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研究生：	林育正 Lin, Yu-Cheng
論文名稱：	點雲建築資訊模型倒塌模式生成與預測 Collapse Mode Generation and Prediction for Point Cloud BIM
指導教授：	侯琮欽 Hou, Tsung-Chin
學位類別：	碩士 Master
系所名稱：	工學院 - 土木工程學系 Department of Civil Engineering
論文出版年：	2019
畢業學年度：	107
語文別：	中文
論文頁數：	82
中文關鍵詞：	相似度、人工神經網路、建築資訊模型、搜索與救援
外文關鍵詞：	search and rescue, artificial neural network, building information modeling, search and rescue
相關次數：	點閱：111 下載：10
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台灣位於環太平洋地震帶上，近年來頻繁的發生規模龐大的自然災害，更有地震的重大災情傳出。地震災害影響之範圍巨大且環境十分艱困危險，且震後救災人員須針對已損害的結構物在短時間內進行搜索與救援(search and rescue, SAR)。隨著電腦科技的進步和建築資訊數位化的相關研究，吾人發想一套結合建築資訊模型(building information modeling, BIM)與動態模擬(dynamic simulation)的系統，規劃一套分析倒塌結構物的流程。本研究將提出一套依據倒塌結構物外部資訊預測內部構件分布的流程。主要內容為利用點雲資料(point cloud data, PCD)配合物件識別(Object Identifier, OID)，依據尺寸大小、相對位置以及梁柱分類標籤化各構件，並依外觀資訊(facade information)建立BIM模型，最後匯入倒塌模擬引擎建立倒塌模擬資料庫。本研究核心步驟為利用歐氏距離和夾角餘弦進行相似度運算與以人工神經網路(Artificial Neural Network，ANN)建立數學模型，兩套方法比對倒塌案例與倒塌模型資料庫。
本研究成果為利用離散元素法建置BIM模型，並且產生大量人工地震進行建築物的倒塌模擬，模擬結果可集合為倒塌模擬資料庫，資料庫可經由兩種方式進行檢驗，一為利用歐氏距離相似度與夾角餘弦相似度進行自我檢驗，利用外部構件相似度與內部構件相似度之相關係數，依據不同的分布狀況，可推論資料庫之優劣與判斷資料庫可能之缺失；一為利用人工神經網路建置數學模型，藉以數學化資料庫，利用倒塌模擬資料進行訓練人工神經網路，再分別依據位移或旋轉進行歐氏距離或夾角餘弦的檢驗，此法可加速輔助SAR行動，且本研究認為此法可藉由增加數學模型複雜度或增加倒塌模擬資料進行優化。

Taiwan is located in the Ring of Fire. In recent years, serious natural disasters have occurred frequently, especially earthquake. The seismic disasters result in structural failures and collapses, and the disaster relief personnel must search and rescue (SAR) for survivors in damaged structures in a short time. This study sets up a system to support SAR action that combines building information modeling (BIM) and dynamic simulation for building a database of the collapse structural model and presents a set of procedures for predicting the internal information based on external information in collapsed structures. This study is divided into three major topics, namely “Building information modeling”, “Similarity algorithms” and “The Mathematization of database”. The first theme uses the 3D computer graphics software, Blender, to make the building information model and simulates with discrete element method (DEM) then collect the results of different seismic periods to database. The second theme applies Euclidean distance and cosine similarity to measure similarity then compare each results of similarities to find the most suitable BIM model for analysis. The last theme applies artificial neural network (ANN) to mathematize the database of the collapse structural model then determine the feasibility of mathematizing with ANN. The results showed the system can predict the internal information based on external information in collapsed BIM model and how to self-test the database and the ANN is useful to mathematize the database. This study obtains good performance with reliability and efficiency because of great resolution capability and simple algorithms and processes.

