化學混凝程序為最常見的處理水及廢水的技術之一，其主要針對水及廢水中的懸浮顆粒與膠體物質進行去除以達淨化水質之目的，其中進、出流水SS濃度變化是判斷系統處理成效優劣之關鍵，而目前在此部分大多以標準水質分析方法得知水質處理狀況再對處理系統進行控制，但因標準分析方法無法即時量測且所需時間長，故無法即時對系統進行控制與調整，僅少部分以自動監測水質的設備進行量測，但目前即時量測設備大多以接觸性量測為主，因初設成本過高且需定期進行維護與更換耗材，而間接提高處理成本；因此本研究利用光學頻譜分析技術建立光學影像變化與水中SS濃度之關係，發展一套非接觸式光學量測水中SS濃度的技術，以即時提供化學混凝程序中SS濃度資訊，並根據於單槽式批次化學混凝水及廢水處理系統中的量測結果顯示利用光學量測SS濃度具適用性與有效性，且與標準檢測方法比較，在650 nm的波長下，其平均差異值為8.10 mg/L，平均差異百分比為8.42 %；在532 nm的波長下，其平均差異值為23.04 mg/L，平均差異百分比為25.33 %；而此二種量測方法在重複分析上，其平均相對差異百分比皆小於5 %，故由上述結果可得知，本研究所開發的光學影像頻譜分析之技術可有效且即時地提供單槽式批次化學混凝水及廢水處理系統內SS濃度資訊，並藉此資訊使處理系統能達到降低單位處理成本、提升出流水質穩定性及水及廢水處理效率之目的。

Coagulation is one of the most important procedure in water / wastewater treatment. Removing suspended solids and colloidal substances from water and wastewater is the main procedure to achieve the purpose of water purification. The concentration of suspended solid of influent and effluent is to determine the effectiveness of chemical process. The current system using the standard methods can not offer the necessary information immediately and completely which can make control strategy of wastewater treatment. To improve information’s efficiency, this study developed an automatic water quality monitoring system with the optical spectrum analysis technique to measure water quality, which has immediate reaction, cost low construction, etc. In addition, it has the advantage of non-contacted and real-time.
This study is mainly to utilizing optical image spectrum analysis technique to measure suspended solids. And the intensity of beam has been revised from surface to underwater by relationship between intensity and distance. The Optical measure results compare with experimental results of standard methods. At wavelength of the incident beam 650 nm, the average difference is 8.10 mg/L and the average percentage difference is 5.42 %. At wavelength of 532 nm and the average difference is 23.04 mg/L, the average percentage difference is 25.33 %. Besides, all of the percentage of average relative difference are below 5 % for duplicate analysis.
Applying optical image spectrum analysis to develop an automatic real-time water quality monitoring system for suspended solids is steady and accurate. It can not only offer real-time information for wastewater treatment, but also improve the efficiency and effectiveness of wastewater treatment.

Amirtharagjah, A., and C.R. O''Melia, “Coagulation Processes: Destabilization, Mixing and Flocculation”, Water Quality & Treatment.4th, pp.269-365, 1990.
Armstrong, F. A. J. and G. T. Boalch, “The ultra-violet absorption of sea water”, Journal of the Marine Biological Association, Vol. 41, pp. 591–597, 1961.
Casellas, M., C. Dagot, M. Baudu, “Set up and assessment of a control strategy in a SBR in order to enhance nitrogen and phosphorus removal”, Process Biochemistry, Vol. 41, pp. 1994–2001, 2006.
Coque, Y., E. Touraud, O. Thomas, “On line spectrophotometric method for the monitoring of colour removal processes”, Dyes and Pigments, Vol. 54, pp. 17–23, 2002.
Chou, S. S., S. C. Lin, and C. P. Huang, “Application of optical monitor to evaluate the coagulation of pulp wastewater”, 1998.
