研究生: |
黃立彬 Li-Bin Huang |
---|---|
論文名稱: |
馬達運轉頻譜監測系統之研製 The Development of a Motor Operation Spectrum Monitoring System |
指導教授: |
張宏展
Hong-Chan Chang |
口試委員: |
吳瑞南
Ruay-Nan Wu 郭政謙 Cheng-Chien Kuo 謝宗煌 Tsung–Huang Hsieh |
學位類別: |
碩士 Master |
系所名稱: |
電資學院 - 電機工程系 Department of Electrical Engineering |
論文出版年: | 2014 |
畢業學年度: | 102 |
語文別: | 中文 |
論文頁數: | 72 |
中文關鍵詞: | 電氣檢測法 、振動檢測法 、馬達狀態監視 、快速傅立葉轉換 、無限脈衝濾波器 |
外文關鍵詞: | Electrical signal analysis, Vibraion signal analysis, Motor condition monitoring system, Fast Fourier Transform, Infinite impulse response filter |
相關次數: | 點閱:288 下載:16 |
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隨著工業自動化技術的蓬勃發展,馬達在工業自動化中扮演重要核心的角色,且已廣泛地應用於工業及電力等各產業之中,馬達設備能否正常健康運轉將直接影響各工廠的運作,一旦發生無預警故障事故,將造成工廠運作停擺造成嚴重的經濟損失,甚至對操作人員安全造成危害。傳統馬達設備的維護方式採用拆卸式的定期保養維護,不但非常耗費人力與時間且無法即時偵測馬達的故障前兆。因此,若能即時掌握馬達運轉的狀況和健康程度,於馬達發生嚴重故障而停止運轉前,提早預警,則可有效提升設備運作的可靠度。本研究旨在研製一套低成本之手持在線式馬達即時資料擷取裝置,以三相感應馬達為標的,並基於先進Cortex-M4核心之微控制器,利用微控制器內建之高速類比數位轉換器量測三相感應馬達的輸入電壓、電流及振動量;並使用數位訊號處理技術,先以無限脈衝濾波器對擷取訊號進行數位濾波,再以快速離散傅立葉轉換技術,進行電氣訊號與振動訊號之頻譜分析,並將分析結果顯示於小型觸控螢幕,讓使用者可即時得到分析結果,進而了解馬達目前的健康狀態。本研究已成功製作原型機並經實地現場量測驗證,分析結果與高階資料擷取卡相較,可得到相似的馬達故障頻譜特徵,其特徵振幅相比誤差率都不超過10%,成功驗證本系統。
As automated industrial technologies have flourished, motors have played a central role in the industrial automation process of various industrial domains such as the power industry. Regular motor equipment operation directly influences the operation of various factories; however, unexpected motor malfunction causes factory operations to cease, which results in severe financial losses and operator safety hazards. Traditional motor equipment is maintained by periodic maintenance through motor detachment, which is labor intensive and time consuming. Moreover, signs of motor malfunction cannot be immediately detected. Thus, understanding motor operation and functionality status in real-time can serve as advanced warnings before motor breakdown occurs, thereby effectively enhancing operating reliability.
In this study, a set of economical handheld online real-time motor data-acquisition devices was developed by using three-phase induction motors; subsequently, the advanced Cortex-M4 microcontroller and its built-in high speed analog-to-digital converter were used to measure the input voltage, current, and vibration of the three-phase induction motor. Digital signal processing technology was adopted, in which acquired signals were digitally filtered through the infinite impulse filter and spectral analysis was conducted on the electrical and vibrational signals through fast Fourier transform. The analytic results were then displayed in real time on a small touch-screen monitor to instantly provide users with results and the current status of the motor.
Overall, a prototype was devised and verified through onsite measurements. Comparing the results to high-end data acquisition modules showed similar motor malfunction spectral characteristics, the amplitude errors of which were less than 10%. Thus, the system developed in this study was successfully verified.
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