面對人類永續發展與水資源永續利用之需求，透過廢水處理系統的自動化與最佳化來提升廢水處理之穩定性、效率及效益，已成為必然的趨勢。因此，研發各種可線上即時自動監測水質與水量的技術與設備以提升處水處理之成效，儼然成為目前研究重點之一。有鑑於傳統量測設備及水質分析實驗無法即時、完整且有效提供擬定控制策略或水質異常時所需之資料與資訊，是故，以光學方法建立即時廢水水質與水量之監測方法與系統，其具有快速量測、不需外加藥劑、建置成本低等優點，可有效解決及改善傳統量測或實驗分析所面臨之問題。
本研究利用光學頻譜分析方法，針對廢水水質之COD與SS，以線上分光光度計掃描廢水之吸收光譜，以多成分演算法依序定性與定量廢水成分；另外結合數位影像分析方法，利用測邊原理以擷取出水位影像像素，再以三角函數及回歸模式方法求得實際水位與流量，最後整合成一套水質與水量即時自動監測系統，並同時以實驗室與實廠監測做驗證。於水質量測方面，對於相同標準品之量測，其量測之標準偏差百分比都小於實驗水質分析方法，另外對於實廠各處理單元或變動性較大之長時間水質量測，其與實驗水質分析之相對誤差大致在於20%與15%以內，於放流水相對差值大致在5mg/L以內；而於流量量測方面，其實驗室量測成果其相對誤差亦在2%以內。結果顯示，利用光學方法建立COD、SS及流量自動即時監測系統，已具有一定程度之穩定性及準確性，並可提供實廠即時資料與資訊做為廢水處理及異常警報之用，以提升自動化處理成效。

To confront the requirement of the sustainable development of human beings and the sustainable use of water resource, it becomes the imperious current that can improve the stability, efficiency and effectiveness of wastewater treatment through the automation and optimization of wastewater treatment systems. For this reason, it is important to research and develop various kinds of technology and equipment of an automatic real-time water quality and water quantity monitoring system. Respecting the deficiencies of the traditional measurement equipments and experiment analysis that can not offer the necessary information immediately and completely when the control strategy of wastewater treatment has to be made or the situation of unusual water quality has happened, the development of an automatic water quality and quantity monitoring system with the optics method that have fast quantity examine, cost low construction, etc., is efficacious to solve and improve the problem caused by the traditional method.
This research is mainly to utilizes spectrum analysis and digital image analysis to develop an automatic real-time water quality and quantity monitoring system which can apply to experiments and wastewater treatment. There are two parts to develop to this research, one is the multiple components algorithm for a qualitative and quantitative analysis method of COD and SS, and the anther is the trigonometric function method and the regression model method for flow and water level. The results indicate that the stability and the accuracy of the monitoring system is superior to the experiment analysis for water quality measurement, and each of the relative percent difference of COD and SS between the monitoring system and the experiment analysis in many place of wastewater treatment is mostly less than 20% and 15%. Moreover, the relative percent difference of flow between the monitoring system and pilot system is less than 2%.
Altogether, Utilizing spectrum analysis and digital image analysis to develop an automatic real-time water quality and quantity monitoring system for COD, SS and flow is stable and accurate respectably. It can not only offer real-time information for wastewater treatment, but also announces the operators that the water quality is unusual in order to improve the efficiency and effectiveness of wastewater treatment.

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