波谱学杂志 ›› 2011, Vol. 28 ›› Issue (2): 244-250.

• 研究论文 • 上一篇    下一篇

基于最大隶属原则的核磁共振波谱模糊识别

王崇杰1*, 周小波1,孙丽媛2, 孙博1, 付颖1, 张占南1,许永廷3,冯春梁4   

  1. 1.  辽宁师范大学 物理与电子技术学院,辽宁 大连 116029; 2. 沈阳航空工业大学 理学院,辽宁 沈阳 110136; 3. 辽宁师范大学 分析测试中心,辽宁 大连 116029; 4. 辽宁师范大学 化学与化工学院,辽宁 大连 116029
  • 收稿日期:2010-07-27 修回日期:2010-11-18 出版日期:2011-06-05 发布日期:2011-06-05
  • 基金资助:

    国家自然科学基金资助项目(60572009), 辽宁省科技基金资助项目(99102004).

Fuzzy Recognition of NMR Spectra Based on the Maximum Principle of Membership

 WANG Chong-Jie1*,ZHOU Xiao-Bo1, SUN Li-Yuan2, SUN Bo1, FU Ying1, ZHANG Zhan-Nan1, XU Yong-Ting3, FENG Chun-Liang4   

  1. 1. College of Physics and Electric Technology, Liaoning Normal University, Dalian 116029, China;
    2. College of Science, Aeronautical Engineering University of Shenyang, Shenyang 110136, China;
    3. Center of Analysis and Test, Liaoning Normal University, Dalian 116029, China;
    4. College of Chemistry and Chemical Industry, Liaoning Normal University, Dalian 116029, China
  • Received:2010-07-27 Revised:2010-11-18 Online:2011-06-05 Published:2011-06-05
  • Supported by:

    国家自然科学基金资助项目(60572009), 辽宁省科技基金资助项目(99102004).

摘要:

介绍了基于最大隶属原则的核磁共振(NMR)波谱模糊识别原理与方法. 提出了关于核磁共振波谱模糊集合的概念,并给出了相应的隶属函数. 通过建立标准谱数据库和相应的模糊识别算法,实现了核磁共振波谱的快速自动定性分析. 对苯酚、邻苯二酚、间苯二酚及对苯二酚4种化合物及其11种混合物样品的1H NMR谱进行了定性分析. 结果表明,在粗略找峰和隶属度阈值在0.45~0.85之间较大范围内取值的情况下,方法均给出了准确的识别结果.

关键词: 核磁共振(NMR), 模糊识别, 最大隶属原则, 谱峰, 化学位移

Abstract:

The principle and method of fuzzy recognition of NMR spectra based on maximum principle of membership were reviewed. The concept of fuzzy set for NMR spectra was first introduced, and then the membership function was given. By establishing library of standard compounds and algorithm of fuzzy recognition, a quick automatic qualitative analysis was achieved. 1H NMR spectra of 11 mixed samples composed of 4 compounds were analyzed. The results show that the compounds in the samples can be recognized accurately even when the peak positions were only calculated roughly, and the threshold of average membership took value from 0.45~0.85.

Key words: NMR, fuzzy recognition, maximum principle of membership, spectra peaks, chemical shift

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