系統識別號 | U0002-0407201713182400 |
---|---|
DOI | 10.6846/TKU.2017.00105 |
論文名稱(中文) | 具異質性Burr XII 型分配下複合動態系統的可靠度研究 |
論文名稱(英文) | Reliability Inference on Composite Dynamic Systems Based on Burr Type-XII Distribution under Heterogeneity |
第三語言論文名稱 | |
校院名稱 | 淡江大學 |
系所名稱(中文) | 統計學系應用統計學碩士班 |
系所名稱(英文) | Department of Statistics |
外國學位學校名稱 | |
外國學位學院名稱 | |
外國學位研究所名稱 | |
學年度 | 105 |
學期 | 2 |
出版年 | 106 |
研究生(中文) | 李依潔 |
研究生(英文) | YI-JIE LI |
學號 | 604650118 |
學位類別 | 碩士 |
語言別 | 繁體中文 |
第二語言別 | |
口試日期 | 2017-06-28 |
論文頁數 | 29頁 |
口試委員 |
指導教授
-
蔡宗儒(078031@mail.tku.edu.tw)
委員 - 吳柏林(berlin@nccu.edu.tw) 委員 - 林豐澤(ftlin@faculty.pccu.edu.tw) |
關鍵字(中) |
貝氏估計 風險函數 馬可夫鏈蒙地卡羅演算法 最大概似估計 順序統計量 |
關鍵字(英) |
Bayesian estimation Hazard function Markov chain Monte Carlo algorithm Maximum likelihood estimation Order Statistic |
第三語言關鍵字 | |
學科別分類 | |
中文摘要 |
複合動態系統廣泛地存在可靠度的應用中,在複合動態系統的設計中,每一元件的失效,皆會造成存活的元件需要承受更高的應力,並增加故障率。本論文使用Burr XII型分配作為元件壽命的基準分配,採用次方趨勢條件比例故障率模型描述系統的元件失效風險,使用Metropolis-Hasting馬可夫鏈蒙地卡羅演算法來估計模型中的參數,並以蒙地卡羅模擬評估估計方法的成效。 |
英文摘要 |
The composite dynamic system has been widely used in practical reliability applications. In the design of composite dynamic system, each component failure induces higher loading on surviving components, and then increases the hazard rate of surviving components. We consider using the Burr type-XII distribution as the lifetime model of components in a composite dynamic system and use power-trend hazard rate function to model the hazard function. Moreover, we develop the Metropolis-Hasting Markov chain Monte Carlo procedure for estimating the model parameters. A simulation study is carried out to evaluate the performance of the proposed estimation method. |
第三語言摘要 | |
論文目次 |
目錄 表格目錄 II 第一章 緒論 1 1.1研究動機 1 1.2論文架構 2 第二章 文獻回顧 3 第三章 方法介紹 9 第四章 模擬結果 15 第五章 結論 24 參考文獻 25 表格目錄 表 3. 1對Burr XII型分配所計算的偏態係數與峰度係數 (參考Burr (1941)) 19 表 3. 2 在有資訊的事前分配、β=5、λ=2、θ=1.002的情況下,所估計的偏差與均方誤差 20 表 3. 3 在有資訊的事前分配、β=5、λ=5、θ=1.002的情況下,所估計的偏差與均方誤差 20 表 3. 4 在有資訊的事前分配、β=5、λ=9、θ=1.002的情況下,所估計的偏差與均方誤差 20 表 3. 5 在有資訊的事前分配、β=8、λ=2、θ=1.002的情況下,所估計的偏差與均方誤差 21 表 3. 6 在有資訊的事前分配、β=8、λ=5、θ=1.002的情況下,所估計的偏差與均方誤差 21 表 3. 7 在有資訊的事前分配、β=8、λ=9、θ=1.002的情況下,所估計的偏差與均方誤差 21 表 3. 8 在無資訊的事前分配、β=5、λ=2、θ=1.002的情況下,所估計的偏差與均方誤差 22 表 3. 9 在無資訊的事前分配、β=5、λ=5、θ=1.002的情況下,所估計的偏差與均方誤差 22 表 3. 10 在無資訊的事前分配、β=5、λ=9、θ=1.002的情況下,所估計的偏差與均方誤差 22 表 3. 11 在無資訊的事前分配、β=8、λ=2、θ=1.002的情況下,所估計的偏差與均方誤差 23 表 3. 12 在無資訊的事前分配、β=8、λ=5、θ=1.002的情況下,所估計的偏差與均方誤差 23 表 3. 13 在無資訊的事前分配、β=8、λ=9、θ=1.002的情況下,所估計的偏差與均方誤差 23 |
參考文獻 |
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