(3.227.0.150) 您好!臺灣時間:2021/05/08 09:27
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

: 
twitterline
研究生:張鈞凱
研究生(外文):Chang, ChunKai
論文名稱:整合性原水濁度檢測系統設計
論文名稱(外文):An Intergrated System Design For Water Turbidity Detection
指導教授:賴金輪
指導教授(外文):ChinLun Lai
口試委員:蒲冠志黃文傑
口試日期:2011-07-15
學位類別:碩士
校院名稱:亞東技術學院
系所名稱:資訊與通訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:78
中文關鍵詞:濁度檢測影像識別
外文關鍵詞:Turbidity DetectionImage Recongition
相關次數:
  • 被引用被引用:0
  • 點閱點閱:164
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:28
  • 收藏至我的研究室書目清單書目收藏:0
隨著科技的快速發展,以及用電的需求提升下,各個國家在替代能源的取得上,正積極開發與布局。而目前台灣已有的水力發電廠,要如何將發電效能和設備提升,在未來綠能發展上,將會是一項重要的議題。由於現今部分水力發電在取水濁度判斷上,大部分文獻多以採檢體方式分析較多,然而對於使用影像監控水質濁度的相關研究,卻渺渺無幾。在本論文中,我們提出一個包括浸入式光散射分析、多頻譜影像分析的整合技術,應用於台電東部水力發電廠的取水壩口,進行原水濁度的檢測,以保護發電機組安全的應用案例。本論文分析不同光譜在不同水質濁度下散射功率的變化,及在水體表面漸層擴散的場型差異,並將檢測結果傳回控制中心,提供給決策人員作為取水與否的判斷依據。實驗結果顯示,吾人所提出的檢測方法與系統,具有施行容易、有效,可適用於環境惡劣的水壩取水判斷,達到預防取水濁度過高而造成的設備損壞及供電損失的要求,故可供推廣發展的價值極高,預期可帶來相當程度的經濟效益與貢獻。
With the advancement of technology and the demands for electricity, every country has been trying to make overall arrangements for alternative energy. Currently in Taiwan, there are hydraulic power plants. How to increase their efficiency in power generation and improve their equipment will be an important issue for future green energy development. Nowadays, to decide influent water turbidity for hydraulic power generation, most of studies choose to take water samples for analyses. However, there are very few existing studies regarding video monitoring for water turbidity. In this paper, an integrating technology, including the immersion light-scattering analysis and the multi-spectral image analysis, is proposed to detect the water turbidity and is implemented in the dam intake of the Taipower east hydraulic power plant to protect the power generator. By analyzing the changes of scattered power with different spectra and water turbidity and the differences in the field patterns of water surface gradient diffusion, the analysis data are sent back to the control center for the decision makers to decide whether to take the water or not. The experiment results show that the proposed testing method and system are simple, efficient, and practical even under very bad weather conditions to make water intake decisions, thus meet the requirement of preventing equipment damage and power loss caused by high influent water turbidity. Therefore, this method is very valuable and should be promoted. It is expected that it will make a great contribution and improve economical effectiveness.
致謝 I
中文摘要 II
英文摘要 III
目錄 IV
表目錄 VII
圖目錄 VIII
第一章 介紹 1
1.1 研究背景與動機 1
1.2 相關文獻 2
1.3 構想與方法 6
1.4 論文架構 7
第二章 背景資訊與檢測設備 8
2.1 原水濁度與光散射資訊 8
2.1.1 高濁度原水的影響 9
2.1.2 高、中、低濁度原水的光散射特性 10
2-2 天長壩環境資訊 13
2.2.1 引水閘門資訊 13
2.2.2 天長壩口水質資訊 15
2.2.3 檢測環境選擇 16
2.3 檢測設備 18
2.3.1 浸入式檢測設備 18
2.3.2 非浸入式檢測設備 19
第三章 識別原理與系統架構 22
3.1設計理念 23
3.1.1 侵入式光訊號散射分析法 23
3.1.2 遙測型多頻譜信號場型分析法 24
3-2分析與處理 25
3.2.1 侵入式光訊號處理 25
3.2.2 遙測型場型影像前處理 26
3.2.3 濁度計算與分析演算法 28
3.2.4 環境參數影響與修正 30
3.3 應用於天長壩之檢測系統設計 35
3.3.1 侵入式檢測系統設計 35
3.3.2 遙測型檢測系統設計 37
第四章 實驗結果與討論 41
4.1 實驗室濁度檢測系統測試 42
4.2 天長壩濁度檢測系統測試 49
4.3 討論 58
4.3.1 系統效能分析 58
4.3.2 系統限制與解決方案 59
第五章 結論與未來工作 62
5.1 結論 62
5.2 未來工作 63
參考文獻 65
附錄 68
附錄 A:天長壩口原水濁度檢測結果 68
附錄 B:論文刊登 74

