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博碩士論文 etd-0713117-222839 詳細資訊
Title page for etd-0713117-222839
論文名稱
Title
以機器視覺抑制移動中水杯外溢之平衡系統
An Image-Based Self-Balance System to Suppress Water Spill for a Moving Cup
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
174
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2017-08-11
繳交日期
Date of Submission
2017-08-21
關鍵字
Keywords
機器視覺、液面晃動力學模型、液面晃動預測、模糊控制、單軸機械手臂
Single-axis robotic arm, Machine vision, Prediction of sloshing liquid surface, Fuzzy control, Sloshing dynamic model
統計
Statistics
本論文已被瀏覽 5673 次,被下載 38
The thesis/dissertation has been browsed 5673 times, has been downloaded 38 times.
中文摘要
人在拿咖啡杯行走時,會透過眼睛觀察容器內液體行為,嘗試經由手腕抑制杯內液體之晃動。本論文結合流體力學模擬的結果與實際水杯晃動實驗發展出一平衡控制方法,同時亦提出一模糊平衡控制器之設計。透過單軸機械平衡系統模仿人類手腕的轉動,並利用攝影機觀測杯內液體晃動幅度,人類靈巧的手眼協調技能可以因而重現。
首先藉由流體場方程式建立水杯受擾動液面晃動力學模型,以了解杯內液體受前後、俯仰擾動後的液面變化特性。而經過一連串的影像處理過程,從攝影機擷取的影像中可解析出液面振幅大小。接著分析液體晃動之週期性行為,可發展出液面晃動預測之平衡控制方法。而為了要模擬人的思維與推理機制,亦提出一模糊控制策略。最後結合單軸機械手腕與攝影機組成之單軸機械平衡系統,透過所提出之兩種控制方法轉動杯子以抑制液面高度的增加。
總共進行兩種實驗,定點平衡實驗與行走平衡實驗,以檢視所提出控制策略之成效。在定點平衡實驗中,振幅抑制速度比起無平衡控制狀況下,液面晃動預測法與模糊控制法分別增加了至少32%與104%。而在行走實驗中,所產生的最大晃動振幅比起無平衡控制狀況下,所提出兩種平衡方法分別降低至少24%與50%;且在行走過程中,超過5 mm高度的振幅次數減少量亦分別明顯超過81%與71%。因此,本論文所提出的兩種平衡液面晃動控制策略均能成功地模仿人在行走時為了防止杯內液體溢出杯外的手眼協調行為,且實驗結果顯示模糊控制法優於液面晃動預測法。
Abstract
When a human walks with a cup of coffee, he usually tries to suppress the sloshing in the cup with his wrist by monitoring the liquid behavior inside the container. In this thesis, a balance control approach by combing fluid mechanics simulation results with actual shaking cup experiments and a fuzzy balance controller are proposed. Through a single-axis mechanical balance system imitating rotation of the human's wrist with a camera to observe the sloshing amplitude in the cup, the dexterous hand-eye coordination skills of humans to balance the sloshing liquid can be reproduced.
First of all, the sloshing dynamic model is established by applying the fluid field equations to understand the variation of liquid surface caused by back and forth excitation and pitching excitation. Through a series of image processing procedures, the amplitude of liquid surface is obtained based on the image acquired by the camera. Then the prediction of sloshing liquid surface balance control strategy by analyzing periodic sloshing behavior of liquid surface can be developed. In order to mimic human’s thinking and reasoning mechanism, a fuzzy control approach is also presented. Finally, the proposed two control algorithms are applied to a single-axis mechanical balance system, which combines a single-axis robotic wrist and a camera, to rotate the cup in order to suppress the growing level of the liquid surface.
Two types of balancing experiment, the fixed position balancing experiment and the walking balancing experiment are conducted to examine the performance of those two proposed control schemes. For the fixed position balancing experiments, the suppressing speeds using the prediction of sloshing liquid surface method and the fuzzy control method compared with no balance control increase at least 32% and 104%, respectively. For the walking balancing experiments, the decreases of the highest peak amplitude for both presented control methods correspondingly reach at least 24% and 50%, compared with no balance control. In addition, the number reductions of amplitude over 5 mm with two different control approaches compared with no balance control apparently are more than 81% and 71%, respectively. Therefore, both presented balancing control schemes can successfully imitate the hand-eye coordination strategies of humans while walking to prevent the liquid in a cup from overflow. Experimental results also demonstrate that the balancing performance of the fuzzy control method is superior to that of the prediction of sloshing liquid surface method.
目次 Table of Contents
論文審定書 i
誌謝 ii
摘要 iii
圖次 ix
表次 xiv
第一章 緒論 1
1.1研究動機與目的 1
1.2研究方法與步驟 2
1.3文獻回顧 4
1.4論文架構 9
第二章 人行走時產生之擾動分析 10
2.1人拿水杯行走之行為模式 10
2.2受試者進行實驗 12
2.3數據分析 13
2.3.1離散型傅立葉轉換 14
2.3.2數據探討 17
2.3.3弦波函數不定積分 21
第三章 水杯受擾動液面晃動之力學模型 22
3.1前後擾動液面模擬 22
3.1.1 流體場方程式 23
3.1.2 模擬結果 28
3.2俯仰擾動液面模擬 33
3.2.1流體場方程式 34
3.2.2 模擬結果 37
3.3模擬結果探討 42
第四章 影像處理 44
4.1 See3CAM_80攝影機 44
4.2影像灰階 46
4.3影像縮小 48
4.4影像二值化 49
4.5 Sobel演算法邊緣偵測 51
4.6液面中央高度偵測 53
4.6.1計算液面中央高點座標 54
4.6.2像素座標位置轉換真實晃動高度 56
4.7影像處理流程 61
第五章 機械結構與控制方法 63
5.1機械結構設計 63
5.1.1馬達規格 63
5.1.2機械結構設計 65
5.2單軸機械平衡系統控制 70
5.3液面晃動預測法 73
5.3.1馬達轉角與液體晃動關係 73
5.3.2液面晃動時間與影像處理時間關係 82
5.3.3抑制晃動流程 88
5.4模糊控制法 90
5.4.1 模糊理論及控制 90
5.4.1.1模糊集合 91
5.4.1.2模糊推論 94
5.4.1.3模糊化及解模糊化 96
5.4.2 設計模糊控制器 98
第六章 實驗結果與分析 107
6.1定點平衡實驗 107
6.1.1硬體架設與實驗器材 107
6.1.2系統開發軟體與人機介面設計 108
6.1.3液面晃動預測法之定點實驗 110
6.1.4模糊控制法之定點實驗 113
6.2 行走平衡實驗 116
6.2.1硬體架設與實驗器材 116
6.2.2液面晃動預測法之行走實驗 118
6.2.3模糊控制法之行走實驗 123
6.3 分析實驗結果與討論 126
第七章 結論與未來規劃 132
7.1結論 132
7.2未來規劃 133
參考文獻 134
附錄 136
參考文獻 References
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[14] See3CAM_80攝影機介紹https://www.e-consystems.com/images/See3CAM /See3CAM_80/8MP-USB3-camera-board.jpg
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