Volume 35 Issue 8
Turn off MathJax
Article Contents
Abstract
Related Articles
ZHANG Li, WANG Ru-Lin, WANG Ying, HE Yu-Kai. Research of Detection Model of Mine-used Infrared Gas Sensor Based on Neural Network[J]. Journal of Mine Automation, 2009, 35(8): 18-21.
Citation: ZHANG Li, WANG Ru-Lin, WANG Ying, HE Yu-Kai. Research of Detection Model of Mine-used Infrared Gas Sensor Based on Neural Network[J]. Journal of Mine Automation, 2009, 35(8): 18-21.
shu

Research of Detection Model of Mine-used Infrared Gas Sensor Based on Neural Network

  • Institute of Mechanical Electronic and Information Engineering of CUMT(Beijing).,Beijing 100083,China

More Information
    Graphical Abstract
    • Abstract
  • The paper briefly introduced the principle of gas infrared detection and pointed out existing problems of traditional absorption model.It established a detection model of infrared gas sensor based on nonlinear approximation capability of RBF neural network,gave the structure of the RBF neural network,and trained the RBF neural network,then obtained RBF neural network structure of the detection model of infrared gas sensor.The experiment results showed that the model has small error and high accurate,which can meet the requirements of mine application.
    • FullText(HTML)
    • References (0)
    • Related Articles

  • Related Articles

    [1]LI Yingna, CUI Yanping, AN Boshuo, LIU Baijian, JIN Jianwei. Research on the roadheader cutting control system based on convolutional neural network and fuzzy PID[J]. Journal of Mine Automation, 2025, 51(1): 61-70, 137. DOI: 10.13272/j.issn.1671-251x.2024070084
    [2]WANG Zhongju, LI Xuanrui, WANG Jinfeng. Intelligent remote centralized control and cutting system for roadheader[J]. Journal of Mine Automation, 2022, 48(S1): 95-96.
    [3]GUO Xijin, SHAO Hongqing, YANG Chunbao, ZHANG Zhiqiang. Research on PFC-PID control algorithm of density and liquid level in heavy medium suspensio[J]. Journal of Mine Automation, 2018, 44(1): 89-95. DOI: 10.13272/j.issn.1671-251x.2017030088
    [4]SUN Xiao-xi, HUANG You-rui, QU Li-guo. Research of time-delay control of wireless network based on RBF neural network PID control[J]. Journal of Mine Automation, 2013, 39(12): 76-81. DOI: 10.7526/j.issn.1671-251X.2013.12.019
    [5]LIU Jie, YANG Hai-qun. Application research of wavelet neural network and PID in maximum power point tracking of wind power system[J]. Journal of Mine Automation, 2013, 39(12): 73-76. DOI: 10.7526/j.issn.1671-251X.2013.12.018
    [6]GUO Xing-ge, WU Jiao-jiao, LIU Jing, SUN Li. Self-tuning fault-tolerant PID control for mine hoist based on BP neural network[J]. Journal of Mine Automation, 2013, 39(6): 45-48.
    [7]AN Feng, LI CAI-yun, WU Xiao-jun, MENG Xin, XUE Pu-chang. Design of PID Controller of Electro-hydraulic Servo System for Running Deviation of Strip Coiler[J]. Journal of Mine Automation, 2009, 35(7): 79-82.
    [8]FU Hua, LI Da-zhi. PID Self-tuning Control System Based on Neural Network[J]. Journal of Mine Automation, 2009, 35(7): 72-75.
    [9]LIU Shi-xian, ZHU Hua, WANG Yong, ZHU Feng-pei. Design of Control System of Emulsion Liquid Level Based on Fuzzy-PID Control[J]. Journal of Mine Automation, 2009, 35(4): 17-19.
    [10]LI Zu-xin , ZHANG Yu-feng , SHI Xin-ling . A New P-FUZZY-PID Controller with Switching Based on Fuzzy Rules[J]. Journal of Mine Automation, 2003, 29(1): 4-6.

Catalog

    Get Citation
    PDF
    XML

    Article Metrics

    Article views (23) PDF downloads (8) Cited by()
    Related

    苏ICP备 05016349号-2

    Supported by: Beijing Renhe Information Technology Co., Ltd. Visits：1150662    Baidu Analytics

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return