[1]HE Yingqing, DENG Ruru, CHEN Qidong, CHEN Lei, and QIN Yan, “Diffuse Attenuation Coefficient of Suspended Sediment based on ASD Spectrometer”, School of Geographic Science and Planning, Sun Yat sen University, Guangzhou 510275, China , vol. 50 (3): 134-140 2011.
[2]Choi, C. H., J. A. Abbott, B. Park, and Y. R. Chen. “Prediction of soluble solid and firmness in apple by visible/near-infrared spectroscopy”, 5th international symposium on fruit, nut, and vegetable production engineering. Davis, CA:U.S.A. 1997.
[3]Delwiche, S. R., M. M. Bean, R. E. Miller, B. D. Webb, and P. C. Williams, “Apparent amylase content of milled rice by near-infrared reflectance spectrophotometry”, Cereal Chem. 72 (2):182-187. 1995.
[4]Delwiche, S. R., K. S. McKenzie, and B. D. Webb. “Quality characteristics in rice by near-infrared reflectance analysis of whole-grain milled samples”, Cereal Chem. 73(2): 257-263. 1996.
[5]Tanabe, T., T. Akinaga, Y. Kohda, S. Kawasaki, Y. Kouno, H. Maeda, T. Mizuno, and H. Aoki, “Internal quality measurement of tropical fruits by near infrared spectroscopic technique (Part2)-Using the specific NIR absorption wavelength on water, cellulose and sugar”, Journal of the Japanese Society of Agricultural Machinery. 27(2): 71-76. 1996.
[6]Williams, P. C., and D. C. Sobering. “Comparison of commercial near infrared transmittance and reflectance instruments for analysis of whole grains and seeds.”, J. Near Infrared Spectrosc. 1 (1): 25-32. 1993.
[7]Sathyendranath S., “Remote sensing of ocean colour in coastal and other opticailly complex waters”, Reports of the International Ocean Colour Coordinating Group[C], No. 3, Dartmouth, Canada, 2000.
[8]He Qing, Tun Caixing, and Shi Weirong, “Remote sensing analysis of surface suspended sediment concentration in the Changjiang estuary”, Progress in Natural Science, vol. 9(6):440-446, 1999.
[9]Ruhl C A, “Combined use of remote sensing and continuous monitoring to analyze the variability of suspended sediment concentration in San Francisco bay California. Estuarine”, Coastal and Shelf Science, vol. 53 : 801~812, 2001.
[10]Meters L K, Smith M O, and Adams J B, “Estimating suspended sediment concentration in surface waters of t he Amazon River Wetlands from Landsat images”, Remote Sensing of Environment, vol. 43 : 281~301, 1993.
[11]Li Yan, Huang W, and Fang Ming. “An algorithm for the retrieval of suspended sediment in coastal waters of China from AV HRR data”, Continental Shelf Research, vol. 18 (5) : 487~5001, 1998.
[12]Lim, H.S., MatJafri, M.Z., and Abdullah, K. “Algorithm for turbidity mapping using digital camera images from a low-altitude light aircraft”, IEEE International Conference on Computer Science and Information Technology, pp.200-204, 2009.
[13]Tang Junwu and Tian Guoliang, “Ocean Color Analysis and an Algorithm for the Retrieval of Multiconstituents Based on Remote Sensing Reflectance” Journal of Remote Sensing, vol. 1(4):252-256, 1997.
[14]Regan, F. Lawlor, A. Flynn, B. O. Torres, J. Martinez-Catala, R. O'Mathuna, and C. Wallace, “A demonstration of wireless sensing for long term monitoring of water quality”, IEEE International Conference on Local Computer Network, pp. 819-825, 2009.
[15]Chih-Hsiung Chang and Chih-Yu, “The relevance between turbidity current distribution in reservoir and special event of catchment area.” Submitted to Department of Environmental Engineering and Science Fooyin University, Taiwan, R.O.C 25, July, 2008.
[16]http://vgekl.njnu.edu.cn/
[17]http://www.ks5u.com/
[18]http://kc.njnu.edu.cn/
[19]http://www.niea.gov.tw/
[20]姚仁泰,「過濾系統組合對原水濁度去除效能之研究」,碩士論文,國立成功大學地球科學研究所,台南(2007)

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