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2018 | 113 | 98-108
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Condition Monitoring of Rotating Machines: A Review

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An uninterrupted health monitoring of machine is essential in various applications where failure of machine leads to loss of quality control, productivity and safety against catastrophic failure. Condition monitoring of machine involves continuous assessment on the performance of rotating components i.e. bearings, gears and motors and anticipating the faults before it cause any adversity. Rotating machines are commonly used in the industry for different applications such as railways, pumps, conveyors, blowers, elevator, mining industry, etc. Condition monitoring of rotating machines has been an important task for technicians, engineers, and researchers mainly to enhance structural reliability in a real time. This paper presents an enlarged survey on the expansion and the recent approaches in the condition monitoring of rotating machines. In current scenario, condition monitoring has proved their ability for fault detection of incipient faults in mechanical machines and equipments. Several techniques such as vibration monitoring, acoustic emission monitoring, invasive monitoring, oil monitoring are available for determining the health of rotating machines but all these monitoring methods needs expensive transducers and sensors.
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  • Department of Mechanical Engineering, National Institute of Technical Teachers Training & Research, Chandigarh - 160019, India
  • Department of Electrical Engineering Engineering, National Institute of Technical Teachers Training & Research, Chandigarh - 160019, India
  • Department of Mechanical Engineering, National Institute of Technical Teachers Training & Research, Chandigarh - 160019, India
  • Department of Mechanical Engineering, National Institute of Technical Teachers Training & Research, Chandigarh - 160019, India
  • Department of Mechanical Engineering, National Institute of Technical Teachers Training & Research, Chandigarh - 160019, India
  • [1] Tarek Aroui, Yassine Koubaa, and Ahm Toumi, Magnetic Coupled Circuit Modelling of Induction manchies oriented to Diagnostics, Leonardo Journal of Sciences, issue 13, pp. 103- 121, Dec. 2008.
  • [2] Mohamed Boucherma, Kaikaa, and Khezzar, Park Model of squirrel cage Induction Machine including space harmonic effects, Journal of Electrical Engineering, pp. 193-199, 2006.
  • [3] Mark M. Hodowanec, William R.Finiey, Scott and W. Kreitzer, Motor field protection and recommended settings and monitoring, IEEE pp. 271-284, 2002.
  • [4] C.M. Riley, B.K. Lin, T.G. Habetler and G.B. Kliman, Stator Current Harmonics and their Causal Vibrations: A Preliminary Investigation of Sensorless Vibration Monitoring Applications, IEEE Trans. on Ind. Appl. vol. 35, no. 1, pp. 94-99, Jan./Feb. 1999.
  • [5] M.Y.Chow, Robert N Sharpe and James C Hung, On the Application and Design of Artificial Neural Networks for motor fault detection – Part I, IEEE Transactions on Industrial Electronics, Vol. 40, No 2, pp. 181- 188, April 1993.
  • [6] P.V. Goode, M.Y. Chow, Using a Neural/Fuzzy system to extract Heuristic knowledge of incipient faults in I.M: part IMethodology, IEEE transactions on industrial Electronics, Vol. 42, No. 2, 131-138, April 1995.
  • [7] J. F. Martins, V. Fernao Pires, and A. J. Pires, Unsupervised Neural-Network-Based Algorithm for an On-Line Diagnosis of Three- Phase Induction Motor Stator Fault, IEEE Transactions On Industrial Electronics, Vol. 54, NO. 1, February, pp. 259-264, 2007.
  • [8] Y. Han and Y. H. Song, CM techniques for electricalequipment: a literature survey, IEEE Power Engineering Review, vol. 22, pp. 59-59, 2002.
  • [9] D. Goyal, B.S. Pabla, Condition based maintenance of machine tools - A review, CIRP Journal of Manufacturing Science and Technology, vol. 10, pp. 24-35, 2015
  • [10] Vanraj, D. Goyal, A. Saini, S.S. Dhami and B.S. Pabla. 2016, April. Intelligent predictive maintenance of dynamic systems using condition monitoring and signal processing techniques - A review. In Advances in Computing, Communication, & Automation (ICACCA) (Spring), International Conference on, pp. 1-6, IEEE, 2016.
  • [11] O. Duque-Perez, D. Morinigo-Sotelo, and M. Perez- Alonso, Diagnosisof induction motors fed by supplies with high harmonic content usingmotor current signature analysis, International Conference on Power Engineering, Energy and Electrical Drives, pp. 1- 6, 2011.
  • [12] W. T. Thomson and M. Fenger, Case histories of current signature analysis to detect faults in induction motor drives, IEEE International Electric Machines and Drives Conference, vol. 3, pp. 1459-1465, 2003.
  • [13] D. Goyal, B.S. Pabla, S.S. Dhami, K.C. Lachhwani, Optimization of condition-based maintenance using soft computing, Neural Computing and Applications, vol. 28(1), pp. 829-844, 2017.
