Xie Ruifeng, Ding Shuyang, Cheng Zeyu, Ma Luowei, Yang Yanzhu
College of Mechanical Engineering, Donghua University, Shanghai 201620, China.
Sensors (Basel). 2025 May 19;25(10):3187. doi: 10.3390/s25103187.
The detection and quantification of fabric tactile sensations are crucial in textile production and marketing as they are closely linked to textile comfort and serve as key criteria for consumers when selecting fabrics. Previous studies have predominantly focused on measuring the physical properties of fabrics, often neglecting correlations between these parameters and tactile sensations. This oversight complicates customers' ability to assess the tactile experience of fabrics during online purchasing. This study first obtained subjective evaluations of three types of fabric tactile sensations through experiments involving volunteer participants. Subsequently, five objective physical properties that characterize fabric tactile properties were proposed and experimentally tested on 15 fabric samples categorized by yarn weight, weave pattern, and material. A fabric tactile spider diagram was created by normalizing the values of the five physical properties across the 15 fabric samples. The grading of the physical properties was then performed based on the proposed evaluation index. These spider diagrams were compared with the subjective evaluation results to analyze the physical properties that most significantly influenced subjective perception, ultimately leading to the development of a highly reliable fabric touch prediction model.
织物触感的检测与量化在纺织品生产和营销中至关重要,因为它们与织物舒适度密切相关,并且是消费者选择织物时的关键标准。以往的研究主要集中在测量织物的物理性能上,常常忽略了这些参数与触感之间的相关性。这种疏忽使得消费者在网上购物时难以评估织物的触感体验。本研究首先通过涉及志愿者参与者的实验获得了对三种织物触感的主观评价。随后,提出了五种表征织物触感特性的客观物理性能,并在按纱线重量、编织图案和材料分类的15个织物样品上进行了实验测试。通过对15个织物样品的五种物理性能值进行归一化处理,创建了织物触感蜘蛛图。然后根据提出的评价指标对物理性能进行分级。将这些蜘蛛图与主观评价结果进行比较,以分析对主观感知影响最显著的物理性能,最终开发出一个高度可靠的织物触感预测模型。