Study of HF Gas Detection in Electrical Equipment by TDLAS Technology

被引:0
|
作者
Zhang, Shiling [1 ]
Hu, Xiaorui [1 ]
Li, Xintian [2 ]
Yue, Yunqi [2 ]
机构
[1] Chongqing Elect Power Res Inst, State Grid Chongqing Elect Power Co, Chongqing, Peoples R China
[2] Henan Prov Rilixin Private Aviat Co, Zhengzhou, Henan, Peoples R China
来源
PROCEEDINGS OF 2019 IEEE 8TH JOINT INTERNATIONAL INFORMATION TECHNOLOGY AND ARTIFICIAL INTELLIGENCE CONFERENCE (ITAIC 2019) | 2019年
关键词
optical cavity design; on-line monitoring; characteristic gas spectrum; absorption peak wavelength;
D O I
10.1109/itaic.2019.8785790
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The schematic diagram of the optical cavity design has been introduced in detail, meanwhile, the principle of measuring gas concentration with optical resonator is also introduced. Using the optical cavity spectroscopy technology, the gas component detection system is set up to realize high precision on-line monitoring of gas components such as HF. The detection system uses narrow line-width semiconductor laser to select the characteristic gas spectrum and output the absorption peak wavelength. Three kinds of gas concentration are measured by time division multiplexing, and the on-line sampling device of closed loop gas is integrated to complete the monitoring platform of high precision. The system needs the saw-tooth wave of 1Hz, which can be generated by internal DA of ADSP-403. At the same time, the system needs a modulation signal of about 5kHz, and the debugging signal with such high frequency can not be generated by DA of micro-controller itself. The system uses DDS generator AD9850 to generate sinusoidal modulation signal which is superimposed on the saw-tooth wave to drive the laser. The paper has developed the SF6 composition monitoring device based on optical attenuation technology, which provides the new research method for the on-line monitoring of gas components such as HF with the high accuracy of 3ppm.
引用
收藏
页码:103 / 107
页数:5
相关论文
共 50 条
  • [22] A TDLAS gas detection method based on digital signal modulation
    Zhang, Lei
    Dai, Xin
    Zhang, Weihua
    Wang, Wenqing
    Liu, Xiaochen
    Li, Wenbo
    OPTICS COMMUNICATIONS, 2025, 574
  • [23] Study of vehicle exhaust detection based on TDLAS
    Zhang Kexin
    Zhu Weimin
    Zhao Jie
    Lu Jinyu
    Liu Tao
    OPTICAL METROLOGY AND INSPECTION FOR INDUSTRIAL APPLICATIONS VI, 2019, 11189
  • [24] Study on the Intelligent Analysis Method of the Infrared Detection of Electrical Equipment
    Xin Jianbo
    Kang Chen
    Chen Tian
    Fu Xiaohua
    Zhou Longwu
    2018 3RD INTERNATIONAL CONFERENCE ON SMART CITY AND SYSTEMS ENGINEERING (ICSCSE), 2018, : 500 - 504
  • [25] Based on TDLAS Technology Gas Concentration Calibration Algorithm for a Large Range
    Ju Yu
    Chen Hao
    Han Li
    Chang Yang
    Zhang Xue-jian
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2020, 40 (12) : 3665 - 3669
  • [26] Insulation Defect Detection of Electrical Equipment Based on Infrared and Ultraviolet Photoelectric Sensing Technology
    Gao, Kai
    Lyu, Lijun
    Huang, Hua
    Fu, ChenZhao
    Chen, Fuchun
    Jin, Lijun
    45TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY (IECON 2019), 2019, : 2184 - 2189
  • [27] Online detection technology for SF6 decomposition products in electrical equipment: a review
    Fan, Xiaopeng
    Li, Li
    Zhou, Yongyan
    Tang, Nian
    Zou, Zhuanglei
    Li, Xiaodian
    Huang, Guojun
    Liu, Mingzheng
    IET SCIENCE MEASUREMENT & TECHNOLOGY, 2018, 12 (06) : 707 - 711
  • [28] Research on CO concentration detection based on deep learning and TDLAS technology
    Wang, Yinsong
    Chen, Shixiong
    Kong, Qingmei
    Gao, Jianqiang
    OPTICS AND LASERS IN ENGINEERING, 2024, 181
  • [29] Methane Concentration Detection System for Cigarette Smoke Based on TDLAS Technology
    Yang Ke
    Zhang Long
    Wu Xiao-song
    Li Zhi-gang
    Wang An
    Liu Yang
    Ji Min
    SPECTROSCOPY AND SPECTRAL ANALYSIS, 2015, 35 (12) : 3310 - 3314
  • [30] Design of Pump Suction Ammonia Detection Device based on TDLAS Technology
    Zhang Wei
    Gao Xingxing
    Tan Qing
    Xiao Jin
    Fang Xiancai
    Gen Xueming
    PROCEEDINGS OF 2017 IEEE 2ND INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC), 2017, : 1323 - 1327