  • [14] R. R. Schoen, T. G. Habetler, F. Kamran, and R. G. Bartfield, Motor bearing damage detection using stator current monitoring, IEEE Transactions on Industry Applications, vol. 31, pp. 1274-1279, 1995.
  • [15] D. Goyal, Vanraj, B.S. Pabla, S.S. Dhami, Condition monitoring parameters for fault diagnosis of fixed axis gearbox: a review, Archives of Computational Methods in Engineering, vol. 23(4), pp. 543-556, 2016.
  • [16] Y. Han, Y.H. Song. CM techniques for electrical equipment—A literature survey. IEEE Trans. Power Deliv. Vol. 18, pp. 4-13, 2003.
  • [17] J. L. H. Silva and A. J. M. Cardoso, "Bearing failures diagnosis in three phase induction motors by extended Park's vector approach, 31st Annual Conference of IEEE Industrial Electronics Society, pp. 6, 2005.
  • [18] J. R. Stack, T. G. Habetler, and R. G. Harley, Fault classification andfault signature production for rolling element bearings in electric machines, IEEE Transactions on Industry Applications, vol. 40, pp.735- 739, 2004.
  • [19] C. Bianchini, F. Immovilli, M. Cocconcelli, R. Rubini, and A. Bellini, Fault detection of linear bearings in brushless ac linear motors byvibration analysis, IEEE Transactions on Industrial Electronics, vol.5 8, pp. 1684- 1694, 2011.
  • [20] M. E. H. Benbouzid, A review of induction motors signature analysisas a medium for faults detection, Proceedings of the 24th Annual Conference of the IEEE Industrial Electronics Society, vol. 4, pp. 1950-1955, 1998.
  • [21] M. Pineda-Sanchez, R. Puche-Panadero, M. Riera- Guasp, A. Sapena-Bano, J. Roger-Folch, and J. Perez- Cruz, Motor CM of induction motor with programmable logic controller and industrialnetwork. Proceedings of the 2011-14th European Conference on Power Electronics and Application, pp. 1-10, 2011.
  • [22] D. Goyal, B.S. Pabla, The vibration monitoring methods and signal processing techniques for structural health monitoring: a review, Archives of Computational Methods in Engineering, vol. 23, pp. 585-594, 2016.
  • [23] D. Goyal, B.S. Pabla, Development of non-contact structural health monitoring system for machine tools, Journal of Applied Research and Technology, vol. 14, pp. 245-258, 2016.
  • [24] S. Kumar, D. Goyal, R.K. Dang, S.S. Dhami, and B.S. Pabla. Condition based maintenance of bearings and gears for fault detection–A review. Materials Today: Proceedings, vol. 5(2), pp. 6128-6137, 2018.
  • [25] S. Kumar, D. Goyal, S.S. Dhami. Statistical and frequency analysis of acoustic signals for condition monitoring of ball bearing. Materials Today: Proceedings, vol. 5(2), pp. 5186-5194, 2018.
  • [26] A.K.Verma, S. Sarangi, and M.H. Kolekar. Misalignment fault detection in induction motor using rotor shaft vibration and stator current signature analysis. International Journal of Mechatronics and Manufacturing Systems, vol. 6(5-6), pp. 422-436, 2013.
  • [27] R. Shnibha, A. Albarbar, A. Abouhnik and G. Ibrahim. A more reliable method for monitoring the condition of three-phase induction motors based on their vibrations. ISRN Mechanical Engineering, 2012.
  • [28] Sudhakar, S. AdiNarayana and M. AnilPrakash. Condition Monitoring of a 3-Ø Induction Motor by Vibration Spectrum anaylsis using Fft Analyser-A Case Study. Materials Today: Proceedings, vol. 4(2), pp.1099-1105, 2017.
  • [29] Ruiz-Gonzalez, F. Vargas-Merino, Application of Slope PWM Strategies to Reduce Acoustic Noise Radiated by Inverter-Fed Induction Motors, IEEE Trans. on Industrial Electronics, vol. 60(7), pp. 2555-2563, 2013.
  • [30] C.G. Nistor, Analysis of noise and heating for three-phase induction motor fed by inverter, Proc. of the 14th International Conference on Optimization of Electrical and Electronic Equipment, Braşov, Romania, pp. 389-396, 2014.
  • [31] S.A. Mortazavizadeh, A. Vahedi and A. Zohouri. Detection of Stator Winding Inter-turn Short Circuit In Induction Motor Using Vibration Specified Harmonic Amplitude, 2nd International Conference on Acoustics & Vibration (ISAV2012), Tehran, Iran, 26-27 Dec. 2012.
  • [32] V. V. Thomas, K. Vasudevan, and V. J. Kumar, Use of air-gap torque spectra for squirrel cage rotor fault identification, 4th IEEE Int. Conf. PIower Electron. Drive Syst. IEEE PEDS 2001 - Indones. Proc. (Cat. No.01TH8594), India, vol. 2, pp. 484– 488, 2001.
