基于双侧阵列电极的电阻抗成像原位膜污染监测

doi:10.11949/0438-1157.20230911

化工学报 ›› 2023, Vol. 74 ›› Issue (11): 4720-4729.DOI: 10.11949/0438-1157.20230911

基于双侧阵列电极的电阻抗成像原位膜污染监测

齐欣欣¹^,²(), 贾辉¹^,²^,³(), 高菲¹^,², 王琦⁴, 尹延梅⁵, 王捷¹^,²^,³

^1.天津工业大学环境科学与工程学院，天津 300387
^2.天津市水质安全评价与保障技术工程中心，天津 300387
^3.天津工业大学沧州研究院，河北沧州 061000
^4.天津工业大学电子与信息工程学院，天津 300387
^5.世韩（天津）节能环保科技有限公司，天津 300384

收稿日期:2023-09-01 修回日期:2023-11-08 出版日期:2023-11-25 发布日期:2024-01-22
通讯作者: 贾辉
作者简介:齐欣欣（2002—），女，硕士研究生，xininqi@163.com
基金资助:
国家自然科学基金面上项目(51978464);天津市科技计划项目(22ZXSYSY00010);天津工业大学沧州研究院资助项目(TGCYY-F-0103)

In situ monitoring of membrane fouling by electrical impedance tomography based on bilateral array electrodes

Xinxin QI¹^,²(), Hui JIA¹^,²^,³(), Fei GAO¹^,², Qi WANG⁴, Yanmei YIN⁵, Jie WANG¹^,²^,³

^1.School of Environmental Science and Engineering, Tiangong University, Tianjin 300387, China
^2.Tianjin Engineering Centre for Safety Evaluation of Waiter Quality & Safeguards Technology, Tianjin 300387, China
^3.Cangzhou Institute of Tiangong University, Cangzhou 061000, Hebei, China
^4.School of Electronics and Information Engineering, Tiangong University, Tianjin 300387, China
^5.Shihan (Tianjin) Energy Conservation and Environmental Protection Technology Co. , Ltd. , Tianjin 300384, China

Received:2023-09-01 Revised:2023-11-08 Online:2023-11-25 Published:2024-01-22
Contact: Hui JIA

摘要/Abstract

摘要：

基于电阻抗成像（electrical impedance tomography，EIT）技术设计了一种双侧阵列电极的膜污染原位监测装置，并应用于动态膜污染过程监测。通过模拟和实验比较了单侧和双侧电极阵列的成像效果。结果表明：电极双侧阵列方式依靠离子流动和外界电流产生额外电势差，监测更灵敏，重建图像与真实图像之间的相关系数0.89，能够更准确获得污染物信息。以高岭土、海藻酸钠（SA）和湖水为污染物，探究了不同污染物在超滤膜面的污染过程，得到了通量和膜污染成像图。结果表明，高岭土污染先集中于进水口附近，之后向中间区域和出水口迁移；湖水絮凝污染物主要分布在出水口附近；SA污染主要集中在进水口附近区域。建立了阻抗变化和污染物厚度之间关系，结果显示随厚度增大，阻抗变化增长速率也增大。

关键词: 超滤, 膜污染, 电阻抗成像, 监测

Abstract:

Based on electrical impedance tomography (EIT) technology, a membrane fouling in situ monitoring device with bilateral array electrodes was designed and applied to dynamic membrane fouling process monitoring. The electrode bilateral array method relies on the ion flow and external current to generate additional potential difference, which makes the monitoring more sensitive, and the correlation coefficient between the reconstructed image and the real image is 0.89, which enables more accurate information about the fouling to be obtained. Using kaolin, sodium alginate (SA) and lake water as model foulants, the different fouling characteristics of ultrafiltration (UF) membrane surface were explored, and flux changes and membrane fouling imaging were obtained. The results showed that kaolin was first concentrated near the inlet, and then migrated to the intermediate region and outlet, flocculated lake water was mainly distributed near the outlet, and SA was mainly concentrated in the inlet. The quantitative relationship between impedance change and the thickness was obtained by reconstructing images from EIT signals. The results showed that the rate of growth of impedance change values increased with increasing thickness.

Key words: ultrafiltration, membrane fouling, electrical impedance tomography, monitoring

中图分类号:

X 524

齐欣欣, 贾辉, 高菲, 王琦, 尹延梅, 王捷. 基于双侧阵列电极的电阻抗成像原位膜污染监测[J]. 化工学报, 2023, 74(11): 4720-4729.

