Characteristic parameters measurement based on flow noise decoupling in horizontal slug flow

doi:10.16085/j.issn.1000-6613.2023-1383

Abstract

Abstract:

Slug flow is a typical two-phase flow pattern of gas-liquid intermittent flow. The measurement of gas slug characteristic parameters is of great significance for the measurement of abrasion pressure drop in slug flow, sectional void fraction, and other flow parameters. In this paper, a gas slug parameter measurement sensor based on the acoustic emission principle was designed, and the noise signals of horizontal pipe slug flow under different flow conditions were measured. Whale optimization algorithm (WOA) was employed to optimize the variational modal decomposition (VMD) for noise signal processing. By analyzing the original signal from the perspectives of energy and entropy, the decoupling of noise signals from the horizontal pipe slug flow was achieved. The noise signals were divided into high-frequency gas-solid noise, medium-frequency gas-liquid noise, and low-frequency liquid-solid noise. The measurement of gas slug frequency and slug length was realized by analyzing the time-domain signals of acoustic emission. The CatBoost algorithm was used to select 8 feature values to construct predictive models for slug flow slug frequency and slug length. The mean absolute percentage error (MAPE) of the slug frequency prediction model was 5.12%, and the relative deviations of 95.25% of experimental points were within the range of ±15%. The mean absolute percentage error (MAPE) of the slug length prediction model was 7.77%, and the relative deviations of 90.48% of experimental points were within the range of ±15%.

Key words: slug frequency, slug length, acoustic emission, flow noise, energy, entropy

摘要：

弹状流是一种典型的气液两相间歇流动形态，气弹特性参数的测量对于弹状流摩擦压降和截面含气率等流动参数测量具有重要意义。本文设计了基于声发射原理的气弹参数测量传感器，并对不同流动条件下的水平管弹状流噪声信号进行了测量。利用鲸鱼优化算法（WOA）变分模态分解（VMD）对噪声信号进行处理，结合原始信号从能量和熵的角度进行分析，完成了对水平管弹状流噪声信号的解耦。将噪声信号分解为高频的气固噪声、中频的气液噪声与低频的液固噪声。通过对声发射时域信号分析实现了弹状流频率与气弹长度参数的测量。利用CatBoost算法选取8个特征值构建了弹状流气弹频率和气弹长度的预测模型。实验结果表明，弹状流频率预测模型平均绝对百分比误差（MAPE）为5.12％，95.25％实验点的相对偏差都在±15％范围内，气弹长度预测模型MAPE为7.77％，90.48％实验点的相对偏差都在±15％范围内。

关键词: 弹频, 气弹长度, 声发射, 流动噪声, 能量, 熵

CLC Number:

TK313

LI Xinlong, ZHANG Zhao, WANG Jiahui, ZHANG Yansheng, DONG Fang. Characteristic parameters measurement based on flow noise decoupling in horizontal slug flow[J]. Chemical Industry and Engineering Progress, 2024, 43(2): 781-790.

李新龙, 张昭, 王嘉辉, 张延胜, 董芳. 基于流动噪声解耦的水平管弹状流气弹特性参数测量[J]. 化工进展, 2024, 43(2): 781-790.

Figures/Tables 17

系统压力 /MPa	温度 /℃	气相表观流速 /m·s^-1	液相表观流速 /m·s^-1	工况点
0.105	20.2	0.849~1.132	0.283~1.273	105

特征值	公式
最大值x(max)	$x m a x = a r g m a x x$
最小值x(min)	$x m i n = a r g m i n x$
平均值（ $x ¯$ ）	$x ¯ = 1 n ∑ i = 1 n x i$
标准差（Std）	$S t d = ∑ i = 1 n (x i - x ¯) 2 n - 1 12$
偏斜度（Skewness）	$S k e w n e s s = 1 n - 1 ∑ i = 1 n (x i - x ¯) 3 S D 3$
峭度（Kurtosis）	$K u r t o s i s = 1 n - 1 ∑ i = 1 n (x i - x ¯) 4 S D 3 - 3$

特征值	公式
最大值x(max)	$x m a x = a r g m a x x$
最小值x(min)	$x m i n = a r g m i n x$
平均值（ $x ¯$ ）	$x ¯ = 1 n ∑ i = 1 n x i$
标准差（Std）	$S t d = ∑ i = 1 n (x i - x ¯) 2 n - 1 12$
偏斜度（Skewness）	$S k e w n e s s = 1 n - 1 ∑ i = 1 n (x i - x ¯) 3 S D 3$
峭度（Kurtosis）	$K u r t o s i s = 1 n - 1 ∑ i = 1 n (x i - x ¯) 4 S D 3 - 3$

序号	参数	参数介绍	输入
1	Loss function	损失函数	RMSE
2	Iterations	最大树数	100
3	Learning rate	学习率	0.05
4	Depth	树的深度	5
5	Random seed	随机种子数	99
6	Od type	过拟合检测类型	Iter
7	Od wait	达成优化目标以后继续迭代的次数	50

