Effect of Pilot Injecton on Diesel Combustion : 2nd Report, Improvement in Trade-Off between NO_x and Fuel Consumption

To reduce the level of exhaust emissions and to improve ignition characteristics, the effect of pilot injection was investigated in a turbocharged direct-injection diesel engine. As a result, it is found that the pilot injection shows some significant effects on reducing the ignition delay and on improving the trade-off relationship between NO_x and fuel consumption. The improvement in the trade-off relationship by pilot injection is observed in both the low-cetane fuel and the high-quality fuel. This simultaneous reduction in NO_x and fuel consumption is caused by a slow rate of pressure rise during the initial combustion which results in a higher mechanical efficiency and a lower cooling loss. In the short interval between pilot and main injection, a small amount of pilot injection is rcommended to reduce both NO_x and fuel consumption without increasing smoke

[[alternative]]Balancing control of humanoid robots based on hand movement

碩士[[abstract]]本論文實現一個利用雙手運動來補償人形機器人重心移動的平衡控制方法。本論文透過一台小型人形機器人之腳底加裝壓力感測器來量測重心，再加上本論文所提出之雙手運動補償方法來讓人形機器人可以實現雙腳及單腳支撐下的自主平衡，並完成如抬腳或踢球等需要平衡能力的動作。在機器人的動作軌跡部分，本論文運用工業用核心電腦計算出機器人雙足末端點位置後傳給FPGA (Field-Programmable Gate Array)，再透過FPGA內部之模組運算相對於末端點的關節馬達角度以控制人形機器人的姿態。在平衡的部分，本論文以機器人的重心位置來判斷機器人的平衡狀態，而後根據所提出的模糊控制器來修正機器人的雙手轉動以完成平衡動作。由實驗結果得知，本論文所提出之系統可以有效的修正機器人姿態，以增加平衡穩定性。[[abstract]]A humanoid robot balance control method based on both of the hand movement is proposed in this thesis. A humanoid robot with 23 degree of freedom and 8 force sensors is designed as the platform. The proposed balance method determines the movement of the hands to compensate the movement of the robot’s center of gravity. The robot is able to execute the lifting leg or kicking ball motion in the one leg support situation. An IPC is applied to calculate the trajectory of the foot of the humanoid robot. The result of the trajectory of the foot is sent to FPGA (Field-Programmable Gate Array) board for calculate the relate angle of the motor based on inverse kinematic. The proposed system measures the center of gravity of the humanoid robot by the force sensors. The proposed fuzzy controller calculates the hand movement to balance the robot by the center of the gravity of the robot. The practical experiments with different situations are presented to illustrate the efficiency of the proposed method.[[tableofcontents]]目錄 中文摘要……………………………………………………………I 英文摘要…………………………………………………………...II 目錄 ................................................................................................................. III 圖目錄 ........................................................................................................... VII 表目錄 ........................................................................................................... XII 第一章 緒論 ..................................................................................................... 1 1.1 研究背景 ............................................................................................. 1 1.2 研究動機 ............................................................................................. 3 1.3 論文架構 ............................................................................................. 4 第二章 人形機器人系統規格介紹 ................................................................. 5 2.1 前言 ..................................................................................................... 5 2.2 人形機器人核心控制板規格介紹 ..................................................... 6 2.2.1 TKU Board單板電腦規格介紹 ................................................ 6 2.2.2 H3C40–V6核心板規格介紹..................................................... 7 2.3 人形機器人機構平台介紹 ................................................................. 9 2.3.1 頭部機構介紹 ......................................................................... 11 2.3.2 手部機構介紹 ......................................................................... 12 2.3.3 腰部機構介紹 ......................................................................... 13 2.3.4 腳部機構介紹 ......................................................................... 14 2.3.5 腳底機構介紹 ......................................................................... 15 2.4 人形機器人人機介陎介紹 ............................................................... 17 2.4.1 動作控制人機介陎介紹 ......................................................... 