Xinxin QI, Hui JIA, Fei GAO, Qi WANG, Yanmei YIN, Jie WANG. In situ monitoring of membrane fouling by electrical impedance tomography based on bilateral array electrodes[J]. CIESC Journal, 2023, 74(11): 4720-4729.

图/表 8

图1 (a)实验装置图；(b)单侧电极评价池分解示意图；(c)双侧电极评价池分解示意图

Fig.1 (a) Experimental device diagram; (b) Schematic diagram of the decomposition of the evaluation cell for the unilateral electrode design; (c) Schematic diagram of the decomposition of the evaluation cell for the bilateral electrode design

图2 EIT 膜污染检测原理示意图

Fig.2 Schematic diagram of the principle of EIT to monitor membrane fouling

图3 单侧、双侧电极仿真

Fig. 3 Unilateral and bilateral electrode simulation

图4 高岭土污染单、双侧监测成像图和实物图对比

Fig. 4 Comparison of single and dual side monitoring imaging and physical maps of kaolin contamination

图5 60 min内溶液污染监测

Fig.5 Fouling monitoring of solution within 60 min

图6 60 min内湖水过滤通量下降和污染监测

Fig.6 Decrease of filtration flux in lake water and fouling monitoring in 60 min

图7 取样点信息及厚度测量和拟合结果

Fig.7 Sampling point information, thickness measurement and fitting results

表1 测试样本拟合数据计算结果

Table 1 Calculation results of fitted data for test samples

样本点	厚度/μm	真实值/Ω	拟合值/Ω	相对误差/%
平均相对误差				4.70
10	442.52	3.01×10^-3	2.86×10^-3	4.94
11	347.05	1.54×10^-3	1.59×10^-3	3.34
12	187.05	4.77×10^-4	4.49×10^-4	5.82

