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以數位影像技術應用於化學混凝沈澱程序自動控制之研究

Application of digital image technique to control chemical coagulation and sedimentation process

作者:陳銘敏
畢業學校:國立聯合大學
出版單位:國立聯合大學
核准日期:2010-09-13
類型:Electronic Thesis or Dissertation
權限:Copyright information available at source archive--National United University....

中文摘要

廢水處理程序中,化學混凝/膠凝,沉澱/沉降程序是常用且不可或缺
之處理單元程序之ㄧ,而混凝過程中,混凝劑的添加量及 GT 值影響膠體
之粒徑大小、面積、碎形維度等,進一步影響沉澱池之效率,混凝劑添加
過量的混凝劑不但造成藥劑的浪費,也會使膠體表面電荷逆轉,產生互相
排斥再穩定狀態。而無論是自來水或廢水之化學混凝或廢水生物處理程
序,最終大都需以重力沉澱方式進行固液分離,使液體與固體充分的分
離。沉澱效果的好壞受到懸浮顆粒沉降性的影響,而顆粒沉降性受顆粒形
成之粒徑大小、比重、形態等有相當大的影響性。另外,沉澱效率亦受沉
澱過程之固體通量(Solid flux)之影響。因此,化學混凝沉澱之效率受到多
元化學性與物理性機制的影響。然而,目前對化學混凝池之效能評估方
法,只能以人工取樣分析,或輔以如雷射分析儀分析其顆粒分佈,作為評
估化學混凝池之操作效率,該方法不但費時且無法或不易做為線上即時、
連續監測之資訊,且雷射粒徑分析儀亦昂貴,應用範圍頗受限制。另外,
現行之化學混凝劑加藥之控制大都以瓶杯實驗(jar test)進行,並無法因應進
流之水質特性即時調整,易造成加藥過量或不足之問題。因此,本研究嘗
試利用線上影像分析技術發展一種具經濟性且簡便之評估化學混凝沉凝
池效率之技術,利用顆粒粒徑、面積、體積大小及碎形維度(Fractal
dimension)並進一步結合沉澱固體通量之理論以分析沉澱池之沉澱效率,
同時將以廢水化學混凝沉澱程序為對象發展一套自動即時之操控方法與
技術,此技術可提供做為線上監測,因此對廢水化學混凝沉澱程序之自動
控制將十分有助益,可節省相關之操作成本,是頗值得發展的技術。

英文摘要

Chemical coagulation and sedimentation process was typically used in
most industrial wastewater treatment plants in Taiwan to remove the suspended
solids and other pollutants. The efficiency of chemical coagulation and
sedimentation will be influenced by the particle size distribution, density, and
fractal dimension. The present method to analysis the particle size characteristics in wastewater is typically using the laser particle counter. It is unable to offer the on-line monitoring for real-time control. On the other hand, the dosage control of coagulant in chemical coagulation and sedimentation is typically according to the results from jar test. It is also unable to be used for real-time control. An image detection system and digital image recognition technical was setup in this study to measure the particle characteristics including particle size distribution, fractal dimension, solid flux etc. for real-time control the chemical coagulation and sedimentation process. The artificial neural network (ANN) will used to construct the control model. This model has high potential to be able to predict the efficiency of sedimentation precisely. Finally, an on-line control strategy for particle setting evaluation and control will be built and used to control the chemical coagulation and sedimentation process.

 

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