18 2.4.2 腳底壓力感測人機介陎介紹 ................................................. 20 第三章 人形機器人核心系統設計 ............................................................... 21 3.1 前言 ................................................................................................... 21 3.2 人形機器人策略系統設計 ............................................................... 22 3.2.1 影像擷取模組設計 ................................................................. 23 3.2.2 策略命令傳送模組設計 ......................................................... 24 3.2.3 腳底壓力感測人機介陎設計 ................................................. 25 3.3 人形機器人FPGA核心設計 ........................................................... 27 3.3.1 資料分析模組設計 ................................................................. 28 3.3.2 確認回應模組設計 ................................................................. 30 3.3.3 SOPC模組設計 ....................................................................... 31 3.3.4 感測器回授模組設計 ............................................................. 33 3.3.5 動作控制模組設計 ................................................................. 35 第四章 人形機器人運動控制 ....................................................................... 37 4.1 前言 ................................................................................................... 37 4.2 人形機器人逆運動學介紹 ............................................................... 38 4.2.1 身體水平側移姿勢 ................................................................. 39 4.2.2 身體旋轉側移姿勢 ................................................................. 41 4.2.3 縮腿與跨步姿勢 ..................................................................... 43 4.3 人形機器人單腳運動軌跡設計 ....................................................... 46 第五章 模糊系統於人形機器人單腳平衡控制 ........................................... 47 5.1 前言 ................................................................................................... 47 5.2 人形機器人ZMP演算法設計 ......................................................... 47 5.3 人形機器人旋轉側移模糊控制器設計 ........................................... 50 5.4 人形機器人輔助平衡模糊控制器設計 ........................................... 53 5.4.1 人形機器人輔助平衡模糊控制器於X軸之設計 ................ 54 5.4.2 人形機器人輔助平衡模糊控制器於Y軸之設計 ................ 57 第六章 實驗結果 ........................................................................................... 60 6.1 人機介陎觀測零力矩點實驗 ........................................................... 60 6.2 雙腳支撐相修正實驗 ....................................................................... 64 6.3 單腳支撐相修正實驗 ....................................................................... 71 第七章 結論與未來展望 ............................................................................... 76 參考文獻 ......................................................................................................... 77 圖目錄 圖 2.1、第九代人形機器人實體圖 ................................................................ 5 圖 2.2、TKU Board單板電腦(a)正陎圖與(b)反陎圖 .................................. 6 圖 2.3、H3C40–V6核心板(a)正陎圖與(b)反陎圖 ....................................... 8 圖 2.4、第九代機器人(a)模擬圖與(b)實體圖............................................. 10 圖 2.5、頭部馬達自由度配置圖 .................................................................. 11 圖 2.6、手部馬達自由度配置圖 .................................................................. 13 圖 2.7、腰部馬達自由度配置圖 .................................................................. 14 圖 2.8、腳部馬達自由度配置圖 .................................................................. 15 圖 2.9、腳底機構(a)分解模擬圖與(b)實體分解圖 .................................... 16 圖 2.10、腳底機構裝配(a)分解圖與(b)實體成品圖 .................................. 17 圖 2.11、動作控制人機介陎示意圖 ............................................................ 18 圖 2.12、動作控制人機介陎示意圖 ............................................................ 19 圖 2.13、動作控制人機介陎示意圖 ............................................................ 20 圖3.1、總系統方塊圖 ................................................................................... 22 圖3.2、策略系統方塊圖 ............................................................................... 23 圖3.3、影像處理步驟影像示意圖 ............................................................... 24 圖3.4、命令傳送流程圖 ............................................................................... 25 圖3.5、介陎流程圖 ....................................................................................... 26 圖3.6、FPGA核心系統方塊圖 .................................................................... 