采用改进极限学习机的混合气体浓度检测方法  

The Detection Method of Mixed Gas Concentration Using Improved Extreme Learning Machine

作　　者：王印松[1] 李震 孔庆梅 高建强[1] Wang Yinsong;Li Zhen;Kong Qingmei;Gao Jianqiang(Department of Automation,North China Electric Power University,Baoding 071003,Hebei,China)

机构地区：[1]华北电力大学自动化系,河北保定071003

出　　处：《应用激光》2024年第11期102-110,共9页Applied Laser

摘　　要：针对现有混合气体浓度检测方法精度较低、易受环境影响等问题,结合可调谐半导体激光吸收光谱(TDLAS)技术,提出一种基于改进灰狼算法优化极限学习机(TGWO-ELM)的混合气体浓度检测方法。针对混合气体光谱信息大样本、多维度的数据特性,采用极限学习机反演气体浓度,利用灰狼优化算法解决极限学习机初始权值与偏置随机生成导致的稳定性差等问题,并改进收敛因子衰减公式缩短算法训练时间。通过模拟中心波长为1580 nm的单激光器对CO与CO_(2)混合气体进行大浓度差实验与变温况仿真实验,检测误差可稳定在0.003%左右。实验表明,TGWO-ELM算法可有效提高混合气体检测精度、稳定性与响应速度,具有较高的工程应用价值。This paper addresses the issues of low accuracy and environmental susceptibility in existing methods for detecting mixed gas concentrations by proposing a method based on the improved TGWO-ELM(Teaching-Guided Firefly Algorithm optimized Extreme Learning Machine)algorithm,integrated with Tunable Diode Laser Absorption Spectroscopy(TDLAS)technology.The method leverages the extreme learning machine for gas concentration retrieval and employs the TGWO algorithm to mitigate stability issues stemming from the initial weights of the extreme learning machine and the random generation of offsets.The convergence factor′s attenuation formula is also improved to reduce algorithm training time.By simulating a single laser with the central wavelength of 1580nm,the large concentration difference experiment and the experiment of changing temperature condition are carried out for the mixed gas of CO and CO_(2),and the detection error can be stabilized at about 0.003%.Experiments show that the TGWO-ELM algorithm can effectively improve the detection accuracy,stability and response speed of mixed gas,and has high engineering application value.

关 键 词：可调谐半导体激光吸收光谱 混合气体 极限学习机 温度补偿 

分 类 号：TN249[电子电信—物理电子学]