基于图像处理判断水混凝中矾花性能的研究及应用进展Research and application progress of judging the performance of flocs based on image processing in water coagulation
郭上科,郭俊文,文昌璧,李博润,滕维忠,江小伟,章德才,乔越
摘要(Abstract):
原水预处理主要分为混凝、沉淀和过滤3个阶段,混凝中的絮凝过程直接影响矾花结构与出水浊度;目前多采用检测出水浊度方法来控制混凝剂加药量,但因时间滞后无法快速反映混凝效果与反馈调节加药量。随着计算机技术的快速发展,利用矾花图像处理技术能够实现快速、准确、实时检测絮凝状态,从而更准确控制加药量,提高混凝效果。从计算机视觉技术角度,概述了絮凝中矾花图像采集与处理的技术特点,介绍了实时跟踪和计算矾花结构特征参数如等效粒径、分形维数等方法,并给出了部分试验结果,通过这些参数可以判断最佳混凝效果,为混凝控制与加药提供依据。
关键词(KeyWords): 絮凝;矾花;图像处理;等效粒径;分形维数
基金项目(Foundation): 中国华能集团有限公司总部科技项目(HNKJ21-HF201)~~
作者(Author): 郭上科,郭俊文,文昌璧,李博润,滕维忠,江小伟,章德才,乔越
DOI: 10.19666/j.rlfd.202310169
参考文献(References):
- [1]蔡鑫.微生物在污水处理中的应用研究[J].工业微生物, 2023, 53(2):37-39.CAI Xin. Study on the application of microorganisms in sewage treatment[J]. Industrial Microbiology, 2023,53(2):37-39.
- [2] WANG D, WU J, DENG L, et al. A real-time optimization control method for coagulation process during drinking water treatment[J]. Nonlinear Dynamics,2021, 105(4):3271-3283.
- [3]符家瑞,周艾珈,刘勇,等.我国城镇污水再生利用技术研究进展[J].工业水处理, 2021, 41(1):18-24.FU Jiarui, ZHOU Aijia, LIU Yong, et al. Research progress of urban sewage reclamation technology in China[J]. Industrial Water Treatment, 2021, 41(1):18-24.
- [4]朱志强.自来水厂混凝投药控制系统分析[J].建材与装饰, 2020, 18(12):284-285.ZHU Zhiqiang. Analysis of coagulant dosage control System in waterworks[J]. Building Materials and Decoration, 2020, 18(12):284-285.
- [5] MULLINS D, COBURN D, HANNON L, et al. Using image processing for determination of settled sludge volume[J]. Water Science and Technology, 2018, 78(2):309-401.
- [6]曾亮.基于图像处理的水中絮体识别方法研究[D].长沙:湖南大学, 2019:1.ZENG Liang. Research on floc recognition method in water based on image processing[D]. Changsha:Hunan University, 2019:1.
- [7] ZHU Z F, WANG H R, YU J S, et al. On the kaolinite floc size at the steady state of flocculation in a turbulent flow[J]. Plos One, 2016, 11(2):148-895.
- [8]陈凯歌,韩晓军,张宇.基于图像处理的混凝控制方法研究[J].供水技术, 2012, 6(1):40-42.CHEN Kaige, HAN Xiaojun, ZHANG Yu. Coagulation control method based on image processing[J]. Water Supply Technology, 2012, 6(1):40-42.
- [9] FAN Y, MA X, DONG X, et al. Characterisation of floc size, effective density and sedimentation under various flocculation mechanisms[J]. Water Science&Technology, 2020, 82(7):1261-1271.
- [10] SUN S, WEBERSHIRK M, LION L W. Characterization of flocs and floc size distributions using image analysis[J]. Environmental Engineering Science, 2016,33(1):25-34.
- [11] HUANG X, BO X, ZHAO Y, et al. Effects of compound bioflocculant on coagulation performance and floc properties for dye removal[J]. Bioresource Technology,2014, 165(19):116-121.
- [12] HUANG X, GAO B, YUE Q, et al. Compound bioflocculant used as a coagulation aid in synthetic dye wastewater treatment:the effect of solution p H[J].Separation&Purification Technology, 2015, 154:108-114.
- [13] ZHU Y, LI H. A new method for the process division and effect evaluation of coagulation based on particle size fractal dimension[J]. Processes, 2018, 6(12):237.
- [14] QIN X, GAO F, CHEN G. Wastewater quality monitoring system using sensor fusion and machine learning techniques[J]. Water Research, 2012, 46(4):1133-1144.
