臺灣博碩士論文加值系統

因石油的日漸枯竭及節能減碳的實際需要，以馬達來推進取代傳統引擎，已漸成為未來趨勢。而感應馬達因具有構造簡單、反應快速、推進力量大等優勢較常被使用，並促使線上即時馬達故障監控亦受到重視。然而，故障監控的準確性與即時性是此項工作中較為困難的，且大量統計顯示馬達故障主要發生於定子、軸承與轉子相關處，這些故障又肇因於電力與機械兩部分，其中又有80%的機械相關故障會導致氣隙偏心現象，而降低馬達功率因數與發生振動，進而損耗電能並擴大故障範圍，情況嚴重時，甚至衍生定子與轉子磨擦問題。若能預知感應馬達將發生故障之時間，進而可先期排訂保養或更換即將故障零組件之時程，以避免因馬達的突然故障而造成人員受傷或營運上的損失。
本文應用Matlab/Simulink來模擬比較感應馬達於正常運轉、配置不均與轉子偏心情況之電流訊號差異，並模擬感應馬達氣隙偏心的故障特徵驗證，再與相關文獻數據比對，最後藉由模糊運算實現不需使用傳統方法，先轉到頻域，再用神經元演算法分析故障狀況，而能於時域下快速且準確比對出感應馬達的偏心故障訊息，並予以判定嚴重等級。

Owing to the gradual depletion of oil and a concern for environmental protection, motors have become the drive system of the future instead of the combustion engine. Among various types of motors, induction motors are often used due to their simple structure, fast reaction, and powerful propulsion force. Thus, the safe operation of motor vehicles is a major concern with the trends in the online fault monitor. However, the accuracy of online monitoring is the most difficult task. Based on statistics, the motor failures caused by electric and mechanical parts may occur mainly in stator, bearing and rotor. Among mechanical faults, 80% of relevant troubles may cause the phenomenon of air-gap eccentricity, leading to the power factor decreasing, motor vibrations, power losses and enlargement of the fault area. Particularly, it may result in the rotor and stator sides to chaft each other in a serious situation. If one can detect motor faults in advance, maintenance schedule or parts replacement can be properly arranged to reduce the risk of suddenly shut down in motor operation.
This thesis simulates the differences of the characteristics of electric current signals for a three-phase induction motor under normal condition, uneven dispose fault and air-gap eccentric fault using Matlab/Simulink. To verify the feasibility of the models developed in the MATLAB/Simulink environment, the simulated fault signals are compared with the results obtained by other research. Finally, this thesis shows that the air-gap eccentricity degree can rapidly and reliably be diagnosed without using the traditional method to transform the fault signals into the frequency domain by analyzing them with a neural algorithm.

摘 要 i
誌 謝 iii
目 錄 iv
頁次 iv
表目錄 vi
圖目錄 vii
符號說明 ix
第一章 序 論 1
1.1前言 1
1.2文獻回顧與研究動機 4
1.3研究方法 6
1.4本文所提方法與論文貢獻 8
1.5論文研究架構 9
第二章 感應馬達氣隙偏心偵測方法之探討 11
2.1 馬達故障偵測之參考依據 11
2.2 故障馬達之電流特徵處理 12
2.3 馬達不平衡負載 15
2.4 感應馬達氣隙偏心 16
2.5 模糊推論演算法 19
2.6 本章小結 20
第三章 三相感應馬達Matlab/Simulink偏心故障模型之實現 23
3.1 三相感應馬達Matlab/Simulink之實現 23
3.2 馬達不平衡負載之Matlab/Simulink實現 30
3.3 馬達氣隙偏心故障之Matlab/Simulink實現 31
3.3.1 靜態偏心運轉之模擬 32
3.3.2 動態偏心運轉之模擬 33
3.3.3 混合偏心運轉之模擬 34
3.4本章小結 36
第四章 模擬結果 37
4.1 馬達不平衡負載分析 37
4.2 馬達氣隙偏心分析 40
4.2.1靜態偏心運轉之模擬分析 41
4.2.2動態偏心運轉之模擬分析 44
4.3 運用模糊理論判定馬達偏心故障 47
4.3.1 三相定子繞組電流均方根分析 47
4.3.2定子繞組電流均方根值之訊號處理 51
4.3.3 模糊推論辨識模擬結果 55
4.4 本章小結 58
第五章 結論與未來展望 59
5.1結論 59
5.2未來展望 59
參考文獻 61
簡 歷 65

[1] H. Bae, Y.-T. Kim, S.-H. Lee, S. Kim, and M. H. Lee, “Fault diagnostic of induction motors for equipment reliability and health maintenance based upon Fourier and wavelet analysis, Artificial Life and Robotics, vol. 9, no. 3, July 2005, pp.112-116.
