|
|
|
|
|
|
Experimental Study on the Void Fraction Determination of Gas-Oil Two-Phase Flow in Elbow Based on Spectral Analysis |
CHE Shao-min1, MA Shi-yi1, LIU Xue-jing1, YIN Xiong1, ZHOU Yan1*, XIONG Bing2, LI Kun2, LI Fei3 |
1. School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an 710049, China
2. AECC Sichuan Gas Turbine Establishment, Chengdu 610500,China
3. School of Electronic Engineering, Xi'an Shiyou University, Xi'an 710065, China
|
|
|
Abstract When air is entrained into the engine lubricating oil system to form an oil and gas two-phase flow, it will seriously affect the normal operation of the lubrication system. Therefore, it is very important to realize the accurate and rapid measurement of the void fraction of the oil-gas two-phase flow in the engine lubricating oil system. This paper determines the void fraction in the engine lubrication system at the elbow based on the spectral matching method. Firstly, the absorption data of oil-gas two-phase flow were obtained at two flow rates and five temperature conditions, covering a gas content range of 0.10% to 1.00% (with an interval of 0.06%). This was accomplished by utilizing near-infrared, visible, and ultraviolet spectrophotometers, followed by rigorous analysis. It was ascertained that the oil-gas two-phase flow demonstrates absorption across all three wavelengths, with the intensity of absorption being correlated to the gas content. Secondly, the data preprocessing method combined with spectral similarity measure is proposed and applied to the gas content spectral analysis of bent pipe, significantly reducing the maximum relative error of gas content prediction based on the original spectrum. Using data enhancement methods such as center and autoscaling combined with Spectral Angle Cosine methods in the near-infrared spectrum, the maximum relative error of the gas content of the new lubricating oil was reduced from 48% to 36% relative to the original spectrum. The method predicts the void fraction of gas-oil two-phase flow in three bands respectively. The experimental conditions include two flow rates and five temperatures, and the influence of the temperature and flow rate of the two-phase flow on the void fraction prediction is analyzed. At the temperature of 30.0 ℃ and the flow rate of 5.1 m·min-1, the gas content information in the ultraviolet band (193.5~413.8 nm) is more closely related to the spectral feature of the direction or shape difference of the spectral vector and the maximum relative error of the gas content prediction is only 6%. In the near-infrared and visible bands, the maximum relative error decreases with the increase of temperature or velocity when the flow rate or temperature is constant. There is no specific effect of temperature on the prediction of gas content in the ultraviolet band. With the increase of the two-phase flow rate, the maximum relative error of gas content prediction tends to increase. The results show that for new lubricating oil with good light transmittance, the gas content data is collected by the ultraviolet spectrometer, and the maximum relative error of gas content prediction is minimum by using standardized pretreatment combined with spectral Angle cosine method.
|
Received: 2024-03-12
Accepted: 2024-06-25
|
|
Corresponding Authors:
ZHOU Yan
E-mail: yan.zhou@mail.xjtu.edu.cn
|
|
[1] WEN Bing-gong, FENG Wu-fa, LIU Wei, et al(闻兵工, 冯伍法, 刘 伟,等). Journal of Geomatics Science and Technology(测绘科学技术学报), 2009, 26(2): 128.
[2] ZHANG Chang-xing, LIU Cheng-yu, QI Hong-xing, et al(张长兴, 刘成玉, 亓洪兴,等). Infrared and Laser Engineering(红外与激光工程), 2020, 49(1): 124.
[3] ZHANG Cong-zheng, XU Yi-qin, GU Zhi-liang, et al(张从征, 许毅钦, 古志良,等). Materials Research and Application(材料研究与应用), 2019, 13(1): 48.
[4] LI Hong-da, LI De-cheng, ZENG Rong(李宏达, 李德成, 曾 荣). Acta Pedologica Sinica(土壤学报), 2021, 58(5): 1224.
[5] HU Peng-fei, WANG Guang-cai, WANG Jing, et al(胡鹏飞, 王广才, 王 静,等). Automation & Instrumentation(自动化与仪器仪表), 2020,(7): 85.
[6] WANG Bao-ming(王宝明). Journal of Hebei University(Natural Science Edition)[河北大学学报(自然科学版)], 1992, 12(4): 75.
[7] AN Bin, CHEN Shu-hai, YAN Wei-dong(安 斌, 陈书海, 严卫东). Chinese Journal of Stereology and Image Analysis(中国体视学与图像分析), 2005, 10(1): 55.
[8] KONG Xiang-bing, SHU Ning, TAO Jian-bin, et al(孔祥兵, 舒 宁, 陶建斌,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2011, 31(8): 2166.
[9] FANG Sheng-hui, GONG Hao(方圣辉, 龚 浩). Geomatics and Information Science of Wuhan University(武汉大学学报·信息科学版), 2006, 31(12): 1044.
[10] ZHANG Jun-zhe, ZHU Wen-quan, DONG Yan-sheng, et al(张浚哲, 朱文泉, 董燕生,等). Acta Geodaetica et Cartographica Sinica(测绘学报), 2013, 42(3): 418.
[11] WEI Xiang-po, YU Xu-chu, FU Qiong-ying, et al(魏祥坡, 余旭初, 付琼莹,等). Geography and Geo-Information Science(地理与地理信息科学), 2016, 32(3): 29.
[12] WANG Zhan, WANG Ke, WANG Wei-chao(王 展, 王 可, 王伟超). Laser & Optoelectronics Progress(激光与光电子学进展), 2019, 56(2): 217.