- [15] FEIZI H, SATTARI M T, MOSAFERI M, et al. An image-based deep learning model for water turbidity estimation in laboratory conditions[J]. International Journal of Environmental Science and Technology, 2023,20(1):149-160.
- [16] CHENG W P, HSIEH Y J, YU R F, et al. Characterizing polyaluminum chloride(PACl)coagulation floc using an on-line continuous turbidity monitoring system[J].Journal of the Taiwan Institute of Chemical Engineers,2010, 41(5):547-552.
- [17]刘宏远,周晓龙,朱海涛,等.在线颗粒计数仪在自来水厂水质监控中的应用[J].中国给水排水, 2014,30(3):44-47.LIU Hongyuan, ZHOU Xiaolong, ZHU Haitao, et al.Application of online particle counter to water quality monitoring at waterworks[J]. China Water Supply and Drainage, 2014, 30(3):44-47.
- [18] CHEN F, LIU W, PAN Z, et al. Characteristics and mechanism of chitosan in flocculation for water coagulation in the Yellow River diversion reservoir[J].Journal of Water Process Engineering, 2020, 34(491):101-191.
- [19]黄孟炯.水处理工艺中数据采集跟踪技术分析[J].科技传播, 2010(13):75.HUANG Mengjiong. Analysis of data acquisition and tracking technology in water treatment process[J].Science and Technology Communication, 2010(13):75.
- [20] LINTERN G, SILLS G. Techniques for automated measurement of floc properties[J]. Journal of Sedimentary Research, 2006, 76(10):1183-1195.
- [21]李爱玲,张伯珩,张健,等.多光谱CCD相机图像采集系统的设计[J].微计算机信息, 2011, 27(12):15-16.LI Ailing, ZHANG Boheng, ZHANG Jian, et al. Design of digital image acquisition system for multispectral CCD camera[J]. Microcomputer Information, 2011,27(12):15-16.
- [22]王瑞萍,史步海,朱学峰.水处理中利用CCD测量混凝效果的研究[J].微计算机信息, 2006, 23(34):158-160.WANG Ruiping, SHI Buhai, ZHU Xuefeng. The research on effect of coagulation using CCD in the water purification[J]. Microcomputer Information, 2006,23(34):158-160.
- [23] ZHANG H, YANG L, ZANG X, et al. Effect of shear rate on floc characteristics and concentration factors for the harvesting of Chlorella vulgaris using coagulationflocculation-sedimentation[J]. The Science of the Total Environment, 2019, 688(20):811-817.
- [24] ASENSI E, ZAMBRANO D, ALEMANY E, et al. Effect of the addition of precipitated ferric chloride on the morphology and settling characteristics of activated sludge flocs[J]. Separation and Purification Technology,2019, 227(17):115-711.
- [25]许梦飞,朱丽娟,刘芯言,等.基于钻采管材断口图像特征的图像预处理方法研究[J].石油管材与仪器,2023, 9(2):50-55.XU Mengfei, ZHU Lijuan, LIU Xinyan, et al. Image preprocessing method based on fracture image characteristics of drolling goods[J]. Journal of Oil Pipe and Instrument, 2023, 9(2):50-55.
- [26]王杰,梁丽珍.计算机图像处理技术在污水处理絮凝效果检测中的应用[J].环境工程, 2013, 31(4):17-20.WANG Jie, LIANG Lizhen. The application of computer image processing technology in detection of flocculation effect of wastewater treatment[J]. Environmental Engineering, 2013, 31(4):17-20.
- [27]王嵩林.水处理过程中图像识别方法的应用与实现[D].北京:北京化工大学, 2018:1.WANG Songlin. The application and implementation of image recognition method in water treatment[D].Beijing:Beijing University of Chemical Technology,2018:1.
- [28]杨伟婷,李保育,左文斌.基于机器视觉的图像处理方法[J].信息技术与信息化, 2021, 46(7):143-145.YANG Weiting, LI Baoyu, ZUO Wenbin. Image process method based on Machine vision[J]. Information Technology and Informatization, 2021, 46(7):143-145.
- [29]张中良.基于机器视觉的图像目标识别方法综述[J].科技与创新, 2016, 3(14):32-33.ZHANG Zhongliang. Overview of image object recognition methods based on machine vision[J]. Science and Technology Innovation, 2016, 3(14):32-33.
- [30] SINGH M, VERMA A, SHARMA N. Multi-objective noise estimator for the applications of de-noising and segmentation of MRI data[J]. Biomedical Signal Processing and Control, 2018, 46(9):249-259.
