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Research on High Performance Methane Gas Concentration Sensor Based on Pyramid Beam Splitter Matrix.
Wang, Boqiang; Zhao, Xuezeng; Zhang, Yiyong; Wang, Zhuogang.
Afiliação
  • Wang B; School of Mechatonics Engineering, Harbin Institute of Technology, Harbin 150006, China.
  • Zhao X; 703 Research Institute, China State Shipbuilding Corporation Limited, Harbin 150010, China.
  • Zhang Y; School of Mechatonics Engineering, Harbin Institute of Technology, Harbin 150006, China.
  • Wang Z; School of Mechatonics Engineering, Harbin Institute of Technology, Harbin 150006, China.
Sensors (Basel) ; 24(2)2024 Jan 17.
Article em En | MEDLINE | ID: mdl-38257694
ABSTRACT
Methane gas concentration detection faces the challenges of increasing accuracy and sensitivity, as well as high reliability in harsh environments. The special design of the optical path structure of the sensitive element provides an opportunity to improve methane gas concentration detection. In this study, the optical path structure of the sensitive element was newly designed based on the Pyramidal beam splitter matrix. The infrared light source was modulated by multi-frequency point-signal superimposed modulation technology. At the same time, concentration detection results and confidence levels were calculated using the four-channel methane gas concentration detection algorithm based on spectral refinement. Through the experiment, it was found that the sensor enables the full-range measurement of CH4; at the lower explosive limit (LEL, CH4 LEL of 5%), the reliability level is 0.01 parts-per-million (PPM), and the limit of detection is 0.5 ppm. The sensor is still capable of achieving PPM-level detections under extreme conditions in which the sensor's optical window is covered by two-thirds and humidity is 85% or dust concentration is 100 mg/m3. Those improve the sensitivity, robustness, reliability, and accuracy of the sensor.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article