研究目的
To investigate the ability of near-infrared spectroscopy to predict the tensile strength of thermally aged fabrics used in protective clothing for wildland firefighters and other workers.
研究成果
NIR spectroscopy can predict the tensile strength of thermally aged fabrics using reflectance measurements at a few wavelengths, with models achieving high adjusted R2 values. This non-destructive method shows potential for practical use in evaluating in-use protective clothing, though further research is needed to address limitations and extend to other fabric types and aging conditions.
研究不足
The study is a proof-of-concept with limitations including a lack of training data for tensile strengths between 300 N and 600 N, focus on single-layer Nomex IIIA fabrics only, no evaluation of other aging factors like UV radiation or abrasion, and potential interference from soiling in real-world conditions. Future work should address these to improve model accuracy and applicability.
1：Experimental Design and Method Selection:
The study used a cone calorimeter for thermal aging of fabric specimens at various heat fluxes and durations, followed by tensile strength measurements and near-infrared spectroscopy. Multivariate linear regression was applied to correlate tensile strength with reflectance values.
2：Sample Selection and Data Sources:
Nomex IIIA fabric specimens in four colors (royal blue, red, yellow, dark blue) were used, cut to 15 cm by 10 cm and conditioned. Specimens were exposed to heat fluxes of 10, 20, 30, and 40 kW/m2 for specified durations.
3：List of Experimental Equipment and Materials:
Cone calorimeter (Fire Testing Technology), Schmidt-Boelter heat flux gauge (Medtherm), infrared thermometer (Cyclops 300AF, Minolta/Land), data acquisition system (Agilent 34970A), tensile testing machine (Instron 1122), UV-Vis-NIR spectrophotometer (Cary 5G, Agilent), thermogravimetric analyzer (TA Instruments Q500), MATLAB for data analysis.
4：Experimental Procedures and Operational Workflow:
Specimens were thermally aged in the cone calorimeter, temperatures were recorded, tensile strength was measured according to ASTM D5034-09, and NIR reflectance spectra were obtained. Data were analyzed using multivariate linear regression in MATLAB.
5：Data Analysis Methods:
Multivariate linear regression was used to develop correlations between tensile strength and reflectance values, with statistical criteria such as R2 and adjusted R2.
独家科研数据包，助您复现前沿成果，加速创新突破
获取完整内容