参考文献 33

1	Scholes C. Advanced membrane technology and applications[J]. Chemistry in Australia,2011,78(2): 33.
2	Ismail A F, Matsuura T. Membrane Technology for Water and Wastewater Treatment, Energy and Environment[M]. Boca Raton: CRC Press,2016.
3	Wang S, Liang S, Liang P, et al. In-situ combined dual-layer CNT/PVDF membrane for electrically-enhanced fouling resistance[J]. Journal of Membrane Science, 2015, 491: 37-44.
4	Kang G D, Cao Y M. Development of antifouling reverse osmosis membranes for water treatment: a review[J]. Water Research, 2012, 46(3): 584-600.
5	Tran T, Bolto B, Gray S, et al. An autopsy study of a fouled reverse osmosis membrane element used in a brackish water treatment plant[J]. Water Research, 2007, 41(17): 3915-3923.
6	Gwon E M, Yu M J, Oh H K, et al. Fouling characteristics of NF and RO operated for removal of dissolved matter from groundwater[J]. Water Research, 2003, 37(12): 2989-2997.
7	Wang S, Xiao K, Huang X. Characterizing the roles of organic and inorganic foulants in RO membrane fouling development: the case of coal chemical wastewater treatment[J]. Separation and Purification Technology, 2019, 210: 1008-1016.
8	Tang C Y, Kwon Y N, Leckie J O. Characterization of humic acid fouled reverse osmosis and nanofiltration membranes by transmission electron microscopy and streaming potential measurements[J]. Environmental Science & Technology, 2007, 41(3): 942-949.
9	Li Q L, Elimelech M. Organic fouling and chemical cleaning of nanofiltration membranes: measurements and mechanisms[J]. Environmental Science & Technology, 2004, 38(17): 4683-4693.
10	Wu S Q, Hua X, Ma B W, et al. Three-dimensional analysis of the natural-organic-matter distribution in the cake layer to precisely reveal ultrafiltration fouling mechanisms[J]. Environmental Science & Technology, 2021, 55(8): 5442-5452.
11	Mairal A P, Greenberg A R, Krantz W B, et al. Real-time measurement of inorganic fouling of RO desalination membranes using ultrasonic time-domain reflectometry[J]. Journal of Membrane Science, 1999, 159(1/2): 185-196.
12	Sim S T V, Chong T H, Krantz W B, et al. Monitoring of colloidal fouling and its associated metastability using Ultrasonic Time Domain Reflectometry[J]. Journal of Membrane Science, 2012, 401/402: 241-253.
13	Chen J, Huang J Y. Texture analysis of UTDR images for enhancement of monitoring and diagnosis of membrane filtration[J]. Chemometrics and Intelligent Laboratory Systems, 2014, 138: 142-152.
14	Li W Y, Liu X, Wang Y N, et al. Analyzing the evolution of membrane fouling via a novel method based on 3D optical coherence tomography imaging[J]. Environmental Science & Technology, 2016, 50(13): 6930-6939.
15	Lee J G, Jang Y, Fortunato L, et al. An advanced online monitoring approach to study the scaling behavior in direct contact membrane distillation[J]. Journal of Membrane Science, 2018, 546: 50-60.
16	Han Q, Li W Y, Trinh T A, et al. Effect of the surface charge of monodisperse particulate foulants on cake formation[J]. Journal of Membrane Science, 2018, 548: 108-116.
17	Chen J, Yang Y C, Wei T Y. Application of wavelet analysis and decision tree in UTDR data for diagnosis of membrane filtration[J]. Chemometrics and Intelligent Laboratory Systems, 2012, 116: 102-111.
18	Gao Y B, Haavisto S, Li W Y, et al. Novel approach to characterizing the growth of a fouling layer during membrane filtration via optical coherence tomography[J]. Environmental Science & Technology, 2014, 48(24): 14273-14281.
19	Zator M, Ferrando M, López F, et al. Microfiltration of protein/dextran/polyphenol solutions: characterization of fouling and chemical cleaning efficiency using confocal microscopy[J]. Journal of Membrane Science, 2009, 344(1/2): 82-91.
20	Le Hir M, Wyart Y, Georges G, et al. Effect of salinity and nanoparticle polydispersity on UF membrane retention fouling[J]. Journal of Membrane Science, 2018, 563: 405-418.
21	Bereschenko L A, Stams A J M, Euverink G J W, et al. Biofilm formation on reverse osmosis membranes is initiated and dominated by Sphingomonas spp[J]. Applied and Environmental Microbiology, 2010, 76(8): 2623-2632.
22	Kromkamp J, Faber F, Schroen K, et al. Effects of particle size segregation on crossflow microfiltration performance: control mechanism for concentration polarisation and particle fractionation[J]. Journal of Membrane Science, 2006, 268(2): 189-197.
23	Brans G, van Dinther A, Odum B, et al. Transmission and fractionation of micro-sized particle suspensions[J]. Journal of Membrane Science, 2007, 290(1/2): 230-240.
24	Vanysacker L, Declerck P, Vankelecom I. Development of a high throughput cross-flow filtration system for detailed investigation of fouling processes[J]. Journal of Membrane Science, 2013, 442: 168-176.
25	孙敏, 贾辉, 秦卿雯, 等. 电阻抗成像原位在线监测超滤膜污染行为研究[J]. 化工学报, 2022, 73(4): 1754-1762, 1847.
	Sun M, Jia H, Qin Q W, et al. In-situ online monitoring of ultrafiltration membrane fouling based on electrical impedance tomography[J]. CIESC Journal, 2022, 73(4): 1754-1762, 1847.
26	聂心童, 孙超, 何亚其, 等. 超滤膜技术在废水处理领域中的应用研究进展[J]. 当代化工研究, 2023(12): 5-7.
	Nie X T, Sun C, He Y Q, et al. Application research progress of ultrafiltration technology in the wastewater treatment area[J]. Modern Chemical Research, 2023(12): 5-7.
27	Wang Q, Guo Z N, Wang J, et al. On-line monitoring of ultrafiltration membrane fouling based on EIT sparse imaging[J]. IEEE Transactions on Instrumentation and Measurement, 2022, 71: 1-11.
28	Wang Z Y, Yue S H, Liu X Y, et al. Estimating homogeneous reference frame for absolute electrical impedance tomography through measurements and scale feature[J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-12.
29	孙丽华, 俞天敏, 田海龙, 等. 典型有机物与超滤膜界面作用及膜污染机制研究[J]. 环境科学学报, 2016, 36(2): 530-536.
	Sun L H, Yu T M, Tian H L, et al. Interaction of typical organic matters on ultrafiltration membrane and the mechanism of membrane fouling[J]. Acta Scientiae Circumstantiae, 2016, 36(2): 530-536.
30	李俊, 奚旦立, 石勇. 动态膜处理污水时阻力分布及污染机理[J]. 化工学报, 2008, 59(9): 2309-2315.
	Li J, Xi D L, Shi Y. Resistance distribution and fouling mechanism of dynamic membrane in wastewater treatment[J]. Journal of Chemical Industry and Engineering (China), 2008, 59(9): 2309-2315.
31	Dusek J, Mikulka J. Measurement-based domain parameter optimization in electrical impedance tomography imaging[J]. Sensors, 2021, 21(7): 2507.
32	Liu X Y, Yao J F, Zhao T, et al. Image reconstruction under contact impedance effect in micro electrical impedance tomography sensors[J]. IEEE Transactions on Biomedical Circuits and Systems, 2018, 12(3): 623-631.
33	Wang Q, Lian Z J, Wang J M, et al. Accelerated reconstruction of electrical impedance tomography images via patch based sparse representation[J]. Review of Scientific Instruments, 2016, 87(11): 114707.