  • [33] M. da Silva, R. J. Povinelli, and N. A. Demerdash, Rotor bar fault monitoring method based on analysis of air-gap torques of induction motors, IEEE Transactions on Industrial Informatics, vol. 9(4), pp. 2274– 2283, 2013.
  • [34] A.G. Garcia-Ramirez, L.A. Morales-Hernandez, R.A. Osornio-Rios, A. Garcia-Perez and R.J. Romero-Troncoso. Thermographic technique as a complement for MCSA in induction motor fault detection. In Electrical Machines (ICEM), 2014 International Conference on (pp. 1940-1945). IEEE, 2014.
  • [35] S. Haus, H. Mikat and M. Nowara, S. T. Kandukuri, U. Klingauf, and M. Buderath: Fault Detection based on MCSA for a 400Hz Asynchronous Motor for Airborne Applications, International Journal of Prognostics and Health Management, 2013
  • [36] Y. Park, M. Jeong, S.B. Lee, J.A. Antonino-Daviu and M. Teska. Influence of blade pass frequency vibrations on MCSA-based rotor fault detection of induction motors. IEEE Transactions on Industry Applications, vol. 53(3), pp. 2049-2058, 2017.
  • [37] Singhal and M. A. Khandekar, Bearing fault detection in induction motor using motor current signature analysis, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 2, no. 7, pp. 3258–3264, 2013.
  • [38] Glowacz and Z. Glowacz, Diagnosis of the three-phase induction motor using thermal imaging, Infrared Phys. Technol. vol. 81, pp. 7–16, 2017.
  • [39] G. Garcia-Ramirez, L. A. Morales-Hernandez, R. A. Osornio-Rios, J. P. Benitez-Rangel, A. Garcia-Perez, and R. D. J. Romero-Troncoso, Fault detection in induction motors and the impact on the kinematic chain through thermographic analysis, Electr. Power Syst. Res. vol. 114, pp. 1–9, 2014.
  • [40] G. T. Singh, C. Anil Kumar, and V. N. A. Naikan, Induction motor inter turn fault detection using infrared thermographic analysis, Infrared Phys. Technol. vol. 77, pp. 277–282, 2016.
  • [41] F. Filipetti, G. Franceschini, C. Tassoni, and P. Vas, EAI techniques in induction machine diagnosis including the speed ripple effect, IEEE Transactions India Applications, vol. 34(1), pp. 98-108, 1998.
  • [42] J.R. Mountain, Fuzzy logic Motor Speed Control with Real-Time interface using 8-bit Embedded Processor, 42nd South Eastern Symposium on System Theory, March 2010.
  • [43] F. Rashidi. Sensorless speed sontrol of induction motor drives using robust and adaptive neuro-fuzzzy based intelligent controller. IEEE international conference on industrial technology (ICIT), pp. 617- 627, 2004.
  • [44] S.S. Tijare, G.D. Thakare, R.P. Argelwar. Multi-purpose DC high voltage generator using CockcroftWalton voltage multiplier circuit. International Journal for scientific Research and development, vol. 2(12), 2015.
  • [45] M. Nikhil, R. Waghamare, P. Argelwar, A. Thakare and S. Urkude. Battery Operated Multistage High voltage generation by using Cockcroft Walton multiplier. International Journal of Engineering Sciences & Research Technology, vol. 4(3) 2015
  • [46] R.S. Marino, S. Peresada and P. Valigi, Adaptive Input-Output Linearizing Control of Induction Motor, IEEE Transaction on Automatic Control, vol. 38(2), pp. 208-221, 2014.
  • [47] L. Frosini, A. Borin, L. Girometta et al., A novel approach to detect short circuits in low voltage induction motor by stray flux measurement, Proc. Int. Conf. Electrical Machines (ICEM), pp. 1538-1544, 2012.
  • [48] L.P.C.M. Filho, R. Pederiva, J.N. Brito, Detection of stator winding faults in induction machines using flux and vibration analysis, Mech. Syst. Signal Process., vol. 42(1), pp. 377-387, 2014.
  • [49] R. Romary, R. Pusca, J.P. Lecointe et al., Electrical machines fault diagnosis by stray flux analysi, Proc. Int. Conf. Electrical Machines Design Control and Diagnosis (Wemdcd), pp. 247-256, 2013
  • [50] O.P. Sondhiya, A.K. Gupta Wear Debris Analysis of Automotive Engine Lubricating Oil Using By Ferrography. International Journal of Engineering and Innovative Technology, vol. 2(5), 2012.
  • [51] A K Agarwal. Experimental investigations of the effect of biodiesel utilization on lubricating oil tribology in diesel engines, Automobile Engineering, vol. 219(D), pp. 703-713, 2005.
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