Non-destructive testing and evaluation of textile thermal-wet properties based on visible and infrared dual-modal imaging

This study proposes a non-destructive testing method based on dual-mode imaging for evaluating the thermal and moisture properties of textiles. By integrating visible-light and infrared thermography with advanced image-processing algorithms – such as Gaussian filtering, Hue-Saturation-Lightness (HSL) space conversion, dynamic Hough transform, and morphological operations – this approach enables non-contact, real-time dynamic monitoring of heat and moisture transfer in fabrics. The experimental setup, which includes a visible-light camera, an infrared camera, a constant-temperature heating rubber plate, and a peristaltic pump, recorded the diffusion of moisture and changes in fabric surface temperature under simulated environmental temperatures of 25°C, 37°C, and 60°C. Following image preprocessing and analysis, key performance parameters – such as maximum wetting diameter, total wetted area, and drying rate – were quantified precisely. Results demonstrate that the system performs robustly in tests involving six fabrics of different materials and colours, effectively overcoming limitations of conventional assessment methods, such as low efficiency, operational complexity, and high cost. This research provides a novel non-destructive tool for optimising sportswear design and improving the thermal comfort of functional textiles, thereby supporting the textile industry’s transition towards higher quality, personalisation, and intelligence.