摘要 ..........................................................................................................................III 
目錄 ..........................................................................................................................XI 
表目錄...................................................................................................................XIV 
圖目錄.................................................................................................................... XV 
第一章緒論 ............................................................................................................. 1 
1 研究動機與目的......................................................................................... 1 
2 研究內容 ..................................................................................................... 2 
3 研究流程 ..................................................................................................... 2 
第二章文獻回顧..................................................................................................... 4 
1 結構物模型建立......................................................................................... 4 
1.1 結構物件辨識.......................................................................................... 5 
1.2 建築資訊模型.......................................................................................... 6 
2 離散元素法................................................................................................. 7 
3 候選解 ......................................................................................................... 8 
3.1 局部搜索.................................................................................................. 9 
4 相似度計算(Similarity Measurement)........................................................ 9 
4.1 歐氏距離法............................................................................................ 10 
4.2 曼哈頓距離............................................................................................ 10 
4.3 切比雪夫距離........................................................................................ 11 
4.4 夾角餘弦................................................................................................ 11 
4.5 漢明距離................................................................................................ 12 
5 數值標準化............................................................................................... 12 
5.1 min-max標準化(Min-max normalization) ........................................... 13 
5.2 對數標準化............................................................................................ 13 
5.3 反正切標準化........................................................................................ 13 
5.4 z-score標準化....................................................................................... 14 
5.5 邏輯函數標準化.................................................................................... 14 
6 數學模型 ................................................................................................... 14
6.1 人工神經網路........................................................................................ 14 
6.2 交叉驗證................................................................................................ 17 
第三章模型建立流程與數據演算方法............................................................... 21 
1 研究流程概述........................................................................................... 21 
2 建築資訊模型建立................................................................................... 25 
2.1 建模工具-Blender 2.79.......................................................................... 25 
2.2 模型設計................................................................................................ 25 
2.3 構件斷面尺寸與材料參數說明............................................................ 27 
2.4 人工地震與倒塌模擬資料庫................................................................ 29 
3 相似度演算法........................................................................................... 30 
3.1 歐氏距離法............................................................................................ 30 
3.2 夾角餘弦................................................................................................ 30 
3.3 min-max標準化(Min-max normalization) ........................................... 31 
3.4 z-score標準化....................................................................................... 31 
3.5 相似度.................................................................................................... 31 
3.6 皮爾遜相關係數.................................................................................... 32 
3.7 Leave-one-out CV.................................................................................. 33 
4 數學模型 ................................................................................................... 33 
4.1 建立人工神經網路................................................................................ 33 
4.2 10-fold CV ............................................................................................. 33 
第四章成果與分析............................................................................................... 34 
1 第1輪模擬(騎樓模型1、參數設定1)................................................... 34 
1.1 相似度演算法........................................................................................ 34 
1.2 數學模型................................................................................................ 39 
2 第2輪模擬(騎樓模型1、參數設定2)................................................... 42 
2.1 相似度演算法........................................................................................ 42 
2.2 數學模型................................................................................................ 47 
3 第3-1輪模擬(騎樓模型1、參數設定3) ............................................... 49 
3.1 相似度演算法........................................................................................ 49 
3.2 數學模型................................................................................................ 54 
4 第3-2輪模擬(騎樓模型2、參數設定3) ............................................... 56
4.1 相似度演算法........................................................................................ 56 
4.2 數學模型................................................................................................ 61 
5 第3-3輪模擬(騎樓模型3、參數設定3) ............................................... 63 
5.1 相似度演算法........................................................................................ 63 
5.2 數學模型................................................................................................ 64 
6 模擬成果比較........................................................................................... 65 
6.1 相似度演算法........................................................................................ 65 
6.2 數學模型................................................................................................ 65 
第五章結論與建議............................................................................................... 66 
1 結論 ........................................................................................................... 66 
2 建議 ........................................................................................................... 68 
參考文獻.................................................................................................................. 69 
附錄一...................................................................................................................... 76 
騎樓模型1構件清單.......................................................................................... 76 
騎樓模型2構件清單.......................................................................................... 78 
騎樓模型3構件清單.......................................................................................... 81

                                    

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