显汗条件下针织面料主观热湿舒适性预测模型的建立

Prediction of Knitted Fabric Subjective Thermal-wet Comfort Properties Based on BP Neural Network

对36种针织面料的动态热湿舒适性客观指标进行测试与分析,再将36种面料制作成服装,通过人体穿着试验对针织面料的主观热湿舒适性感觉进行评定。随机选取其中28种面料建立了针织面料热湿舒适性客观评价指标与主观评价指标之间的BP神经网络预测模型,并通过该模型对另外8种针织面料进行验证和评估,结果表明,该模型能较好地预测针织面料的主观热湿舒适性。

In this paper,the dynamic thermal-wet comfort objective evaluation indexes of 36 kinds of knitted fabrics were tested and analyzed.And then the 36 kinds of knitted fabrics were made into clothes of same style.The thermal-wet comfort subjective evaluation indexes of these clothes were assessed by wearing tests.28 kinds of the fabrics were selected to establish the prediction model between the objective and subjective evaluation indexes based on BP neural network.The other 8 kinds of fabrics were used to validate the accuracy of the model.The results showed that the model can effectively predict the subjective thermal-wet comfort properties of fabrics.