使用近红外 (NIR) 摄像头识别织纤维
Fariborz Eghtedari1, Leszek Pecyna1, Rhys Evans1
1The Manufacturing Technology Centre, Ansty Business Park, Pilot Way, Coventry CV7 9JU, UK.
Journal of imaging
|April 25, 2025
概括
本研究探讨使用近红外 (NIR) 摄像头来识别织材料,这对于回收至关重要. 一个新的度量可靠地区分棉花和聚,即使在具有挑战性的染料.
科学领域:
- 材料科学 材料科学 材料科学
- 织工程 织工程 织工程
- 频谱学是一种光谱学.
背景情况:
- 准确的织品成分识别对于有效的织品再利用和回收过程至关重要.
- 目前的方法在可靠地区分不同类型的织物,特别是棉花和聚等常见材料方面面临挑战.
- 染料的存在,如碳黑,进一步使材料分析复杂化.
研究的目的:
- 调查使用近红外 (NIR) 摄像机识别织材料的可行性.
- 开发一种可运输的度量标准,用于区分棉花和聚织品.
- 为了评估系统在存在具有挑战性的染料,如碳黑的性能.
主要方法:
- 使用近红外 (NIR) 摄像头,配备带通波器,以捕捉织品图像.
- 采用统计方法来分析来自NIR相机像素阵列的强度数据.
- 定义并验证了一种可重复的,稳定的材料识别指标,独立于相机曝光和照明.
主要成果:
- 确定了一种可靠的指标,能够区分棉花 (平均指标值0.68, ±2%的偏差) 和聚 (平均指标值1.0, ±1%的偏差).
- 该指标显示独立于相机曝光设置和物理照明的变化.
- 该系统成功检测到碳黑染料,从而能够分析未染色区域.
结论:
- 具有定义度的近红外 (NIR) 成像为准确的织材料识别提供了可行的解决方案.
- 开发的技术提供了一种稳定且可重复的方法来区分棉花和聚,克服了常见的行业挑战.
- 这种方法显示出增强织品回收的希望,因为它允许精确的材料分类,即使是难以分析的染色织物.
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