- [31] VAN M, GE S S, CEGLAREK D. Fault estimation and accommodation for virtual sensor bias fault in image-based visual servoing using particle filter[J]. IEEE Transactions on Industrial Informatics, 2017, 14(4):1312-1322.
- [32]陈娟,陈乾辉,师路欢,等.图像跟踪中的边缘检测技术[J].中国光学与应用光学, 2009, 2(1):46-53.CHEN Juan, CHEN Qianhui, SHI Luhuan, et al. Edge detection technology in image tracking[J]. Chinese Optics and Applied Optics, 2009, 2(1):46-53.
- [33]王芳,钱炜,李文超.基于数学形态学的图像边缘提取方法[J].机械工程与自动化, 2015, 44(1):46-48.WANG Fang, QIAN Wei, LI Wenchao. Edge detection algorithm based on mathematical morphology[J].Mechanical Engineering&Automation, 2015, 44(1):46-48.
- [34] WANG Z, WANG E, ZHU Y. Image segmentation evaluation:a survey of methods[J]. Artificial Intelligence Review, 2020, 53(1):5637-5674.
- [35]张春玲,杨新年,向洪波,等.基于阈值分割与形态学变化的树叶面积测量方法研究[J].无线互联科技,2022, 19(19):133-136.ZHANG Chunling, YANG Xinnian, XIANG Hongbo,et al. Study of leaf area measurement based on threshold segmentation and morphological change[J]. Wireless Internet Technology, 2022, 19(19):133-136.
- [36] FELZENSZWALB P F, HUTTENLOCHER D P.Efficient graph-based image segmentation[J].International Journal of Computer Vision, 2004, 59(2):167-181.
- [37] SENTHILKUMARAN N, RAJESH R. Edge detection techniques for image segmentation-a survey of soft computing approaches[J]. International Journal of Recent Trends in Engineering, 2007, 1(2):250-254.
- [38]葛杰,曹晨晨,李光.基于机器视觉的图像形状特征提取方法研究进展[J].包装学报, 2015, 7(1):54-60.GE Jie, CAO Chenchen, LI Guang. Research progress in shape feature extraction methods based on machine vision[J]. Journal of Packaging, 2015, 7(1):54-60.
- [39]郭建甲,范新南,卜桂花,等.基于数字图像处理技术的污水自动加絮凝剂研究[J].工业水处理, 2008,28(5):51-53.GUO Jianjia, FAN Xinnan, BU Guihua, et al. Research on automatic flocculant addition of wastewater based on digital image processing technology[J]. Industrial Water Treatment, 2008, 28(5):51-53.
- [40]吕玉龙,张双翼,徐鸿凯,等.矾花形态特征量化和识别方法研究进展[J].给水排水, 2022, 58(增刊1):1108-1113.LYU Yulong, ZHANG Shuangyi, XU Hongkai, et al. A brief description of the methods used to quantify and identify morphological characteristics of flocs[J]. Water Supply and Drainage, 2022, 58(Suppl.1):1108-1113.
- [41] WANG B, SHUI Y, HE M, et al. Comparison of flocs characteristics using before and after composite coagulants under different coagulation mechanisms[J].Biochemical Engineering Journal, 2017, 121(7):107-117.
- [42]马启栋,孔月萍,李博宇,等.水处理过程中的絮体图像纹理特征分析及应用[J].给水排水, 2023, 59(3):15-20.MA Qidong, KONG Yueping, LI Boyu, et al. Analysis and application of floc image texture characteristics in water treatment process[J]. Water Supply and Drainage,2023, 59(3):15-20.
- [43]张松兰.基于卷积神经网络的图像识别综述[J].西安航空学院学报, 2023, 41(1):74-81.ZHANG Songlan. A review image recognition based on Convolutional neural networks[J]. Journal of Xi’an Aeronautical University, 2023, 41(1):74-81.
- [44]李春静.基于MATLAB图像处理的混凝效果的检测方法研究[D].唐山:河北联合大学, 2014:1.LI Chunjing. The coagulation effect detection research based on MATLAB image processing[D]. Tangshan:North China University of Science and Technology,2014:1.
- [45] ZHANG H Y, LI C, LI L L, et al. Uncovering the optimal structural characteristics of flocs for microalgae flotation using Python-OpenCV[J]. Journal of Cleaner Production,2023, 385(58):135-748.
- [46]翟士才,陆明刚.基于OpenCV的絮体颗粒跟踪与沉速测量系统研究[J].计量与测试技术, 2017, 44(1):47-50.ZHAI Shicai, LU Minggang. Research on tracking and sedimentation velocity of flocs based on OpenCV[J].Metrology and Testing Technology, 2017, 44(1):47-50.