References 23

1	MOHMMED A O, AL-KAYIEM H H, NASIF M S, et al. Effect of slug flow frequency on the mechanical stress behavior of pipelines[J]. International Journal of Pressure Vessels and Piping, 2019, 172: 1-9.
2	MOHMMED A O, AL-KAYIEM H H, OSMAN A B. Investigations on the slug two-phase flow in horizontal pipes: Past, presents, and future directives[J]. Chemical Engineering Science, 2021, 238: 116611.
3	KIM Hyeong-Geun, KIM Sung-Min. Experimental investigation of flow and pressure drop characteristics of air-oil slug flow in a horizontal tube[J]. International Journal of Heat and Mass Transfer, 2022, 183(PA): 122063.
4	WILKENS R J, THOMAS D K. A simple technique for determining slug frequency using differential pressure[J]. Journal of Energy Resources Technology, 2008, 130(1): 014501.
5	BERTOLA V, CAFARO E. Slug frequency measurement techniques in horizontal gas-liquid flow[J]. AIAA Journal, 2002, 40: 1010-1012.
6	王长亮, 靳遵龙, 王永庆, 等. 微通道气液两相流研究进展[J]. 化工进展, 2017, 36(S1): 1-7.
	WANG Changliang, JIN Zunlong, WANG Yongqing, et al. Research progress of gas-liquid two-phase flow in micro-channels[J]. Chemical Industry and Engineering Progress, 2017, 36(S1): 1-7.
7	唐静, 张旭斌, 蔡旺锋, 等. 微通道内液-液两相流研究进展[J]. 化工进展, 2013, 32(8): 1743-1748.
	TANG Jing, ZHANG Xubin, CAI Wangfeng, et al. Research progress of liquid-liquid two-phase flow in microchannels[J]. Chemical Industry and Engineering Progress, 2013, 32(8): 1743-1748.
8	陈蔚阳, 宋欣, 殷亚然, 等. 矩形微通道内液相黏度对气泡界面的作用机制[J]. 化工进展, 2023, 42(7): 3468-3477.
	CHEN Weiyang, SONG Xin, YIN Yaran, et al. Effect of liquid viscosity on bubble interface in the rectangular microchannel[J]. Chemical Industry and Engineering Progress, 2023, 42(7): 3468-3477.
9	AL-KAYIEM H H, MOHMMED A O, AL-HASHIMY Z I, et al. Statistical assessment of experimental observation on the slug body length and slug translational velocity in a horizontal pipe[J]. International Journal of Heat and Mass Transfer, 2017, 105: 252-260.
10	CAZAREZ-CANDIA O, BENÍTEZ-CENTENO O C. Comprehensive experimental study of liquid-slug length and Taylor-bubble velocity in slug flow[J]. Flow Measurement and Instrumentation, 2020, 72: 101697.
11	ARCHIBONG-ESO A, BABA Y, ALIYU A, et al. On slug frequency in concurrent high viscosity liquid and gas flow[J]. Journal of Petroleum Science and Engineering, 2018, 163: 600-610.
12	ZHAI Lusheng, XU Bo, XIA Haiyan, et al. Simultaneous measurement of velocity profile and liquid film thickness in horizontal gas-liquid slug flow by using ultrasonic Doppler method[J]. Chinese Journal of Chemical Engineering, 2023, 58: 323-340.
13	BAENSCH F, BAER W, WOSSIDLO P, et al. Damage evolution detection in a pipeline segment under bending by means of acoustic emission[J]. International Journal of Pressure Vessels and Piping, 2023, 201: 104863.
14	ZHANG Han, LIN Zhenyuan. Analytical solution of acoustic emission in soft material with cracks by using reciprocity theorem[J]. Engineering Fracture Mechanics, 2023, 277: 108996.
15	FANG Lide, LIANG Yujiao, LU Qinghua, et al. Flow noise characterization of gas-liquid two-phase flow based on acoustic emission[J]. Measurement, 2013, 46(10): 3887-3897.
16	HII N C, TAN C K, WILCOX S J, et al. An investigation of the generation of acoustic emission from the flow of particulate solids in pipelines[J]. Powder Technology, 2013, 243: 120-129.
17	HUSIN S, ADDALI A, MBA D. Feasibility study on the use of the acoustic emission technology for monitoring flow patterns in two phase flow[J]. Flow Measurement and Instrumentation, 2013, 33: 251-256.
18	ZHAO Ning, LI Chaofan, JIA Huijun, et al. Acoustic emission-based flow noise detection and mechanism analysis for gas-liquid two-phase flow[J]. Measurement, 2021, 179: 109480.
19	ZHOU Yefeng, YANG Lei, LU Yujian, et al. Flow regime identification in gas-solid two-phase fluidization via acoustic emission technique[J]. Chemical Engineering Journal, 2018, 334: 1484-1492.
20	HAN Li, JING Huitian, ZHANG Rongchang, et al. Wind power forecast based on improved long short term memory network[J]. Energy, 2019, 189: 116300.
21	WANG Xin, GUO Liejin, ZHANG Ximin. An experimental study of the statistical parameters of gas-liquid two-phase slug flow in horizontal pipeline[J]. International Journal of Heat and Mass Transfer, 2007, 50(11/12): 2439-2443.
22	BENDIKSEN K H. An experimental investigation of the motion of long bubbles in inclined tubes[J]. International Journal of Multiphase Flow, 1984, 10(4): 467-483.
23	DOROGUSH A V, ERSHOV V, GULIN A. CatBoost: Gradient boosting with categorical features support[EB/OL]. 2018: arXiv: 1810.11363. .

