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研究生:鄭伊峻
研究生(外文):Yi-Chun Cheng
論文名稱:應用應變計於重型車輛載重之自動量測
論文名稱(外文):Using Strain Gages for Automatic Measurement of Payload for Heavy Vehicles
指導教授:呂宗熙
指導教授(外文):Tzong-Shi Liu
學位類別:碩士
校院名稱:國立交通大學
系所名稱:機械工程系
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2002
畢業學年度:90
語文別:中文
論文頁數:89
中文關鍵詞:應變計重型車輛葉片彈簧自動量測
外文關鍵詞:Strain GagesHeavy VehiclesLeaf SpringAutomatic Measurement
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近年來重型車輛的肇事率逐漸上升,除了駕駛本身的因素外,就是由於超載所導致煞車不及和不易操控。因此本研究旨在研發安裝於車輛上能夠自動量測載重的裝置,以便於駕駛和執法人員隨時檢視載重。為了達成容易安裝、準確度高以及低成本的考量,本研究使用應變計黏貼於每一組懸吊的葉片彈簧,根據葉片彈簧受力變形造成的應變計輸出電壓,換算出懸吊荷重和全車荷重。由實車測試發現利用四組懸吊受力相加,計算重量的方式,其誤差不小,因此本研究利用類神經網路建立模型,以模擬實驗時非線性的影響,並且減少荷重讀值的誤差。本研究利用實車測試的數據驗證了所建立模型的準確性。

Accidents caused by heavy vehicles have been increasing these years. It is mainly due to the fact that vehicle overloading results in steering difficulty and braking distance. Therefore, this work aims to develop the automatic payload measurement for heavy vehicles, so as to allow drivers and policemen monitor vehicle payload on board. For the ease of installation, high accuracy, and lower cost, this work proposes to stick strain gages on each leaf spring in vehicle suspensions. From measured voltage output of strain gages in each suspension, the vehicle payload is calculated. To reduce payload reading error, this work develops neural network models to account for nonlinear effects. Finally, this work verifies model accuracy based on experimental data.

第一章 緒論……………………………………………………….1
1.1 研究動機……………………………………………………….1
1.2 文獻回顧………………………………………………….2
第二章 力感測器性能測試……………………………………….3
2.1 相關電路……………………………………………………….4
2.1.1 電壓放大電路……………………………………………….4
2.1.2 低通濾波器………………………………………………..10
2.2 靜態特性……………………………………………………..21
2.3 動態特性……………………………………………………..24
第三章 葉片彈簧及應變計……………………………………..30
3.1 葉片彈簧介紹………………………………………………..30
3.2 應變計………………………………………………………..37
3.3 葉片彈簧實驗………………………………………………..42
第四章 實車測試及相關電路…………………………………….49
4.1 相關電路…………………………………………………….49
4.1.1 惠斯頓電橋實作……………………………………………49
4.1.2 歸零電路……………………………………………………50
4.1.3 穩壓電路……………………………………………………51
4.2 實車測試…………………………………………………….54
4.2.1 左側部分……………………………………………………61
4.2.2 右側部分……………………………………………………63
4.2.3 前側部分……………………………………………………65
4.2.4 後側部分……………………………………………………67
4.2.5 中間部分……………………………………………………69
4.2.6 角落部分……………………………………………………71
4.3 實驗結果分析……………………………………………….73
第五章 類神經網路模型………………………………………….79
第六章 結論與未來方向………………………………………….89

Golovko, V., Savitsky, Y., and Maniakov, N., “Modeling Nonlinear Dynamic using Multilayer Neural Networks” Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, International Workshop, pp.197-202, Jul. 2001.
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Nishitani Katsuo, “Electromagnetic-Type Load Weighing Apparatus”, United States Patent 5243146, 1993.
Petrovic’, I., Baotic’, M., and Peric’, N., “Model Structure Selection for Nonlinear System Identification Using Feedforward Neural Networks”, Neural Networks, Proceedings of IEEE-INNS-ENNS International Joint Conf., Vol. 1, pp.53-57, 2000.
Principe, Jose’ C., Euliano, Neil R., and Lefebvre Curt W., “Neural and Adaptive Systems: Fundamentals through Simulations”, John Wiley & Sons, New York, 2000.
Randall, W. A., and Tagliarini, G. A., “Using Feed Forward Neural Networks to Model the Effect of Precipitation on the Water Levels of the Northeast Cape Fear River”, Southeast Conf., Proceedings IEEE, pp.338-342, 2002.
SAE Handbook Supplement, “Manual on Design and Application of Leaf Springs”, Society of Automotive Engineers, 1962.
Shimizu, Shinichiro, Aoshima, Hideyuki, and Su, Laiping, all of Shizuoka, “Load Deflecting Degree Computing Apparatus and Carrying Weight Computing Apparatus for Vehicle”, United States Patent 6069324, 2000.
Zhang, M., Xu, S., and Fulcher, J., “Neuron Adaptive Higher Order Neural Network Models for Automated Financial Data Modeling”, Neural Networks, IEEE Transactions on, Vol. 13, pp.188-204, Jan. 2002.
何中庸編譯,濾波器分析與設計,全華科技圖書公司,台北,民國八十八年。
楊善國編著,感測與量度工程,全華科技圖書公司,台北,民國九十年。
盧明智,盧鵬任編著,感測器應用與線路分析,全華科技圖書公司,台北,民國八十五年。
羅華強編著,類神經網路─MATLAB的應用,清蔚科技公司,新竹,民國九十年。
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