臺灣博碩士論文加值系統

離心式冰水機故障種類，可分成急性(hard)及慢性(soft)故障二大類。其中慢性故障是指系統於運轉過程及不當維修保養所造成性能降低之故障，通常這類型故障前期並不容易辨別，造成故障發生後未能及時偵測診斷與通報，使故障被忽略一段時間，進而影響自動控制及性能監視系統的正常作動，更將造成大量能源消耗。有鑑於此，為了提高離心式冰水機長期穩定運轉之考量，發展自動化離心式冰水機自動化故障偵測與診斷之相關研究，就顯得十分重要。
本研究主要目的為發展創新離心式冰水機自動化故障偵測診斷策略。其研究內容如下，首先藉由文獻回顧尋求自動化FDD策略中，具有代表性之性能指標迴歸模式，並利用實驗室數據進行分析與綜合評估。再者藉由離心式冰水機故障模擬實驗，對於本文及其他文獻提出之故障分類器以圖解進行綜合分析，並以數值量化綜合評估本文所提出之創新離心式冰水機自動化FDD策略，於各種故障程度下之故障偵測率與故障診斷率。
研究結果發現僅有複變數多項式迴歸模式對於十一種性能指標之CVRMSE都在5%標準內，為四種模式之中對於此十一種性能指標之預測能力最佳。此外以圖解法結果發現，Wang and Cui故障分類器僅能診斷出三種故障，Reddy故障分類器可診斷四種慢性故障，而本文所提出之故障分類器能成功診斷出七種過程中慢性故障。最後以數值量化表示本文所提出策略之故障偵測與診斷率，結果發現於故障程度4時，其故障偵測率為67%~100%，故障診斷率為67%~100%。

There are two kinds of centrifugal chiller faults, “Hard faults”and“Soft faults”. Soft faults means system operating process and unsuitable maintaining cause low performance fault, it is usually hard to find in the early stage. The fault can’t be detected and promulgated immediately, effecting the automatic control and performance monitor normal operation, causing large energy consumption. In order to raise the operating stability of centrifugal chiller in a long term, studying on an Automated Fault Detection and Diagnosis (FDD) Strategy research appears very important.
The present paper studied on developing innovative Automated Fault Detection and Diagnosis (FDD) Strategy with centrifugal chiller. First, finding representative performance index regression model for Automated FDD Strategy from references and analyzing and estimating with experiment data. Second, by the experiment on the fault of centrifugal chiller, analyzing this paper and other references with chart and quantize the innovative Automated FDD Strategy with all kinds of faults in Fault detection rate and Fault Diagnosis rate.
The result revealed that only multivariate polynomial regression model eleven performance indexes are in 5% of CVRMSE standard. Four models have the best anticipative ability in eleven performance indexes. Otherwise, Wang’s fault classifier can only diagnose three kinds of faults and Reddy’s is four, but this paper is seven. Finally, when the fault degree reaches four, both the fault detection rate and the fault diagnosis rate are between 67~100%.

摘要 i
ABSTRACT ii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 前言 1
1.1 研究背景 1
1.2 文獻回顧 3
1.3 研究目的 6
第二章 故障偵測與診斷理論概述 7
2.1 離心式冰水機慢性故障的種類 7
2.2 故障偵測與診斷理論介紹 8
2.2.1 故障偵測 9
2.2.2 故障診斷 9
2.2.3 故障的評估 9
2.2.4 系統反應程序 10
第三章 創新離心式冰水機故障偵測與診斷策略 11
3.1 發展穩態過濾器 13
3.2 定義性能指標 14
3.3 建立性能指標之迴歸模式 18
3.3.1 文獻中性能指標迴歸模式 18
3.3.2 數據分析之統計原理 20
3.3.3 性能指標迴歸模式之求解流程 21
3.4 發展故障偵測門檻 27
3.5 建立故障分類器 30
第四章 實驗數據分析 33
4.1 實驗目的 33
4.2 實驗系統與設備 33
4.3 實驗內容 34
第五章 結果與討論 38
5.1 分析性能指標迴歸模式之適用性 38
5.2 評估各種故障分類器對於故障之診斷能力 44
5.2.1 Wang and Cui故障分類器 44
5.2.2 Reddy故障分類器 52
5.2.3 本文提出之故障分類器 60
5.3 綜合分析本策略之故障偵測率與故障診斷率 69
5.3.1 本策略之故障偵測率 69
5.3.2 本策略之故障診斷率 71
第六章 結論 73
參考文獻 75
符號說明 78

