| DC 欄位 |
值 |
語言 |
| DC.contributor | 環境工程研究所 | zh_TW |
| DC.creator | 游佩蓉 | zh_TW |
| DC.creator | Pei-jung You | en_US |
| dc.date.accessioned | 2009-7-23T07:39:07Z | |
| dc.date.available | 2009-7-23T07:39:07Z | |
| dc.date.issued | 2009 | |
| dc.identifier.uri | http://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=963206023 | |
| dc.contributor.department | 環境工程研究所 | zh_TW |
| DC.description | 國立中央大學 | zh_TW |
| DC.description | National Central University | en_US |
| dc.description.abstract | 廢水處理為ㄧ種耗費大量人力、物力與財力資源卻又不容忽視的處理程序，因此，可提供即時、完整且有效的控制策略時所需的廢水之水質成分及其濃度等資訊，以提升廢水處理系統之穩定性及處理效率，已成為目前的研究重點。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SS、有機物及重金屬，透過多組稀釋倍數與不同孔徑濾紙過濾水樣，建立廢水不同顆粒粒徑與其濃度之光譜資料庫，並發展一套多波長SS定性與定量的分析方法，藉此改善顆粒干擾光譜分析之問題，再配合其他成分之水樣資料庫，做為發展廢水水質監測系統的基礎。光譜分析方法應用倒傳遞類神經網路建立懸浮微粒濃度與其粒徑分佈之推估模式，無論在推估單顆粒或是多種粒徑顆粒混合之水樣，其推估結果誤差低於10%。將SS對UV/VIS/NIR吸收光譜產生之吸光值先予以扣除，再利用多成分定性定量演算法，其推估有機物或是重金屬水樣誤差低於5%。實廠驗證方面，藉由此量測技術可同時準確推估SS顆粒粒徑分佈、COD濃度及重金屬成分與濃度，其推估結果誤差低於15%，符合人工檢測誤差範圍。結果顯示，本研究所研發之量測技術具有穩定度及可靠度，未來可提供給業界或實廠即時廢水水質監測之技術，以提升廢汙水處理系統之成效。
| zh_TW |
| dc.description.abstract | Process automation has become one of the most important issues for water and wastewater industry to meet strengthening water quality and effluent standards. Therefore, it is important to research and develop various kinds of technology and device of an automatic real-time water quality 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 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 utilize spectrum analysis technique and back-propagation neural network to measure SS, organic compounds and heavy metals concentration. According to the experimental results shown, by diluting and filtering samples procedure can measure SS, organic compounds and heavy metals concentration and eliminate UV/VIS/NIR spectrum analysis interference with SS concentration and particle size. The result of SS concentration and particle size has shown the error was less 10%. Besides, using spectrum database and spectrum analysis to measure COD and heavy metals concentration, the error was less 15%.
Utilizing spectrum analysis to develop an automatic real-time water quality monitoring system for COD、 SS and heavy metals 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.
| en_US |
| DC.subject | SS | zh_TW |
| DC.subject | UV/VIS/NIR吸收光譜 | zh_TW |
| DC.subject | 有機物 | zh_TW |
| DC.subject | 重金屬 | zh_TW |
| DC.subject | 倒傳遞類神經 | zh_TW |
| DC.subject | SS | en_US |
| DC.subject | ANN | en_US |
| DC.subject | heavy metals | en_US |
| DC.subject | COD | en_US |
| DC.subject | UV/VIS/NIR absorption spectrum | en_US |
| DC.title | 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 | zh_TW |
| dc.language.iso | zh-TW | zh-TW |
| DC.title | Using UV/VIS/NIR Spectrum Analysis to Measure Simultaneous with SS, Organic Compounds and Heavy Metals Concentration | en_US |
| DC.type | 博碩士論文 | zh_TW |
| DC.type | thesis | en_US |
| DC.publisher | National Central University | en_US |