[2] A. C. Smith and D. G. Dorrell, “Calculation and measurements of unbalance magnetic pull in cage induction motors with eccentric rotors, Part 1: Analytical model, IEE Proceedings on Electric Power Applications, vol. 143, no. 3, May 1996, pp. 193-201.
[3] S. P?yh?nen, M. Negrea, P. Jover, A. Arkkio, and H. Hy?tyniemi, “Numerical magnetic field analysis and signal processing for fault diagnostic of electrical machines, International Journal for Computer and Mathematics in Electrical and Electronic Engineering, vol. 22, no. 4, October 2003, pp. 969-981.
[4] J. R. Cameron, W. T. Thomson, and A. B. Dow, “Vibration and current monitoring for detecting airgap eccentricity in large induction motors, IEE Proceedings on Electric Power Applications, vol. 133, no. 3, May 1986, pp. 155-163.
[5] Pedro Vicente Jover Rodr?guez, Anouar Belahcen, Antero Arkkio, Antti Laiho, and Jos? A. Antonino-Daviu, “Air-gap force distribution and vibration pattern of induction motors under dynamic eccentricity, Electrical Engineering, vol. 90, no. 3, February 2008, pp. 209-218.
[6] J. Faiz, B. M. Ebrahimi, and H. A. Toliyat, “Effect of magnetic saturation on static and mixed eccentricity fault diagnosis in induction motors, IEEE Transactions on Magnetics, vol. 45, no. 8, August 2009, pp. 3137-3144.
[7] J. Faiz, B. M. Ebrahimi, B. Akin, and H. A. Toliyat, “Dynamic analysis of mixed eccentricity, IET Electric Power Applications, vol. 4, no. 1, April 2010, pp. 1-16.
[8] J. Faiz, B. M. Ebrahimi, B. Akin, and H. A. Toliyat, “Comprehensive eccentricity fault diagnosis in induction motors using finite element method, IEEE Transactions on Magnetics, vol. 45, no. 3, March 2009, pp. 1764-1767.
[9] J. F. Bangura, and N. A. Demerdash, “Comparison between characterization and diagnosis of broken bars/end-ring connectors and airgap eccentricities of induction motors in ASD’s using a coupled finite element-state space method, IEEE Transactions on Energy Conversion, vol. 15, no. 1, March 2000, pp. 48-56.
[10] J.-H. Jung, J.-J. Lee, and B.-H. Kwon, “Online diagnosis of induction motors using MCSA, IEEE Transactions on Industrial Electronics, vol. 53, no. 6, December 2006, pp. 1842-1852.
[11] W. T. Thomson, D. Rankin, and D. G. Dorrell, “On-line current monitoring to diagnose airgap eccentricity in large three-phase induction motors - industrial case histories verify the predictions, IEEE Transactions on Energy Conversion, vol. 14, no. 4, December 1999, pp. 1372-1378.
[12] W. T. Thomson and A. Barbour, “On-line current monitoring and application of a finite element method to predict the level of static airgap eccentricity in three-phase induction motors, IEEE Transactions on Energy Conversion, vol. 13, no. 4, December 1998, pp. 347-357.
[13] J. Faiz and M. Ojaghi, “Unified winding function approach for dynamic simulation of different kinds of eccentricity faults in cage induction machines, IET Electric Power Applications, vol. 3, no. 5, April 2009, pp. 461-470.
