An eight-channel-based near infrared void fraction measurement system using T-ART algorithm

• Published in: Optics and lasers in engineering Vol. 161; p. 107385
• Main Authors: Fang, Lide, Yuan, Xinyue, Zhang, Zhenyu, Zhou, Cong, Li, Honglian, Chen, Mingjing, Lan, Kang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.02.2023
• Subjects: Iterative reconstruction algorithm; Near-infrared tomography; Sensor optimization; Void fraction; Void fraction; Sensor optimization; Iterative reconstruction algorithm; Near-infrared tomography
• ISSN: 0143-8166; 1873-0302
• DOI: 10.1016/j.optlaseng.2022.107385

•An eight-channel array sensor is designed based on the principle of the near-infrared optical tomography system.•The void fraction of the stratified flow was analysed based on Tikhonov for a priori information and algebra reconstruction technique fusion (T-ART). and void fraction of the flow pattern measured by the algorithm is compared with the void fraction obtained by the Particle Image Velocimetry (PIV) technique.•The void fraction was evaluated with type A evaluation of uncertainty and the result was 0.787±0.0964 indicating that the measurement results were accurate and reliable. The testing of gas-liquid two-phase flow parameters is of great importance for product quality assessment, cost reduction, and production safety. In this paper, an eight-channel array sensor is designed based on the principle of the near-infrared optical tomography system. The void fraction of the stratified flow was analysed based on Tikhonov for a priori information and Algebra Reconstruction Technique fusion (T-ART). and void fraction of the flow pattern measured by the algorithm is compared with the void fraction obtained by the Particle Image Velocimetry (PIV) technique. Finally, the void fraction was evaluated with type A evaluation of uncertainty and the result was 0.787±0.0964 indicating that the measurement results were accurate and reliable.