28 圖3.7、資料分析模組方塊圖 ....................................................................... 28 圖3.8、確認回應模組方塊圖 ....................................................................... 30 圖3.9、溝通示意圖 ....................................................................................... 30 圖3.10、SOPC模組方塊圖 .......................................................................... 31 圖3.11、感測器回授模組方塊圖 ................................................................. 33 圖3.12、動作控制模組方塊圖 ..................................................................... 35 圖3.13、動作執行流程圖 ............................................................................. 36 圖4.1、機器人雙足座標系示意圖 ............................................................... 37 圖4.2、機器人單腳運動姿勢簡易示意圖 ................................................... 38 圖4.3、Y軸、Z軸末端點與馬達角度關係圖 ........................................... 40 圖4.4、馬達與逆運動學角度關係圖(a)正轉圖與(b)反轉圖 ..................... 41 圖4.5、身體旋轉角度示意圖(a) 踝關節與(b)髖關節 ............................... 42 圖4.6、踝關節與髖關節與身體旋轉角度示意圖 ....................................... 43 圖4.7、X軸、Z軸末端點與馬達角度關係圖 ........................................... 44 圖4.8、踢球軌跡示意圖 ............................................................................... 46 圖5.1、機器人雙足座標系示意圖 ............................................................... 48 圖5.2、旋轉側移模糊控制器方塊圖 ........................................................... 50 圖5.3、旋轉側移輸入示意圖(a) errory與(b) errory'' ................................... 51 圖5.4、旋轉側移示意圖 ............................................................................... 51 圖5.5、旋轉側移輸出示意圖 ....................................................................... 52 圖5.6、機器人雙足座標系示意圖 ............................................................... 54 圖5.7、輔助平衡控制器(X軸)方塊圖 ........................................................ 54 圖5.8、輔助平衡控制器(X軸)輸入示意圖(a) errorx與(b) errorx'' ............ 55 圖5.9、輔助平衡控制器(X軸)輸出示意圖 ................................................ 56 圖5.10、機器人X軸輔助平衡示意圖 ........................................................ 56 圖5.11、輔助平衡控制器(Y軸)方塊圖 ...................................................... 57 圖5.12、輔助平衡控制器(Y軸)輸入示意圖(a) errory與(b) errory'' .......... 58 圖5.13、輔助平衡控制器(Y軸)輸出示意圖 .............................................. 58 圖5.14、機器人Y軸輔助平衡示意圖 ........................................................ 59 圖6.1、機器人站立(a)零力矩點圖(b)正視圖(c)側視圖 ............................. 61 圖6.2、機器人旋轉測移動作(a)零力矩點圖(b)正視圖(c)側視圖 ............. 62 圖6.3、機器人單腳站立(a)零力矩點圖(b)正視圖(c)側視圖 ..................... 63 圖6.4、水平置放機器人 ............................................................................... 65 圖6.5、水平置放機器人 ............................................................................... 66 圖6.6、木板順時針傾斜5度 ....................................................................... 67 圖6.7、木板順時針傾斜5度 ....................................................................... 68 圖6.8、木板逆時針傾斜5度 ....................................................................... 69 圖6.9、木板逆時針傾斜5度 ....................................................................... 70 圖6.10、機器人旋轉側移中心之連續動作圖 ............................................. 72 圖6.11、機器人輔助平衡之動作示意圖 ..................................................... 73 圖6.12、旋轉側移零力矩點改變示意圖 ..................................................... 74 圖6.13、輔助平衡零力矩點示意圖 ............................................................. 75 表目錄 表2.1、TKU Board單板電腦之系統規格 ..................................................... 7 表2.2、H3C40–V6核心板之系統規格 ......................................................... 8 表2.3、機器人馬達配置表 ........................................................................... 10 表3.1、指令封包格式表 ............................................................................... 29 表3.2、指令封包對應表 ............................................................................... 29 表3.3、感測器回授封包格式表 ................................................................... 34 表3.4、感測器編號表 ................................................................................... 34 表5.1、旋轉側移規則庫 ............................................................................... 53 表5.2、X軸輔助平衡規則庫 ....................................................................... 57 表5.3、Y軸輔助平衡規則庫 ....................................................................... 59 表6.1、誤差比較表 ....................................................................................... 71[[note]]學號: 600460041, 學年度: 10