[1]	高学金, 姚玉卓, 韩华云, 齐咏生. 基于注意力动态卷积自编码器的发酵过程故障监测[J]. 化工学报, 2023, 74(6): 2503-2521.
[2]	明迁, 高逸, 胡剑, 李盛杰, 王金江. 热交换器泄漏故障虚拟感知方法研究[J]. 化工学报, 2023, 74(4): 1836-1846.
[3]	宋冰, 郑城风, 侍洪波, 陶阳, 谭帅. 基于VAE-OCCA的质量相关故障检测方法研究[J]. 化工学报, 2023, 74(4): 1630-1638.
[4]	王思琪, 顾天宇, 陈献富, 王通, 李佳, 柯威, 李小锋, 范益群. 陶瓷膜用于杜仲叶提取液澄清的分离特性与膜污染机制研究[J]. 化工学报, 2023, 74(3): 1113-1125.
[5]	刘壮壮, 鞠然, 刘崇涛, 宋建超, 李洋洋, 吴厚凯, 李同, 陶秀萍. 电化学膜生物反应器处理污水性能提升策略及研究现状[J]. 化工学报, 2023, 74(11): 4433-4444.
[6]	籍帅航, 王金江, 蔡睿, 孙雪皓, 葛伟凤. 数字孪生驱动的热交换器降阶建模及智能感知方法研究[J]. 化工学报, 2023, 74(10): 4218-4228.
[7]	王雅琳, 潘雨晴, 刘晨亮. 基于GSA-LSTM动态结构特征提取的间歇过程监测方法[J]. 化工学报, 2022, 73(9): 3994-4002.
[8]	曾欣欣, 白慧娟, 俞娟, 黄培, 杨超, 徐俊波. 面向空天动力用聚酰亚胺树脂基复合材料介尺度结构与调控[J]. 化工学报, 2022, 73(6): 2352-2369.
[9]	孙敏, 贾辉, 秦卿雯, 王琦, 郭子楠, 罗艳茹, 王捷. 电阻抗成像原位在线监测超滤膜污染行为研究[J]. 化工学报, 2022, 73(4): 1754-1762.
[10]	高学金, 何紫鹤, 高慧慧, 齐咏生. 基于联合典型变量矩阵的多阶段发酵过程质量相关故障监测[J]. 化工学报, 2022, 73(3): 1300-1314.
[11]	张兰河, 汪露, 李梓萌, 唐宏, 郭静波, 贾艳萍, 张明爽. 电极超滤膜生物反应器处理阴离子表面活性剂废水[J]. 化工学报, 2022, 73(10): 4679-4691.
[12]	唐和礼, 张冰, 黄冬梅, 申渝, 高旭, 时文歆. XDLVO理论在膜污染解析中的应用研究[J]. 化工学报, 2021, 72(3): 1230-1241.
[13]	朱雄卓, 张瀚文, 杨春节. 基于高斯混合模型的MWPCA高炉异常监测算法[J]. 化工学报, 2021, 72(3): 1539-1548.
[14]	王开珍, 王书浩, 李韵浩, 周勇, 高从堦. 原位合成法制备高通量聚砜超滤膜及其性能研究[J]. 化工学报, 2021, 72(3): 1712-1721.
[15]	王文广, 谭明, 孙小寒, 杨兴涛, 张晓东, 张杨, 赵洪武. 基于海水淡化中试的超滤膜清洗工艺及机理[J]. 化工学报, 2020, 71(S2): 289-296.

基于双侧阵列电极的电阻抗成像原位膜污染监测

In situ monitoring of membrane fouling by electrical impedance tomography based on bilateral array electrodes

RichHTML

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

图/表 8

参考文献 33

相关文章 15

编辑推荐

Metrics

本文评价