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研究生:路敬平
研究生(外文):LU, JING-PING
論文名稱:基於渦電流微位移感測器與類神經網絡之幾何誤差測量系統
論文名稱(外文):Geometric Error Measurement System based on Eddy Current Displacement Sensor and Artificial Neural Network
指導教授:黃榮堂黃榮堂引用關係
指導教授(外文):HUANG, JUNG-TANG
口試委員:黃榮堂胡毓忠李尉彰
口試委員(外文):HUANG, JUNG-TANGHU, YUH-CHUNGLI, WEI-CHANG
口試日期:2022-05-19
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:機械工程系機電整合碩士班
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:2022
畢業學年度:110
語文別:中文
論文頁數:93
中文關鍵詞:工具機幾何誤差渦電流微位移感測器類神經網路
外文關鍵詞:Machine ToolGeometric ErrorEddy Current Displacement SensorArtificial Neural Network
ORCID或ResearchGate:orcid.org/0000-0002-7964-5076
相關次數:
  • 被引用被引用:1
  • 點閱點閱:50
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  • 收藏至我的研究室書目清單書目收藏:0
幾何誤差是工具機各類誤差之基礎,各項幾何誤差組成工具機整體之體積誤差,幾何誤差中之角度誤差會因阿貝原理而放大,為影響工具機體積誤差之主要因素。幾何誤差之量測技術普遍基於鐳射系統,但鐳射系統易受到環境影響,無法安裝在工具機上作為長期監控手段。故本研究使用實驗室開發之納米級渦電流微位移感測器,利用壓電納米位移校正平臺校正感測器,將感測器安裝於工具機床台下量測床台與滑軌間電感值。根據三軸工具機體積誤差公式,分析角度誤差、定位誤差、阿貝偏位之相互關係。用鐳射干涉儀量測x軸定位誤差、俯仰度誤差、偏擺度誤差。使用反向傳播類神經網路,將俯仰度誤差、偏擺度誤差作為輸入,定位誤差作為輸出,驗證角度誤差與定位誤差之關係。再分組輸入不同位置的感測器資料,分別輸出定位誤差與三種角度誤差,將鐳射干涉儀資料作為驗證,反復調整隱藏層層數和神經元數等參數,並測試各類演算法的收斂效果,確定最佳的模型和參數。最終實現用渦電流微位移感測器代替鐳射干涉儀測量工具機幾何誤差之目的。
Geometric error is the basis of all kinds of errors of machine tool, each geometric error constitutes the volume error of machine tool as a whole, and the Angular error of geometric error will be amplified by Abbe principle, which is the main factor affecting the volume error of machine tool. The measurement technology of geometric error is generally based on laser system, but the laser system is susceptible to environmental influence and cannot be installed on the machine tool as a long-term monitoring method. Therefore, the nano-scale eddy current micro-displacement sensor developed in the laboratory was used in this research, and the piezoelectric nano-displacement correction platform was used to correct the sensor. The sensor was installed on the platform to measure the inductance between the stage and the guideway. According to the formula of volume error of three-axis machine tool, the relationship between Angular error and position error abbe deviation is analyzed. X axis positioning error , pitch error , yaw error was measured by laser interferometer. The relationship between Angular error and positioning error is verified by using back propagation artificial neural network with pitch error and yaw error as input and positioning error as output. Then group and input sensor data of different positions, output positioning error and three kinds of Angular error respectively, take laser interferometer data as verification, repeatedly adjust the hidden layer number and neuron number and other parameters, and test the convergence effect of various algorithms to determine the best model and parameters. Finally, eddy current micro-displacement sensor is used to replace laser interferometer to measure the geometric error of machine tool.
摘要 i
ABSTRACT ii
誌謝 iv
目錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究動機與目的 1
1.2 文獻探討 4
第二章 渦電流微位移感測器 9
2.1 量測原理 9
2.2 系統架構 12
2.3 開發環境 16
2.4 壓電納米位移校正平臺 17
2.5 性能測試 18
第三章 角度誤差 25
3.1 幾何誤差定義 25
3.2 阿貝偏位 26
3.3 體積誤差影響因素 27
3.4 角度誤差量測方法 28
第四章 類神經網路 31
4.1 基本概念 31
4.2 反向傳播演算法 32
4.2.1 激活函數 35
4.2.2 損失函數 36
4.3 最佳化方法 37
4.3.1 梯度下降法 37
4.3.2 牛頓法 38
4.3.3 Levenberg Marquardt演算法 40
4.3.4 共軛梯度法 41
第五章 實驗與分析 43
5.1 設備規格 43
5.2 量測資料集 44
5.2.1 定位誤差 46
5.2.2 俯仰度誤差 49
5.2.3 偏擺度誤差 52
5.3 資料預處理 55
5.3.1 滾動度誤差 58
5.3.2 俯仰度誤差 59
5.3.3 偏擺度誤差 60
5.4 類神經網路訓練結果 63
5.4.1 實驗一 65
5.4.2 實驗二 69
5.4.3 實驗三 83
第六章 結論與未來展望 88
6.1 結論 88
6.2 未來展望 89
參考文獻 90


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