Fold in the body and wear clothes with contrast cuffs, etc., can fold greater stiffness, a more clear line.
improve the strength of
wear clothing of the collar, pockets, cuffs, belts and other parts required to maintain a stable shape and a certain degree of stiffness of. This point, on the thin fabric of the clothing is even more prominent. As the use of contrast, so many a protective clothing layer, fabric is not due to excessive stretching and deformation, can wash and wear more clothing.
increasing degrees
thick clothing for wear before the increase and sleeve parts of sharks, such as to generate a generous丰挺results.
impact wear interlining bonded fabric and the quality of the general parameters
interlining bonded fabric and garment fabric quality by, Fusible Interlining, bonding process parameters, such as the impact of various factors. Reference GB/T11389-11402, FZ/64008-2000 hot-melt woven Fusible Interlining cloth standard technical requirements and related information, Fusible Interlining Fabric with compatibility studies generally include the following parameters:
fabric parameters: fabric density, organizations , Oil on plump degrees, thickness, fabric yarn linear density and twist coefficient;
Fusible Interlining parameters: the thickness of the end of cloth, the cloth interlining plump, the resin particle size, coating weight, the yarn twist Interlining coefficient;
bonding process parameters: bonding temperature, bonding pressure, bonding time;
Fusible Interlining with fabric adhesive compound after the performance parameters: peel strength, dimensional changes of dry-cleaning, washing-size changes Washing performance (including the washing and dry cleaning), glue seepage area, drape, integrated handle value THV, free formaldehyde content.
wear new method of bonding quality of prediction
clothing in order to improve the intrinsic quality of the fashion industry at home and abroad in recent years, scientific and technical personnel from the garment fabric, Fusible Interlining and after adhesive bonding process and the quality of the mutual relations start with Fusible Interlining fabrics in the clothing of reasonable quality compatibility and adhesion prediction has been carried out a series of studies. Researchers have successfully established a FAST based on experimentally measured fabric mechanical properties, on the adhesion complexes after the handle and drape to the prediction model, then according to KES fabric evaluation system to determine the various parts of wearing apparel and interlining the best Group allocation program. However, due to neglecting the basic fabric and interlining structural properties of the adhesive quality, designer fabrics and can not in accordance with the performance of interlining to determine the ideal bonding group with the program. Given the surface wear characteristics of matching accessories, to meet Chinas wear high-quality, automated assembly line production of the development trend of this paper, according to the latest research at home and abroad, from the fabric and lining to the basic structure prediction quality bonding methods Discussion.
Ways
artificial neural network artificial neural network for data analysis are a new type of smart technology that can simulate human biological nervous system to specific things to study and reasoning, the technology in many ways than the traditional regression method is more powerful prediction capability, has been widely used in various fields and shows good prospects. In the garment processing, clothing application of artificial neural network researchers for many complex issues a lot of research and experimentation, research and Practice has proved that artificial neural networks in interlining bonded fabric and the quality of prediction, performance prediction fabric processing and garment seams objective grading evaluation achieved good results. In accordance with the relevant research results, in our country wear the matching of underlayment, be able to use artificial neural network set up under the fabric and interlining structural properties, as well as adhesive bonding conditions to predict the quality level of goods after the composite model, so that enterprises in the clothing production more quickly be able to wear for a particular choice of the ideal interlining fabrics.
interlining bonded fabric and quality depends on the fabric, interlining and pressing conditions, and many other factors, the researchers adopted a large number of apparel fabric and interlining structural properties analysis of variance, analysis of variance was significant effect of the test results show that fabric and interlining structural properties as well as a combination of conditions affecting the adhesive bonding composite materials after a major factor in the quality grading; will have a significant impact on the structure of performance parameters is reflected in the scatter, the scatter plot shows that after bonding compound the quality and grade of material with the fabric of an integrated handle value THV, plump cloth and the thickness increases, but with the fabric of the increase in yarn twist factor and reduced; with interlining integrated handle value THV, plump cloth and the thickness of the increased, but with the amount of resin, resin particle size and interlining yarn twist factor increases. As the pressing temperature, time, and the interdependence between the pressure, it is not possible to isolate bonding time, temperature and pressure of each option on the bond after the composite grading of the impact of quality goods. As a result of various factors affect the quality of bonding between the complex interactions, the traditional methods of bonding quality is difficult to make further specific prediction. Because of its artificial neural network prediction of nonlinear structural systems with fault-tolerant and contingency capabilities, Taiwan apparel researchers used three BP network structure, the three were input layer, output layer and hidden layer. The fabric and interlining structural properties of the 13 parameters as the network input values, adhesion complexes after grading the quality of the output value as the network has successfully under the fabric and interlining structural properties of the adhesive after the complex had a quality rating prediction. Artificial Neural Network Residual analysis showed that the artificial neural network model can under the fabric and interlining structural properties effectively binding prediction quality of the final grade.
Knowledge Base Knowledge Base
Ways and machine learning is the process of computer simulation of human thinking automatic access to knowledge, to address the issue of a relatively complex methods of artificial intelligence. Practice in engineering, artificial intelligence issues has become increasingly sophisticated. Through machine learning databases and information systems to automatically compressed into a knowledge base, can be completed automatically for solving complex problems. Apparel sector scientific and technological personnel research and practice show that the method be able to use knowledge base to better analysis and prediction after adhesion complexes forming properties. University of Maribor Slovenia
scholars Ways to use the knowledge base, using RETIS package for machine learning, regression trees in order to express the form of knowledge to predict the post-adhesion complex forming properties and analysis of specific parameters of the relationship between successful According to the structural properties of fabrics used in the wool coat adhesion complexes forming performance prediction. At the same time, studies have shown that in machine learning to study the database to add more samples, can adapt to a greater variety Knowledge accessories adhesion surface quality analysis and prediction, the field of research and application will also demonstrate a broader space.
production in wear, in order to obtain the desired contour shape garments, fabrics and the type and quality of Fusible Interlining must be coordinated, and to understand the impact of adhesion properties after the complex interaction between the parameters of the relationship need to have substantial expertise and data. Knowledge of machine learning techniques to generate samples can study any particular field of the necessary rules and relationships, simplifying the process, as we have proposed an analytical performance wear fabrics and Fusible Interlining bonding relationship and prediction of performance after the complex A new method. Concluding remarks
wear
represents corporate and individual image, thereby wear it is necessary to achieve pleasing to look at the requirements, but also to fully meet the required work activities. Fusible Interlining greatly enhanced the use of type and intensity of wear, such as security functions. With the development of wear and wear fabric types of growing, and constantly improve the level of wear crinoline matching and efficiency become very important topic.
wear fabrics and interlining in the formation of complex adhesion process, as a result of the performance of fabrics and interlining as well as the bonding conditions between the various factors that complicated the role and influence each other, making traditional methods of statistical analysis of variance and discriminant analysis are difficult to After completion of the bonding composite qualitative quantitative evaluation items. Artificial neural network and knowledge base technology to solve nonlinear problems as a result and a strong function of the characteristics of study for our analysis and prediction after the adhesive quality of complex provided an effective analytical techniques and tools. Smart Ways such study abroad and garment industry practice to obtain good results. Can imagine these methods and new technologies applied in Chinas wear. (07-11-23)