References
- Cohen, L., 1995, “Time-Frequency Analysis,” Prentice Hall
- Eren, L., Teotrakool, K. and Devaney, M., 2007, “Bearing Fault Detection via Wavelet Packet Decomposition with Spectral Post Processing,” Instrumentation and Measurement Technology Conference - IMTC 2007,Warsaw, Poland https://doi.org/10.1109/IMTC.2007.379444
- Gertler, J. J., 1998, Fault Detection and Diagnosis in Engineering Systems, Marcel Dekker, Inc, America
- Norton, M. P. and Karczub, D. G., 2003, “Fundamentals of Noise and Vibration Analysis for Engineers,” Cambridge University Press, United Kingdom
- Vetterli, M. and Kovacevic, J., 1995, “Wavelet and Subband Coding,” Prentice Hall
- Akansu, A. N. and Haddad, R. A., 1992, “Multiresolution Signal Decomposition,” Academic Press
- Chung, B.-H. and Shin, D.-C., 2004, “A Development of the Algorithm to Detect the Fault of the Induction Motor Using Motor Current Signature Analysis,” Transactions of the Korean Society for Noise and Vibration Engineering, Vol. 14, No. 8, pp. 675~683 https://doi.org/10.5050/KSNVN.2004.14.8.675
- McInerny, S. A. and Dai, Y., 2003, “Basic Vibration Signal Processing for Bearing Fault Detection,” IEEE transaction on Education, Vol. 46, pp. 149~156 https://doi.org/10.1109/TE.2002.808234
- Isermann, R., 2006, “Fault Diagnosis System : An Introduction from Fault Detection to Fault Tolerance,” Springer, Germany
- Isermann, R., 1994, “Integration of Fault Detection and Diagnosis Methods,” In Proceeding of IFAC Symposium on fault detection, Supervision and Safety for Technical Processes, Espoo, Finland, pp. 587~609
- Isermann, R., 1997, “Supervision, Fault Detection and Diagnosis Methods- an Introduction,” Control Engineering Practice – CEP. Vol. 5, No. 5, pp. 639~652 https://doi.org/10.1016/S0967-0661(97)00046-4
- Chung, B.-H. and Shin, D.-C., 2002, “A Study on Detection of Broken Rotor Bars in Induction Motors Using Current Signature Analysis,” Transactions of the Korean Society for Noise and Vibration Engineering, Vol. 12, No. 4, pp. 287~293 https://doi.org/10.5050/KSNVN.2002.12.4.287
- Widodo, A. and Yang, B.-S., 2006, “Intelligent Fault Diagnosis of Induction Motor Using Support Vector Machines,” Proceedings of the KSNVE Annual Autumn Conference 2006, KSNVE06A-11-03
- Tran, V. T., Yang, B.-S. and Oh, M.-S., 2006, “Fault Diagnosis of Induction Motors Using Decision Trees,” Proceedings of the KSNVE Annual Autumn Conference 2006, KSNVE06A-11-04
- Calis, H., 1998, “Current-based Detection of Mechanical Faults in Induction Motors,” PhD thesis, University of Sussex
- Chow, T. W. S., 1996, “Condition Monitoring of Electrical Machines Using Third-order Spectrum Analysis,” IEEE IAS Annual Meeting. Vol. 1, pp. 679~686 https://doi.org/10.1109/IAS.1996.557109
- Schoen, R., 1994, “On-line Current-based Condition Monitoring of Three-phase Induction Machines,” PhD thesis at Georgia Institute of Technology
- Boyle, C., et al, 1994, “Online Current Monitoring to Detect Misalignment and Dynamic Eccentricity in Three-phase Induction Motor Drives,” In: Proceedings of the 29th Universities Power Engineering Conference 1, Galway, Ireland, pp. 5~8
- Cameron, J. R., 1987, “Vibration and Current Monitoring for Online Detection of Airgap Eccentricity in Induction Motors. PhD Thesis at Robert Gordon Institute of Technology
- Arkan, M., Calis, A. H. and Tagluk, A. M. E, 2005, 'Bearing and Misalignment Fault Detection in Induction Motors by Using the Space Vector Angular Fluctuation Signal,' Electrical Engineering. Vol. 87, pp. 197~206 https://doi.org/10.1007/s00202-004-0242-6
- McInerny, S. A. and Dai, Y., 2003, “Basic Vibration Signal Processing for Bearing Fault Detection,” IEEE Transaction on Education, Vol. 46, No. 1, pp. 149~156 https://doi.org/10.1109/TE.2002.808234
- Yang, B.-S., Kim, K. J. and Han, T., 2004, “Fault Diagnosis of Induction Motors Using Data Fusion of Vibration and Current Signals,” Transactions of the Korean Society for Noise and Vibration Engineering, Vol. 14, No. 11, pp. 1091~1100 https://doi.org/10.5050/KSNVN.2004.14.11.1091
- Thomson, W. T. and Fenger, M., 2001, “Current Signature Analysis to Detect Induction Motor Faults,” IEEE Industry Applications Magazine, pp. 26~31 https://doi.org/10.1109/2943.930988
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