- [47] ZHOU X, JIN W, WANG L, et al. Improving primary sludge dewaterability by oxidative conditioning process with ferrous ion-activated peroxymonosulfate[J]. Korean Journal of Chemical Engineering, 2020, 37(9):1498-1506.
- [48] KINOSHITA T, NAKAISHI K, KURODA Y.Determination of kaolinite floc size and structure using interface settling velocity[J]. Applied Clay Science,2017, 148(11):11-16.
- [49]陈峰,阮鸿雁,杨强.基于絮体等效直径的混凝剂加注量自动控制技术[J].工业用水与废水, 2005, 36(6):50-52.CHEN Feng, RUAN Hongyan, YANG Qiang. Automatic control technology of coagulant dosage based on equivalent particle size of flocs[J]. Industrial Water and Wastewater, 2005, 36(6):50-52.
- [50]李健华,史步海.基于絮体等效直径的混凝控制研究[J].微计算机信息, 2008, 25(13):3-4.LI Jianhua, SHI Buhai. Research on coagulation control based on flocs equivalent particle size[J]. Microcomputer Information, 2008, 25(13):3-4.
- [51]徐敏,杜洪宇,窦微笑,等.钙矾石法去除脱硫废水硫酸根沉淀物沉降特性研究[J].工业水处理, 2022,42(3):123-130.XU Min, DU Hongyu, DOU Weixiao, et al. Setteability of ettringite precipitate for sulfate removal from flue gas desulfurization wastewater[J]. Industrial Water Treatment, 2022, 42(3):123-130.
- [52] DARAEI H, AKYOL B, KHEDHER M, et al.Continuous floc image analyser(C-FIA)for tracking floc particle dynamics during coagulation-flocculation-settling processes[J]. Water Research&Technology,2023, 9(5):1331-1341.
- [53] CYDZIK-KWIATKOWSKA A, RUSANOWSKA P,GLOWACKA K. Operation mode and external carbon dose as determining factors in elemental composition and morphology of aerobic granules[J]. Archives of Environmental Protection, 2016, 42(1):74-79.
- [54]江南,雒鹏飞,童志明,等.含钛聚硅酸盐絮凝剂的合成及处理压裂返排液研究[J].工业水处理, 2021,41(5):73-79.JIANG Nan, LUO Pengfei, TONG Zhiming, et al.Synthesis of titanium containing polysilicate flocculant and treatment of fracturing flowback fluid[J]. Industrial Water Treatment, 2021, 41(5):73-79.
- [55] TAN Y, MENG X, JIANG Z, et al. Research on flocculant selection for classified fine tailings based on micro-characterization of floc structure characteristics[J].Materials(Basel, Switzerland), 2022, 15(7):24-60.
- [56] CHAKRABORTI R K, ATKINSON J F, VAN B J E.Characterization of alum floc by image analysis[J].Environmental Science&Technology, 2000, 34(18):3969-3976.
- [57]伍薇.基于分形理论的再生水混凝处理试验研究[D].天津:天津大学, 2012:1.WU Wei. Experimental research of recycled water coagulation treatment based on fractal theory[D]. Tianjin:Tianjin University, 2012:1.
- [58] RAO X K, JIA B L, LI L U. Research and development of coagulation dosage control system for a waterworks based on artificial neural network[J]. Journal of Yangtze River Scientific Research Institute, 2017, 34(5):136-140.
- [59] HUSSEIN M A, El SR M, ALAMRY K A, et al. Efficient water disinfection using hybrid polyaniline/graphene/carbon nanotube nanocomposites[J]. Environmental Technology, 2018, 40(21):1-38.
- [60]高超.基于机器视觉的水处理絮凝过程中絮体检测与絮体性能研究[D].南昌:华东交通大学, 2016:1.GAO Chao. The study on floc measurement and floc performance in the flocculation process of water treatment based on machine vision[D]. Nanchang:East China Jiaotong University, 2016:1.
- [61] TANG P, GREENWOOD J, RAPER J A, et al. A model to describe the settling behavior of fractal aggregates[J].Journal of Colloid and Interface Science, 2002, 247(1):210-219.
- [62]李冬梅,施周,梅胜,等.絮凝条件对絮体分形结构的影响[J].环境科学, 2006, 27(3):488-492.LI Dongmei, SHI Zhou, MEI Sheng, et al. Effect of flocculation conditions on aggregates fractal structures[J]. Environmental Science, 2006, 27(3):488-492.