[1]	TIAN Shihong, GUO Lei, LI Na, YUWEN Chao, XU Lei, GUO Shenghui, JU Shaohua. Scientific basis and development trend of microwave heating enhanced flash evaporation process [J]. Chemical Industry and Engineering Progress, 2024, 43(1): 135-144.
[2]	ZENG Yue, WANG Yue, ZHANG Xuerui, SONG Xiwen, XIA Bowen, CHEN Ziqi. Research progress of green ammonia synthesis from renewable energy and economic analysis of hydrogen-ammonia storage and transportation [J]. Chemical Industry and Engineering Progress, 2024, 43(1): 376-389.
[3]	LI Jitong, WANG Gang, XIONG Yaxuan, XU Qian. Energy and exergy analysis of single-effect absorption refrigeration system with different refrigerants [J]. Chemical Industry and Engineering Progress, 2023, 42(S1): 104-112.
[4]	ZHANG Ruijie, LIU Zhilin, WANG Junwen, ZHANG Wei, HAN Deqiu, LI Ting, ZOU Xiong. On-line dynamic simulation and optimization of water-cooled cascade refrigeration system [J]. Chemical Industry and Engineering Progress, 2023, 42(S1): 124-132.
[5]	HU Yafei, FENG Ziping, TIAN Jiayao, SONG Wenji. Waste heat recovery performance of an air-source gas engine-driven heat pump system in multi-heating operation modes [J]. Chemical Industry and Engineering Progress, 2023, 42(8): 4204-4211.
[6]	WANG Jiansheng, ZHANG Huipeng, LIU Xueling, FU Yuguo, ZHU Jianxiao. Analysis of flow and heat transfer characteristics in porous media reservoir [J]. Chemical Industry and Engineering Progress, 2023, 42(8): 4212-4220.
[7]	WANG Shuaiqing, YANG Siwen, LI Na, SUN Zhanying, AN Haoran. Research progress on element doped biomass carbon materials for electrochemical energy storage [J]. Chemical Industry and Engineering Progress, 2023, 42(8): 4296-4306.
[8]	YE Zhendong, LIU Han, LYU Jing, ZHANG Yaning, LIU Hongzhi. Optimization of thermochemical energy storage reactor based on calcium and magnesium binary salt hydrates [J]. Chemical Industry and Engineering Progress, 2023, 42(8): 4307-4314.
[9]	YANG Pengwei, YU Linzhu, WANG Fangfang, JIANG Haoxuan, ZHAO Guangjin, LI Qi, DU Mingzhe, MA Shuangchen. Application prospect, challenge and development of ammonia energy storage in new power system [J]. Chemical Industry and Engineering Progress, 2023, 42(8): 4432-4446.
[10]	LI Yanling, ZHUO Zhen, CHI Liang, CHEN Xi, SUN Tanglei, LIU Peng, LEI Tingzhou. Research progress on preparation and application of nitrogen-doped biochar [J]. Chemical Industry and Engineering Progress, 2023, 42(7): 3720-3735.
[11]	ZHANG Kai, LYU Qiunan, LI Gang, LI Xiaosen, MO Jiamei. Morphology and occurrence characteristics of methane hydrates in the mud of the South China Sea [J]. Chemical Industry and Engineering Progress, 2023, 42(7): 3865-3874.
[12]	LIN Hai, WANG Yufei. Distributed wind farm layout optimization considering noise constraint [J]. Chemical Industry and Engineering Progress, 2023, 42(7): 3394-3403.
[13]	SUN Xudong, ZHAO Yuying, LI Shirui, WANG Qi, LI Xiaojian, ZHANG Bo. Textual quantitative analysis on China’s local hydrogen energy development policies [J]. Chemical Industry and Engineering Progress, 2023, 42(7): 3478-3488.
[14]	XUE Kai, WANG Shuai, MA Jinpeng, HU Xiaoyang, CHONG Daotong, WANG Jinshi, YAN Junjie. Planning and dispatch of distributed integrated energy systems for industrial parks [J]. Chemical Industry and Engineering Progress, 2023, 42(7): 3510-3519.
[15]	LI Jiyan, JING Yanju, XING Guoyu, LIU Meichen, LONG Yong, ZHU Zhaoqi. Research progress and challenges of salt-resistant solar-driven interface photo-thermal materials and evaporator [J]. Chemical Industry and Engineering Progress, 2023, 42(7): 3611-3622.