首页> 外文会议>2014 International Conference on Information, Communication Technology and System >The implementation of preconcentrator in electronic nose system to identify low concentration of vapors using neural network method
【24h】

The implementation of preconcentrator in electronic nose system to identify low concentration of vapors using neural network method

机译:神经网络方法在电子鼻系统中预浓缩器识别低浓度蒸气中的实现

获取原文
获取原文并翻译 | 示例

摘要

Vapor identification system having high sensitive and discriminative capabilities is much needed in various applications such as in monitoring of environmental condition, detecting of hazardous substances, and producing of flavored foods or drinks and others. Nowadays, electronic nose technology which consists of gas sensor array and neural network pattern recognition could not recognize well for the low concentration vapors. In this research, the implementation of a preconcentrator was used to increase the vapor concentration allowing the electronic nose system to gain its high sensitivity and selectivity. The experimental result showed that the electronic nose system equipped with the preconcentrator could distinguish ethanol, benzene and acetone vapors in low concentrations successfully.
机译:在各种应用中,例如在监视环境状况,检测有害物质以及生产调味食品或饮料等中,非常需要具有高灵敏度和区分能力的蒸气识别系统。如今,由气体传感器阵列和神经网络模式识别组成的电子鼻技术无法很好地识别低浓度蒸汽。在这项研究中,使用预浓缩器来增加蒸气浓度,从而使电子鼻系统获得其高灵敏度和选择性。实验结果表明,配备预浓缩器的电子鼻系统可以成功区分低浓度的乙醇,苯和丙酮蒸气。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号