基于机器视觉的机织物耐静水压性能检测  

Hydrostatic pressure inspection of woven fabrics based on machine vision

作　　者：倪嘉陆 王若雯 石文慧 袁志磊 徐平华 NI Jialu;WANG Ruowen;SHI Wenhui;YUAN Zhilei;XU Pinghua(School of Fashion Design&Engineering,Zhejiang Sci-Fech University,Hangzhou 310018,China;Shanghai Customs District,Shanghai 200135,China;Clothing Engineering Research Center of Zhejiang Rrovince,Zhejiang Sci-Fech University,Hangzhou 310018,China;Key Laboratory of Silk Culture Inheritage and Products Design Digital Technology,Ministry of Culture and Tourism,Zhejiang Sci-Fech University,Hangzhou 310018,China)

机构地区：[1]浙江理工大学服装学院,杭州310018 [2]上海海关,上海200135 [3]浙江理工大学浙江省服装工程技术研究中心,杭州310018 [4]浙江理工大学丝绸文化与产品设计数字化技术文化和旅游部重点实验室,杭州310018

出　　处：《现代纺织技术》2024年第1期18-26,共9页Advanced Textile Technology

基　　金：国家自然科学基金青年基金项目(61702460);浙江理工大学科研业务费专项资金资助项目(22076215-Y);浙江理工大学教育教育教学改革研究重点项目(jgzd202202);浙江理工大学优秀研究生学位论文培育基金项目(LW-YP2022054、LW-YP2022055)。

摘　　要：为提升机织物静水压检测效率,实现静水压自动评级,在优化视频采集模块的基础上,利用改进的背景差分法,对不同表观机织物静水压性能进行测试和分析。利用3D打印技术,实现采集设备和光源的封装;实时对视频帧进行掩膜、去噪和分割处理,以获得稳定有效的观测区域;利用优化更新背景策略的背景差分法,结合高斯混合模型,实现织物出水位置和帧位的实时记录,进而换算出织物耐静水压值。结果表明:该方法总体优于常规背景差分法、高斯混合模型背景差分法;对纯色和宽条格织物检测表现良好,误差在0.37%~2.77%;但对于细密的规则条纹和不规则印花织物误差较大,误差率在9.27%以上。该方法能够有效地检测纯色和部分规则花纹织物,对复杂表观织物的适用性有待提升。Hydrostatic pressure resistance of textiles is an important indicator affecting the wet comfort of textiles.In fabric research and testing stage,the hydrostatic pressure method is commonly used to assess the water resistance of textiles.Current standards such as ISO 811:2018,GB/T 4744—2013,and AATCC 127—2017 are applicable to evaluating the water resistance of various fabrics and non-woven materials(such as canvas,geotextiles,and tent fabrics) that have undergone waterproofing treatments.However,these standards still require inspectors to stop the equipment when the third water droplet is observed.Manual judgment has many disadvantages,such as the delay in human-machine operation,the inability to accurately describe the water discharge position,the need for inspectors' presence,and poor reproducibility.Therefore,exploring the automatic ispection of the hydrostatic pressure of woven fabrics is of great significance.Machine vision-based hydrostatic pressure testing can be understood as dynamically tracking transparent,nearly circular water droplet targets on the substrate of fabric.Currently,existing methods for detecting moving targets include optical flow,frame difference,and background subtraction.There are still some shortcomings in the current image-based detection of dynamic water droplets on fabrics.First,optical flow method has a high computational complexity,which can easily lead to delay and misjudgment in video droplet tracking.Second,the frame difference method is sensitive to light and holes are easy to appear in the segmented motion foreground when water droplets move slowly.There are many limitations in its application.Third,Gaussian mixture model has weak convergence and poor contour detection integrity,and is not robust to external factors such as environmental noise and lighting.Fourth,infrared images have poor detection results in static water pressure testing due to the small temperature difference between water droplets on the fabric surface and the fabric surface caused by prolonged contac

关 键 词：机织物 静水压 抗渗水性 水珠 高斯混合模型 

分 类 号：TS107.4[轻工技术与工程—纺织工程]