[1]胡耀袓，”台灣冷凍空調產業與技術發展現況”，第八屆海峽兩岸冷凍空調學術暨技術交流會，台中，2007。
[2]李宗興，”雙段離心式冰水機容量調節與喘振抑止控制邏輯之開發”，教育部產學合作計畫，2006。
[3]劉中哲、強忠萍、楊秉純、胡耀袓，”台灣地區R-134a 二級壓縮離心式壓縮機與製冷機組發展現況”，第八屆海峽兩岸冷凍空調學術暨技術交流會，台中，2007。
[4]陳俊漢、強忠萍、孫健理，”離心式冰水主機控制系統研究”，機械工業雜誌，287期，第57-59頁。
[5]Wang, S.W. and J.T. Cui. 2005b. A model-based online fault detection and diagnosis strategy for centrifugal chiller systems. International Journal of Thermal Sciences. 44(10):986-999.
[6]陳家榮，”冰水主機節能系統效率提昇”，能源服務業成功案例示範觀摩研討會，新竹，2006。
[7]林逸群，”應用專家系統於中央空調系統之故障診斷”，碩士論文，國立台北科技大學電機工程系碩士班，台北，2002。
[8]張佑民，”故障診斷專家系統於中央空調應用分析”，碩士論文，國立中山大學機械與機電工程研究所，高雄，2006。
[9]Braun, J.E. 2003. Automated fault detection and diagnostics for vapor compression cooling equipment. Transactions of the ASME. 125 (3):266-274.
[10]Jia, Y. and T.A. Reddy. 2003. Characteristic physical parameter approach to modeling chillers suitable for fault detection, diagnosis. Transactions of the ASME. 125(3):258-265.
[11]Katipamula, S. and M.R. Brambley. 2005a. Methods for fault detection diagnostics and prognostics for building systems-a review, part I. HVAC and R Research. 11(1):3-25.
[12]Katipamula, S. and M.R. Brambley. 2005b. Methods for fault detection, diagnostics, and prognostics for building systems-a review, part II. HVAC and R Research. 11(2):169-187.
[13]Wang, S.W. and J.T. Cui. 2005a. Sensor-fault detection, diagnosis and estimation for centrifugal chiller systems using principal-component analysis method. Applied Energy 82(3):197-213.
[14]Xu, X., F. Xiao, and S. Wang. 2008. Enhanced chiller sensor fault detection, diagnosis and estimation using wavelet analysis and principal component analysis methods. Applied Thermal Engineering 25(2-3):226-237.
[15]Wang, S.W. and J.T. Cui. 2006. A robust fault detection and diagnosis strategy for centrifugal chillers. HVAC and R Research. 12(3):407-428.
[16]Reddy, T.A. 2007a. Application of a generic methodology to assess four different chiller FDD methods (RP-1275). HVAC&R Research. 13(1):711-729.
[17]Reddy, T.A. 2007b. Formulation of a generic methodology for assessing FDD methods and its specific adoption to large chillers. ASHRAE Transactions 113(1):281-295.
[18]Reddy, T.A. 2007c. Development and evaluation of a simple model-based automated fault detection and diagnosis (FDD) method suitable for process faults of large chillers. ASHRAE Transactions 113(1):27-39.
[19]Isermann, R. 1984. Process fault detection based on modeling and estimation a survey. Automatica. 20(4):387-404.
[20]Armstrong, P., L. Norford, and S. Leeb. 2004. Fault detection in rooftop cooling equipment by power signature analysis, The 10th International Refrigeration Conference, USA.
[21]Kim, M., S.H. Yoon, P.A. Domanski, and W. Vance Payne. 2008. Design of a steady-state detector for fault detection and diagnosis of a residential air conditioner. International Journal of Refrigeration. Article in press.
[22]Yik, F.H.W. and V.K.C. Lam. 1998. Chiller model for plant design studies. Building Services Engineering Research and Technology. 19(4):233-242.
[23]Reddy, T.A. and K.K. Andersen. 2002. An evaluation of classical steady-state off –line linear parameter estimation methods applied to chiller performance data. HVAC&R Research 8(1):101-124.
[24]黃登源，”應用迴歸分析”，華泰文化，1998。
[25]趙民德、謝邦昌，”迴歸分析”，曉園出版社，2000。
[26]潘南飛，”工程統計”，全威圖書，2003。
[27]吳榮彬，”工程統計學原則與應用”，美商麥格羅希爾國際股份有限司台灣分公司，2003。
[28]徐世輝，”品質管理”，滄海書局，1991。
[29]張公緒、何國偉、錢仲候、鄭慧英，”品質管理”，曉園出版社，1996。
[30]張倫，“品質管理與管制”，華泰文他事業股份有限公司，2006。
[31]張織雲、呂汝漢、簡兆權編，”統計品質管理”，曉園出版社，1991。
[32]Comstock, M.C. and J.E. Braun. 1999. Experimental data from fault detection and diagnostic studies on a centrifugal chiller. ASHEAE RP-1043 Report # 4036-1.
[33]Hydeman, M., Sreedharan, P., Webb, N., and S. Blanc. 2002. Development and testing of a reformulated regression-based electric chiller model. ASHRAE Transactions. HI-18-2.