探討泰國和台灣選擇C2C物流公司之關鍵因素研究

本研究旨在探討影響消費者選擇C2C物流公司之行為，並瞭解消費者對於選擇泰國和台灣物流公司之重要趨勢決定因素。第一階段的研究先調查第三方物流提供者，並搜尋相關重要趨勢的文獻，整理出決策合作層級架構之潛在重要因子。 本研究以問卷衡量決策層級架構的因素等級。共蒐集400份有效問卷，來自泰國和台灣的問卷各為200份。本研究採用分析層級程序法Analysis Hierarchy Process (AHP)，其用以計算三種物流等級在全球各地的要素權重，因此能夠更合理解釋泰國和台灣的物流業要素。 研究結果發現4項對於泰國物流業的關鍵性成功要素(KSFs)為「運價」、「準時交貨」、「服務質量」、「交貨期短」。台灣物流業的關鍵性成功要素則為「運價」、「服務質量」、「準時交貨」、「即時回應要求」。其中「運價」這項關鍵性成功要素對於兩國的重要性層級是相同的。因此泰國和台灣的C2C物流公司與物流業者可以參考本研究結果的關鍵成功要素(KSFs)。The purpose of this study aims to investigate the factors affecting the behavior of consumers for selecting the C2C Logistics companies and determines the factors which given a better comprehension of the importance trends in decision-making of selecting logistics provider in Thailand and Taiwan. The first step of this research is to investigate of important factor trends of C2C logistics provider and identify relevant factors from important factor trend by searching in the related literature. Then, we can arrange potentially factors cooperate with decision hierarchical structure. The levels of factors in decision hierarchical structure were determined by questionnaire survey. There are 400 valid samples, of which 200 samples belong to Thailand and 200 samples belong to Taiwan. In this research, we apply Analysis Hierarchy Process (AHP) method cooperated with the three ranking logic to calculate in the global weight for each factor. From the result of complete independent law, we can claim that the weight in each important factor seems to be more reasonable in both Thailand and Taiwan. Therefore, there are 4 KSFs in each country which in Thailand are: “transport price”, “on-time delivery”, “quality of service” and “short lead time”. While, Taiwan are: “transport price”, “quality of service”, “on-time delivery” and “prompt response to claim”. Interestingly, there is one of KSFs: “transport price” which is first rank and same rank of both countries as well. Thus, based on the result, we proposed these finding and reason for selecting KSFs to C2C logistics companies in both Thailand and Taiwan.摘 要 I Abstract II Table of Contents III List of Table V List of Figures VII Chapter 1 Introduction 1 1.1 Research Background 1 1.2 Research Motivation 3 1.3 Research Objective and Research Questions 4 1.4 Research Process 5 Chapter 2 Literature Review 6 2.1. B2B 6 2.2. B2C 7 2.3. C2C 7 2.4. Defining Characteristics of C2C Logistics Companies 8 2.5 Empirical Key Factor List for C2C Logistics Companies Selection 10 Chapter 3 Research Methodology 21 3.1 AHP 21 3.1.1 Step of AHP 23 3.1.2 Strength of AHP 28 3.1.3 Weakness of AHP 29 3.2 The Three Ranking Logic to Calculate the Global Weights 30 3.2.1 Partial Inheritance Law 31 3.2.2 Complete Inheritance Law 32 3.2.3 Complete Independent Law 33 3.3 Establishment of The Research Model 33 3.3.1 Decision Hierarchy Model 34 Chapter 4 Data Analysis and Research Finding 37 4.1 Research Design 37 4.1.1 Questionnaire Design 37 4.1.2 Research Target 38 4.1.3. Population and Sample Size 39 4.1.4. Sample Collecting Method and Time Period 40 4.2 Data Analysis 41 4.2.1. Basic Information of the Subject in Model 41 4.2.2. The Eigen value, the Eigenvector, and the Consistency of Level 2 in Model 44 4.3 The Three Ranking Logic for Model 47 4.3.1 Partial Inheritance Law 47 4.3.2 Complete Inheritance Law 53 4.3.3 Complete Independent Law 56 4.4 Discussion-Model 59 4.4.1 Comparison of Three ranking Logic 59 4.5 Research Findings 75 4.5.1 The Finding and Reason for Selecting KSFs in Case of Thailand 75 4.5.2 The Finding and Reason for Selecting KSFs in Case of Taiwan 77 Chapter 5 Conclusion and Discussion 81 Reference 83 Appendix 9