Dentel, S. K., A. V. Thomas and K. M. Kingery, “Evaluation of the Streaming Current Detector-I. Use in jar tests”, Water Research, Vol. 23, pp. 413–421, 1989.
Dobbs, R. A., R. H. Wise and R. B. Dean, “The use of ultra-violet absorbance for monitoring the total organic carbon content of water and wastewater”, Water Research Pergamon Press, Vol. 6, pp. 1173–1180, 1972.
Eisenlauer, J. and D. Horn, “Fibre-optic sensor technique for flocculant dose control in flowing suspensions”, Colloids and Surfaces, Vol.14, pp. 121–134, 1984.
Fecht, I. and M. Johnson, “Non-contact scattering-independent water absorption measurement using a falling stream and integrating sphere,” Measurement Science and Technology, Vol. 10, pp. 612-618, 1999.
Gregory, J. and D. W. Nelson, “Monitoring of aggregates in flowing suspension”, Colloids and Surfaces, Vol.18, pp. 175–188, 1986.
Kayodea, T. O. and J. Gregory, “A new technique for monitoring alum sludge conditioning”, Water Research, Vol.22, pp.85-90, 1988.
Kim, J. H., M. Chenb, N. Kishidac, R. Sudoa, “Integrated real-time control strategy for nitrogen removal in swine wastewater treatment using sequencing batch reactors” , Water Research, Vol. 38, pp. 3340–3348, 2004.
Maier, H. R., N. Morgan and C. W. K. Chow, “Use of artificial neural networks for predicting optimal alum doses and treated water quality parameters”, Environmental Modelling & Software, Vol. 19, pp. 485-494, 2004.
Miller, R. L. and J. F. Cruise, “Effect of Suspended Sediments on Coral Growth:Evidence from Remote Sensing and Hydrologic Modeling”, Remote sensing of Environment, Vol. 53, pp. 177-187, 1995.
National instrument. “LabVIEW Machine Vision and Image Processing Course Manual,” 1st ed. N.I. Corporation, pp .5-1 – 5-12, 2008.
Rosen, C. and J. A. Lennox, “Multivariate and multiscale monitoring of wastewater treatment operation,” Water Research, Vol. 38, No. 14, pp. 3402–3410, 2001.
Weinreich, G., W. Schilling, A. Birkely and T. Moland, “Pollution based real time control strategies for combined sewer systems”, 1998.
Yu, R. F., S. L. Liaw, C. N. Chang and W. Y. Cheng, “Applying real-time control to enhance the performance of nitrogen removal in the continuous-flow SBR system”, 1999.
Yu, R. F., S. L. Liaw, C. N. Chang and M. C. Chen, “Application of artificial neural network to control the coagulant dosing in water treatment plant”, Water Science & Technology, Vol. 42, pp. 403–408, 2000.
江志威，「水位與SS即時自動監測技術與裝置之發展與建立」，國立中央大學環境工程研究所，碩士論文，2009。
行政院環境保護署，「環境檢測方法－水量測定方法」，行政院環境保護署全球資訊網，http://www.niea.gov.tw/，2010。
黃春融、詹寶珠，「由影像處理到電腦視覺」，科學發展，361期，2003。
徐奕喬，「渠道水質與水量即時自動監測系統之初步研發」，國立中央大學環境工程研究所，碩士論文，2010。
游佩蓉，「利用UV/VIS/NIR吸收光譜同步量測水中SS、有機物及重金屬之研究」，國立中央大學環境工程研究所，碩士論文，2009。
張守進、劉醇星、姬梁文，「半導體雷射」，科學發展，349期，2002。
雷一弘，「應用數位影像技術於廢水真色色度監測之研究」，國立中央大學環境工程研究所，碩士論文，2000。
劉鴻慶，「懸浮顆粒沉澱特性量測技術與裝置之發展與建立」，國立中央大學環境工程研究所碩士論文，2009。
謝易錚，「以立體視覺實作盲人輔具系統」，國立中央大學資訊工程研究所，碩士論文，2006。