文献类型：会议论文

英文题名：Recognition of Acoustic Effective Relaxational Lines for Gas Detection Using Minimum Distance Clustering

作者：Zhang, Kesheng Guo, Xiaoxue Hu, Wensheng Ou, Weihua

第一作者：张克生

通信作者：Zhang, KS[1]

机构：[1]Guizhou Inst Technol, Sch Elect & Informat Engn, Guiyang 550003, Peoples R China;[2]Guizhou Normal Univ, Sch Big Data & Comp Sci, Guiyang 550001, Guizhou, Peoples R China

第一机构：贵州理工学院

通信机构：corresponding author), Guizhou Inst Technol, Sch Elect & Informat Engn, Guiyang 550003, Peoples R China.|贵州理工学院;

会议论文集：International Conference on Security, Pattern Analysis, and Cybernetics (ICSPAC)

会议日期：DEC 15-17, 2017

会议地点：Shenzhen, PEOPLES R CHINA

语种：英文

外文关键词：Minimum distance clustering; Acoustic Effective Relaxational Lines; Gas Detection; Recognition Analysis

年份：2017

摘要：Acoustic propagation characteristics, i.e., the frequency-dependent sound speed and absorption depend upon the composition of the gas. The position of an acoustic absorption peak can be synthesized by the measured acoustic propagation characteristics at two frequencies. In this paper, we propose a sensing method based on the minimum distance clustering to recognize acoustic effective relaxational Lines, which are composed of acoustic absorption spectral peaks, for gas concentration detection. Simulation results demonstrate that the proposed method can extract the information of gas concentration and environmental temperature from the recognized acoustic effective relaxational Lines.