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初步研究了物理法再生涤纶和原生涤纶的鉴别方法。通过“溶解-沉淀法”提取涤纶中游离齐聚物,用高效液相色谱(HPLC)法检测聚酯齐聚物的分布;在HPLC数据预处理中,依次采用小波变换法、相关性优化规整法和主成分分析方法达到基线校正、信号对齐和数据降维目的;建立反向传播人工神经网络模型,实现物理法再生涤纶的自动识别。该模型不能识别化学法再生涤纶,仅对物理法再生涤纶有效。研究结果表明:采用化学模式识别方法处理涤纶中齐聚物分布可用于鉴别物理法再生涤纶。
A preliminary study of the physical method of identification of polyester and virgin polyester. Polyester free oligomer was extracted by “dissolution-precipitation method”, and the distribution of polyester oligomer was detected by high performance liquid chromatography (HPLC). In the pretreatment of HPLC data, wavelet transform was used in turn, and correlation The optimized normalization method and principal component analysis method achieve the goal of baseline correction, signal alignment and data dimensionality reduction. The model of back propagation artificial neural network is established to realize the automatic identification of regenerated polyester by physical method. The model does not recognize chemically regenerated polyester and is only effective for physical regeneration of polyester. The results show that the use of chemical pattern recognition method to treat oligomers distribution in polyester can be used to identify physical regeneration of polyester.