中国物理B ›› 2016, Vol. 25 ›› Issue (2): 24201-024201.doi: 10.1088/1674-1056/25/2/024201

• ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS • 上一篇    下一篇

New pattern recognition system in the e-nose for Chinese spirit identification

Hui Zeng(曾慧), Qiang Li(李强), Yu Gu(谷宇)   

  1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  • 收稿日期:2015-07-14 修回日期:2015-08-31 出版日期:2016-02-05 发布日期:2016-02-05
  • 通讯作者: Yu Gu E-mail:guyu@ustb.edu.cn
  • 基金资助:
    Project supported by the National High Technology Research and Development Program of China (Grant No. 2013AA030901) and the Fundamental Research Funds for the Central Universities, China (Grant No. FRF-TP-14-120A2).

New pattern recognition system in the e-nose for Chinese spirit identification

Hui Zeng(曾慧), Qiang Li(李强), Yu Gu(谷宇)   

  1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
  • Received:2015-07-14 Revised:2015-08-31 Online:2016-02-05 Published:2016-02-05
  • Contact: Yu Gu E-mail:guyu@ustb.edu.cn
  • Supported by:
    Project supported by the National High Technology Research and Development Program of China (Grant No. 2013AA030901) and the Fundamental Research Funds for the Central Universities, China (Grant No. FRF-TP-14-120A2).

RichHTML

0

PDF (PC)

386

赞

摘要： This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (Sf), crest factor value (Cf), impulse factor value (If), clearance factor value (CLf), kurtosis factor value (Kv) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively.

关键词: new pattern recognition system, polymer quartz piezoelectric crystal sensor e-nose, principle components analysis (PCA), back propagation (BP) algorithm, Chinese spirit identification

Abstract: This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance (QCM) principle, and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an 8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value (A), root-mean-square value (RMS), shape factor value (Sf), crest factor value (Cf), impulse factor value (If), clearance factor value (CLf), kurtosis factor value (Kv) are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis (PCA) method. Finally the back propagation (BP) neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively.

Key words: new pattern recognition system, polymer quartz piezoelectric crystal sensor e-nose, principle components analysis (PCA), back propagation (BP) algorithm, Chinese spirit identification

中图分类号:  (Pattern recognition)

  • 42.30.Sy
43.60.Lq (Acoustic imaging, displays, pattern recognition, feature extraction) 07.07.Df (Sensors (chemical, optical, electrical, movement, gas, etc.); remote sensing)