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研究生:洪茂棋
研究生(外文):HONG, MAO-QI
論文名稱:開發智能控制模組及應用高斯模型於軸承健康診斷之研究
指導教授:鄭志鈞
口試委員:劉建聖蔡孟勳鄭志鈞林明宗
口試日期:2019-04-10
學位類別:碩士
校院名稱:國立中正大學
系所名稱:機械工程系研究所
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:2019
畢業學年度:107
語文別:中文
論文頁數:62
中文關鍵詞:智能控制模組感測器電路軸承診斷離散小波分解相對峰值總合比高斯模型
相關次數:
  • 被引用被引用:1
  • 點閱點閱:268
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:1
本論文的第一部分在於開發一套整合感測電路之智能控制模組,此模組能夠
於 1ms 內同步擷取 CNC 內部插補、伺服訊號與外部溫度以及振動訊號。為取得
正確且有用的資料,感測器的擷取電路設計必須非常謹慎,以避免機台的環境及
電力干擾。故在振動訊號的擷取採用主動濾波、電源隔離等方法隔絕大部份雜訊。
而在硬體的擴充性也是重點,故本硬體在電路設計上進行模組化,提供使用者自
由串接所需要的模組,目前共開發了:熱電偶、電阻式溫度計、A/D 轉換以及壓
電加速規,共四種擷取模組。除正常運作之外,為測試電路穩定性,本硬體依照
IEC 規範測試其電磁相容(EMC)程度,達到工業應用等級。為了讓此模組擁有智
能化相關功能,本論文在第二部分開發軸承診斷演算法進行健康值的監控。透過
量 測 到的 振動 訊號 ,經 過 相對 峰值 總合 比(Relative peak to sum ratio) 以 及
BayesShrink 方法取得離散小波分解(Discrete wavelet decomposition)的層數以及去
雜訊的閥值,提高特徵訊號的訊雜比(Signal-to-Noise ratio),再針對時域及頻域訊
號進行特徵萃取。透過將健康軸承的特徵迴歸成高斯模型後,以此模型為基準來
判斷目前的軸承運轉狀態是否正常。
目錄
表目錄
圖目錄
第一章 緒論
1-1前言
1-2研究動機與目的
1-3文獻回顧
1-3-1 工具機智能化設備
1-3-2 軸承診斷演算法
1-3-3 文獻回顧總結
第二章 感測器原理
2-1熱電偶
2-2電阻式溫度感測器
2-3微機電型加速規
2-4壓電型加速規
第三章 感測器擷取模組驗證
3-1熱電偶
3-2類比訊號
3-3壓電型加速規
3-4擷取卡規格比較
3-5干擾測試
3-6應用實例
第四章 軸承診斷演算法
4-1振動訊號前處理
4-1-1 小波分解
4-1-2 小波分解去雜訊
4-2特徵擷取
4-2-1 頻域特徵
4-2-2 主成分分析
4-3軸承狀態判斷
4-4演算法驗證
第五章 結論與未來展望
5-1研究結論
5-2未來研究方向
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