[14] J. F. Bangura and N. A. Demerdash, “Effects of broken bars/end-ring connectors and airgap eccentricities on ohmic and core losses of induction motors in ASD’s using a coupled finite element-state space method, IEEE Transactions on Energy Conversion, vol. 15, no. 1, March 2000, pp. 40-47.
[15] C.-H. Chang, “A fast method for determining electrical and mechanical qualities of induction motors using a PC-aided detector, IEEE Transactions on Instrumentation and Measurement, vol. 43, no. 4, August 1994, pp. 624-629.
[16] X. Huang, T. G. Habetler, R. G. Harley, and E. J. Wiedenbrug, “Using a surge tester to detect rotor eccentricity faults in induction motors, IEEE Transactions on Industry Applications, vol. 43, no. 5, September/October 2007, pp. 1183-1190.
[17] Pedro Vicente Jover Rodr?guez, and Antero Arkkio, “Detection of stator winding fault in induction motor using fuzzy logic, Applied Soft Computing, vol. 8, no. 2, March 2008, pp. 1112-1120.
[18] J. O. P. Pinto, B. K. Bose, and L. E. B. Silva, “A stator flux oriented vector-controlled induction motor drive with space vector synthesis by neural networks, IEEE Industry Applications Socity Annual Meeting, Rome, Italy, 2000, pp. 2614-2626.
[19] M’hamed Drif and A. J. Marques Cardoso, “Airgap-eccentricity fault diagnosis, in three-phase induction motors, by the complex apparent power signature analysis, IEEE Transactions on Industrial Electronics, vol. 55, no. 3, March 2008, pp. 1404-1410.
[20] W. T. Thomson and M. Fenger, “Current signature analysis to detect induction motor faults, IEEE Industry Applications Magazine, vol. 7, no. 4, July/August 2001, pp. 26-34.
[21] 黃劍鋒、林瑞光，“無刷直流電機可靠性及其故障模式分析, 電機控制學報，第4卷，第4期，2000，pp. 198-201。
[22] 楊玉崗、周立、辛克鋒，“三相非同步電動機動態特性的模組仿真, 遼寧工程技術大學學報，第21卷，第6期，2002年12月，pp. 751-753。
[23] J. Faiz, B. M. Ebrahimi and M. B. B. Sharifian, “Finite element transient analysis of an on-load three-phase squirrel-cage induction motor with static eccentricity, Electromagnetics, vol. 27, no. 4, 2007, pp. 207-227.
[24] P. C. Krause, O. Wasynczuk, S. D. Sudhoff, Analysis of electric machinery and drive systems, 2nd Edition, McGraw-Hill Book Company, March 2002.
[25] 林益富，“馬達動力特性量測新技術, 佳準科技股份有限公司，第221期，2007年3月，pp. 76-79。
[26] 付家才、薑?，“小波變換技術在電機故障診斷上的應用, 黑龍江科技學院、電氣與資訊工程學院，哈爾濱，第16卷，第6期，2006年11月，pp. 349-356。
[27] M. Hajiaghajani, H. A. Toliyat, and I. M. S. Panahi, “Advanced fault diagnosis of a DC motor, IEEE Transactions on Energy Conversion, vol. 19, no. 1, March 2004, pp. 60-65.
[28] A. M. Knight and S. P. Bertani, “Mechanical fault detection in a medium-sized induction motor using stator current monitoring, IEEE Transactions on Energy Conversion, vol. 20, no. 4, December 2005, pp. 753-760.
[29] B. Ozpineci and L. M. Tolbert, “Simulink implementation of induction machine model – A modular approach, IEEE International Electric Machines and Drives Conference, vol. 1, February 2003, pp. 728-734.
[30] Fr?d?ric Champavier, “Condition monitoring of induction motors using vibration and electrical signature analysis, http://www1.cetim.fr/eemods09/pages/programme/073-Champavier-final.pdf, September 2009.
[31] Pedro Vicente Jover Rodr?guez, Jos? A. Antonino-Daviu, E. Mu?oz, A. Arkkio, “A simplified online technique for the detection of eccentricity in induction motors, International Conference on Electrical Machines, Paper no. 114, Crete Island, Greece, September, 2006.