织物撕裂性能状态感知和分类由多源数据驱动
Jianmin Huang1,2, Qingchun Jiao3, Yifan Zhang3
1Zhejiang Institute of Standardization (Zhijiang Standardization Think Tank), Hangzhou, China.
PloS one
|April 16, 2024
概括
这项研究引入了一种新的方法来监测织物撕裂强度测试. 它准确地分类了测试状态,改善了织品质量控制中的工作流程和可追溯性.
科学领域:
- 织工程 织工程 织工程
- 材料科学 材料科学 材料科学
- 质量控制 质量控制 质量控制
背景情况:
- 织品的撕裂强度对于产品质量至关重要,但在实验室测试中容易受到设备,环境和人为因素的变化.
- 目前的测试方法缺乏影响因素的可追溯记录和测试活动的有效分类,阻碍了流程优化.
- 显然,需要一个强大的系统来监测和分类织物撕裂性能测试,以确保可靠和可重复的结果.
研究的目的:
- 建议使用多源数据进行面料撕裂性能测试的状态意识和分类方法.
- 开发一种能够实时监测测试期间电气参数,操作环境和操作员行为的系统.
- 为了提高织物撕裂测试过程的可追溯性和分类准确性.
主要方法:
- 织物撕裂性能测试活动的系统设计,具有实时监控功能.
- 多源数据收集,包括电气参数,环境条件和操作者的行动.
- 使用具有十倍交叉验证的决策树支矢量机器 (DTSVM) 进行数据预处理和分类.
主要成果:
- 开发的系统有效地感知了织物撕裂性能测试过程.
- 在分类不同织物测试状态时,获得了超过98.73%的高精度.
- 该系统在监测和分类测试活动方面表现强.
结论:
- 拟议的状态意识和分类方法显著提高了对织物撕裂性能测试的认知.
- 该系统有助于不断改进织物撕裂性能测试的工作流程和可追溯性.
- 该系统的广泛应用可以导致更可靠的织品质量评估.
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