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.

[1] 經濟部能源局，「產業節能總動員，政府全面推動馬達革新計畫」，2008年。
[2] 楊國安，旋轉機械故障診斷實用技術，中國石化出版社，2012年。
[3] 台灣電力股份有限公司，「PD線上長期監測系統之技術研討」，2012年。
[4] 古峰昌，「多功能局部放電分析儀之研製及其應用」，博士論文，台灣科技大學電機工程學系，2013年。
[5] Sridhar. S,K.UmaRao,　“Detection of simultaneous unbalanced under-voltage and broken rotor fault in induction motor,” Condition Assessment Techniques in Electrical Systems (CATCON),　 2013 IEEE 1st International Conference, pp. 48-53, 2013.
[6] Santanu Das,P. Purkait,S. Chakravorti,　“Characterization of short circuit faults and incipient insulation degradation between stator winding turns of induction motor,” Condition Assessment Techniques in Electrical Systems (CATCON), 2013 IEEE 1st International Conference, pp. 54-59, 2013.
[7] Joksimovic, G.M. and Penman, J., “The Detection of Inter-Turn Short Circuits in the Stator Windings of Operating Motors,” IEEE Transactions on Industrial Electronics, Vol. 47, No. 5, pp. 1078-1084, 2000.
[8] Tsypkin, M., “Induction motor condition monitoring: Vibration analysis technique a twice line frequency component as a diagnostic tool,” IEEE International Electric Machines & Drives Conference (IEMDC), pp. 117-124, 2013.
[9] T. Ishikawa,R. Ishigame, M. Matsunami, and N. Kurita,　“Analysis and failure diagnosis of squirrel-cage induction motor with broken rotor,” Electrical Machines and Systems (ICEMS), pp. 1-5, 2012.
[10] Sridhar, S., Rao, K.U.,　“Detection of simultaneous unbalanced under-voltage and broken rotor fault in induction motor,” Condition Assessment Techniques in Electrical Systems (CATCON), pp.48- 53, 2013.
[11] Martin Riera-Guasp, Man’es Fern’andez Cabanas, Jose A. Antonino-Daviu, Manuel Pineda-S’anchez, and Carlos H. Rojas Garc’ıa, “Influence of nonconsecutive bar breakages in motor current signature analysis for the diagnosis of rotor faults in induction motors,” IEEE Transaction on Energy Conversion, Vol. 25, pp. 80-89, 2010.
[12] Schoen, R.R., Habetler, T.G., Kamran, F. and Bartfield, R.G., “Motor bearing damage detection using stator current monitoring,” IEEE Transactions on Industry Applications, Vol. 31, No. 6, pp. 1274-1279, 1995.
[13] Faiz, J., Ebrahimi, B.M., Akin, B., Toliyat, H.A.,　“Finite element transient analysis of induction motors under mixed eccentricity fault,” Magnetics, IEEE Transactions, pp. 66-74, 2008.
[14] Jover Rodriguez, Belahcen, A., Arkkio, A., Laiho, A., Antonino-Daviu, J.A., “Air-gap force distribution and vibration pattern of Induction motors under dynamic eccentricity,” Electrical Engineering, Vol. 90, No. 3, pp. 209-218, 2008.
[15] 李宜達，數位信號處理-從設計到實現，全華科技圖書股份有限公司，2005年。
[16] Yeary, M.B. , Griswold, N.C.,　“Adaptive IIR filter design for single sensor applications,” Transactions on Instrumentation and Measurement, Vol.51, no.2, 2002.
[17] Der-Feng Huang,　“A computational form of the least square error frequency sampling method for the linear phase FIR filter design,” Image and Signal Processing, 2009. CISP '09. 2nd International Congress, pp.1-4, 2009.
[18] 王鵬華、曾建誠、丁建均、陳常侃，離散時間訊號處理，全華科技圖書股份有限公司，2003年。
[19] IMI SENSORS A PCB PIEZOTRONICS DIV.,　“Precision Triaxial Industrial ICPR Accelerometer Installation and Operating Manual,” June 2013,
http://www.directindustry.com/prod/imi-sensors/triaxial-accelerometers-111589-1115647.html
[20] STMicroelectronics,“STM32F4x7-Datasheet,“June 2013,
http://www.st.com/web/catalog/mmc/FM141/SC1169/SS1577/LN11
[21] SEGGER Microcontroller,“EMWIN Graphic Library with Graphical User Interface, ”June 2013,
http://www.segger.com/emwin.html
[22] National Instrument, “NI PMA-1115 Portable PXI LCD Monitor and Keyboard Accessory,”June 2013,
http://sine.ni.com/nips/cds/view/p/lang/en/nid/204583.
[23] 陳立元、范逸之、廖錦棋，Visual Basic2010與自動化系統監控-RS232串列通訊，松崗電腦圖書資料股份有限公司，2011年。
[24] Betta, G. , Liguori, C. , Paolillo, A. , Pietrosanto, A.,“A DSP-based FFT-analyzer for the fault diagnosis,”Instrumentation and Measurement Technology Conference, IMTC 2001.Proceedings of the 18th IEEE, Vol.1 pp.572- 577, 2001.