Research and application progress of judging the performance of flocs based on image processing in water coagulation

GUO Shangke; GUO Junwen; WEN Changbi; LI Borun; TENG Weizhong; JIANG Xiaowei; ZHANG Decai; QIAO Yue

doi:10.19666/j.rlfd.202310169

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Research and application progress of judging the performance of flocs based on image processing in water coagulation

更新时间：2025-09-28

- Research and application progress of judging the performance of flocs based on image processing in water coagulation
- Thermal Power Generation Vol. 53, Issue 5, Pages: 1-9(2024)
- 作者机构：
  
  1. 华能海南发电股份有限公司东方电厂
  2. 西安热工研究院有限公司
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202310169
  CLC： TU991.2
- Published：2024
- 稿件说明：
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GUO Shangke, GUO Junwen, WEN Changbi, et al. Research and application progress of judging the performance of flocs based on image processing in water coagulation[J]. Thermal power generation, 2024, 53(5): 1-9.
DOI：

GUO Shangke, GUO Junwen, WEN Changbi, et al. Research and application progress of judging the performance of flocs based on image processing in water coagulation[J]. Thermal power generation, 2024, 53(5): 1-9. DOI： 10.19666/j.rlfd.202310169.

摘要

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。

Abstract

Raw water pretreatment can be divided into three stages: coagulation

sedimentation and filtration. The flocculation process directly affects the structure of alum and the turbidity of effluent. At present

the method of measuring the turbidity of the effluent is usually used to control the dosage of coagulant

but due to the time lag

it can not quickly reflect the coagulation effect and adjust the dosage of the feedback. With the rapid development of computer technology

the application of alum image processing technology can realize rapid

accurate and real-time detection of flocs state

so as to control the dosage more accurately and improve the coagulation effect.From the perspective of computer vision technology

this paper summarizes the technical characteristics of alum image acquisition and processing in flocs

introduces the method of real-time tracking and calculating the characteristic parameters of alum structure

such as equivalent particle size

fractal dimension

etc.

and some test results are also provided. Through these parameters the best coagulation effect can be judged

which provides the basis for coagulation control and dosing.

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