[13] LIU Yi-cen, LIU Xi, YANG Lin, et al(刘益岑, 刘 曦, 杨 琳,等). The Journal of Light Scattering(光散射学报), 2023, 35(3): 296.
[14] YANG Wen-zong, TANG Xing-jia, ZHANG Peng-chang, et al(杨文宗, 唐兴佳, 张朋昌,等). Sciences of Conservation and Archaeology(文物保护与考古科学), 2023, 35(4): 11.
[15] GUO Ye-cai, CAO Jia-lu, HAN Ying-ying, et al(郭业才, 曹佳露, 韩莹莹,等). Acta Optica Sinica(光学学报), 2023, 43(20): 152.
[16] QI Hai-chao, SONG Yan-song, ZHANG Bo, et al(齐海超, 宋延嵩,张 博,等). Chinese Optics(中国光学), 2023,16(5):1056.
[17] Riahi S, Bahroudi A, Abedi M, et al. Geocarto International, 2023, 38(1):2159068.
[18] Paul R, Chakravortty S, Maitra S, et al. Journal of Food Science and Technology, 2024,61(7):1334.
[19] Aulich J, Chojniak D, Bett A J, et al. Solar RRL, 2024,8: 2300783.
[20] Harati M, Mashayekhi M, Mohammadnezhad H, et al. Earthquakes and Structures, 2021, 21(4): 425.
[21] Challagulla S P, Bhavani B D, Suluguru A K, et al. Current Science, 2023, 124(8): 928.
|
[1] |
XIE Xing1, CHENG Xin-peng1, ZHANG Lu1*, LUO Jing1, WANG Le-huai1, LIN Wen-jing1, LU Fei-yan1, TU Zong-cai1, 2*. Study on the Interaction Mechanism of Ellagic Acid and Urolisine A~D With HSA Based on Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2025, 45(01): 282-290. |
[2] |
WANG Fang-yuan1, 2, ZHANG Jing-yi1, 2, YE Song1, 2, LI Shu1, 2, WANG Xin-qiang1, 2*. Raman Signal Extraction Method Based on Full Spectrum Principal
Component Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(12): 3327-3332. |
[3] |
LIU Qing-song1, DU Wen-jing1, LUO Bo2, LI Kai-ge1, DAN You-quan1*, XU Luo-peng1, YANG Xiu-feng2, TANG Shen-lan1. Near Infrared Hyperspectral Identification of Surface Damage on Aircraft Wings[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3069-3074. |
[4] |
WANG Zi-le, ZHANG Zhe*, ZHANG Yun-xue, XIANG Si-meng, WEI Zhen-bo, WEN Sheng-you, WANG Zhan-shan. Fabrication and Characterization of Multilayer Analyzer Crystals for
X-Ray Fluorescence Analysis on Light Elements[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(11): 3120-3127. |
[5] |
LI Zhen-yu1, ZHAO Peng1, 2*, WANG Cheng-kun3. Tree Class Recognition in Open Set Based on an Improved Fuzzy
Reasoning Classifier[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1868-1876. |
[6] |
LI Yu-heng1, 2, 3, YANG Lu1, 2, 3*, GE Ruo-chen1, 2, 3. Study on the Interaction and Stability of Mixed Proteinaceous Binders in Polychrome Relics[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(07): 1946-1951. |
[7] |
WANG Yong-jun1, WU Gui-wen2*, HUANG He1, LI Tong-jun3. A Two-Stage Efficient Global Optimization Algorithm for Solving LED Spectral Matching Coefficient[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(06): 1591-1599. |
[8] |
LI Zhen, HOU Ming-yu, CUI Shun-li, CHEN Miao, LIU Ying-ru, LI Xiu-kun, CHEN Huan-ying, LIU Li-feng*. Rapid Detection Method of Flavonoid Content in Peanut Seed Based on Near Infrared Technology[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(04): 1112-1116. |
[9] |
WANG Peng1, 2, 3,WANG Zhen-ya2,WANG Shun2,ZHANG Jie2,ZHANG Zhe2,YANG Tian-hang2,WANG Bi-dou1, 2*,LUO Gang-yin1, 2*,WENG Liang-fei2,ZHANG Chong-yu3,LI Yuan3. Fluorescence Crosstalk Correction for Multiple Quantitative PCR Based on Principal Component Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(04): 1151-1157. |
[10] |
XU Jie1, 2, 3, GU Yi1, 2*, SONG Bao-lin1, 2, GE Liang-quan1, ZHANG Qing-xian1, YANG Wen-jia4. A Review of the Auxiliary Measurement of Nobble Gases in LIBS[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(03): 601-609. |
[11] |
SHUI Bi-wen1, 2, 3, SUN Man-li1, 2, YU Zong-ren3*, WANG Zhuo3, ZHAO Jin-li3, CUI Qiang3. Spectroscopic Analysis of the Mural's Materials in Prince Shi's Palace of the Taiping Heavenly Kingdom[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(02): 452-459. |
[12] |
YANG Chao-pu1, 2, FANG Wen-qing3*, WU Qing-feng3, LI Chun1, LI Xiao-long1. Study on Changes of Blue Light Hazard and Circadian Effect of AMOLED With Age Based on Spectral Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 36-43. |
[13] |
BAO Hao1, 2,ZHANG Yan1, 2*. Research on Spectral Feature Band Selection Model Based on Improved Harris Hawk Optimization Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 148-157. |
[14] |
FAN Ping-ping,LI Xue-ying,QIU Hui-min,HOU Guang-li,LIU Yan*. Spectral Analysis of Organic Carbon in Sediments of the Yellow Sea and Bohai Sea by Different Spectrometers[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 52-55. |
[15] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
|
|
|
|