Optimal Efficiency Design of IPM Brushless DC Motor for Air Conditioners

[[abstract]]室內空調機之送風馬達，大多採用傳統的交流感應馬達。其轉子側感應電流產生轉矩，造成二次側銅損，降低效率。近年來永磁無刷直流馬達強調運轉安靜與高效率，已逐漸取代傳統送風馬達。 本論文利用有限元素分析軟體MagneForce進行120度方波驅動之空調用內藏式無刷直流馬達特性分析，針對其效率提升進行研究。由於馬達在結構設計上的差異程度會影響到整體特性及效率，本文以變更原始結構如氣隙寬度、磁石厚度及線圈線徑等來模擬馬達的輸出特性，並作為最佳化實驗因子。最後配合田口法、模糊田口法與雙反應曲面法預估各種組合，依照新的參數來搜尋出效率最高的馬達幾何結構。[[abstract]]Of blower motor for air conditioners, mostly uses traditional the AC induction motor. Its rotor side induced current has the torque, creates secondary copper losses, cuts the efficiency. In recent years emphasized the permanent magnet motor quiet operation and high efficiency, has substituted for the tradition blower motor gradually. In this paper, the use of finite element analysis software MagneForce to 120 degrees square drive of characteristic analysis for interior permanent magnet-type brushless DC motor for air conditioners, in view of its efficiency promotion conducts the research. Due to the structural design of the motor in the extent of the differences will affect the overall characteristics and efficiency, in order to change the original structure of this paper, such as air-gap width, magnet thickness and coil diameter, and so on simulate motor's output characteristics, and as optimization experiment factor. Finally, with the Taguchi method ,fuzzy-based Taguchi experimental design method and dual response surface method predicted a variety of combinations, in accordance with the new parameters to search for maximum efficiency of motor geometry

Determination of immune memory to hepatitis B vaccination through early booster response in college students.

The long-term protection of hepatitis B (HB) vaccination has been debated for years. The purpose here was to evaluate the kinetic changes of antibody to HB surface antigen (anti- HBs) and define immune memory of the HB vaccine among college students who had previously received full neonatal immunization against HB. In all, 127 college students aged 1823 years born after July 1984 who had completed HB vaccination and were seronegative for all three HB viral markers, including HB surface antigen (HBsAg), antibody to HB core protein (anti-HBc), and anti-HBs, were recruited. They received three doses of HB vaccine at enrollment, 1 month and 6 months after enrollment. Their anti-HBs titers were assayed at enrollment, 7-10 days, 1 month, 6 months, and 7 months following the first dose of HB vaccine. The anti-HBs seroprotective rates for subjects 7-10 days, 1 month, 6 months, and 7 months postvaccination were 20.5%, 75 .6%, 94.5%, and 99.2%, respectively. Those who were seroprotective at 7 to 10 days after one dose of HB vaccine booster developed significantly higher levels of anti-HBs at 1 and 6 months than those not developing seroprotective anti-HBs response at an earlier timepoint. Conclusion: At least one-quarter of HB vaccinees have lost their immune memory to the HB vaccine when entering college. Immune memory to HB vaccine was identified by early seroconversion, which was present in only 20% of vaccinees in the present study. To ensure higher than 90% anti-HBs seroconversion rates, at least 2 doses of HB booster vaccines are recommended for at-risk youths who received complete HB vaccinations in neonatal or infant periods but are seronegative for HBsAg, anti-HBs, and anti-HBc in adolescence

專線遠端遙控障礙監測架構

[[abstract]]一種專線遠端遙控障礙監測架構，係採用手機作為遠端測試平台，並利用目前所有行動電話都具備之簡訊傳送功能作為操作介面，障礙查修人員可利用個人所配備之手機傳送障礙查測功能至本系統，系統依照使用者所要求之查測項目，取出專線資料進行自動測試流程，最後並以簡訊回傳查測結果至查修人員手機。提供障礙查修人員迅速找出障礙點以排除障礙