电子鼻研究进展及在中国白酒检测的应用

发布时间：2018-12-18 04:54

【摘要】：基于传感器技术、信号处理技术和模式识别技术发展起来的电子鼻技术是过去二十年中发展最为迅速的气相分析和气体检测技术之一,它已逐渐在生物医学、环境监测、农业生产、食品检测等多个领域得到应用.电子鼻是利用对待测气体具有交叉敏感性的传感器阵列将待测气体中的混杂气味组分信息转化为与时间、成分、浓度或含量相关的可测物理信号组,利用信号采集系统输出含有待测气体特征信息的数字信号,通过模式识别系统分析数字信号得到待测气体综合气味信息和隐含特征,实现对待测气体快速、系统、准确的鉴别和分析.本文综述了电子鼻技术中的传感器技术和模式识别技术及在中国白酒品牌鉴定、风味识别、酒龄检测方面的最新研究进展;以聚合物石英压电传感器型电子鼻为例,阐明该电子鼻的技术方案及其在中国白酒检测中的应用;展望电子鼻未来研究方向.
[Abstract]:Electronic nose technology, which is based on sensor technology, signal processing technology and pattern recognition technology, is one of the fastest developing gas phase analysis and gas detection technologies in the past two decades. It has gradually been used in biomedical, environmental monitoring. Agricultural production, food testing and other fields have been applied. An electronic nose is a group of measurable physical signals that use an array of sensors that are cross-sensitive to the gases to be tested to convert information about the mixed odour components in the gas under test into measurable physical signals related to time, composition, concentration, or content. The signal acquisition system is used to output the digital signal which contains the characteristic information of the gas to be tested. By analyzing the digital signal through the pattern recognition system, the comprehensive odor information and the implied characteristics of the gas under test are obtained, so that the gas can be treated quickly and systematically. Accurate identification and analysis. In this paper, the sensor technology and pattern recognition technology in electronic nose technology and the latest research progress in Chinese liquor brand identification, flavor recognition and wine age detection are reviewed. Taking the polymer quartz piezoelectric sensor electronic nose as an example, the technical scheme of the electronic nose and its application in the detection of liquor in China are expounded, and the future research direction of the electronic nose is prospected.
【作者单位】：北京科技大学自动化学院;
【基金】：国家高新技术研究发展计划资助项目(2013AA030901) 国家自然科学基金资助项目(61672094)
【分类号】：TP212

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