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2018 | 91 | 31-43
Article title

Condition monitoring of systems in thermal power plant for vibration, motor signature, noise and wear debris analysis

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Condition monitoring is technique used to monitor the condition of an equipment or machinery without interrupting it working. Condition monitoring techniques are carried out when the machine is in operation. Most widely used condition monitoring techniques include vibration monitoring, motor current signature analysis, noise monitoring and wear debris analysis. Vibration monitoring detects the presence of unbalanced forces generated due to misalignment, damaged bearing, electrical defects and resonance. Motor current signature analysis is used to determine the defects in motor by analyzing the spectrum generated by the tongue tester. Noise monitoring is performed with the help of acoustic noise meter and wear debris is done to determine the contamination level of lubrication oil in various engines. These techniques are found to be highly efficient in determining the defects of the systems like pump at an early stage. A detailed study on these condition monitoring techniques has been carried out in this paper and also the methods for analysis of the results obtained from these tests are also discussed.
Physical description
  • Mechanical Engineering Department, University of Petroleum and Energy Studies, Dehradun, India
  • Mechanical Engineering Department, University of Petroleum and Energy Studies, Dehradun, India
  • [1] C. De Michelis, C. Rinaldi, C. Sampietri, and R. Vario, “2 - Condition monitoring and assessment of power plant components,” in Power Plant Life Management and Performance Improvement, J. E. Oakey, Ed. Woodhead Publishing, 2011, pp. 38–109.
  • [2] V. Medica-Viola, B. Pavković, and V. Mrzljak, Numerical model for on-condition monitoring of condenser in coal-fired power plants, Int. J. Heat Mass Transf. vol. 117, no. Supplement C, pp. 912–923, 2018.
  • [3] M. N. James, D. G. Hattingh, D. Asquith, M. Newby, and P. Doubell, Residual stresses in condition monitoring and repair of thermal power generation components, Theor. Appl. Fract. Mech. vol. 92, no. Supplement C, pp. 289–297, 2017.
  • [4] G. M. West, S. D. J. McArthur, and D. Towle, Industrial implementation of intelligent system techniques for nuclear power plant condition monitoring, Expert Syst. Appl. vol. 39, no. 8, pp. 7432–7440, 2012.
  • [5] A. Roque, J. M. F. Calado, and J. M. Ruiz, Vibration Analysis versus Current Signature Analysis, IFAC Proc. Vol., vol. 45, no. 20, pp. 794–799, 2012.
  • [6] V. Dlamini, R. Naidoo, and M. Manyage, A non-intrusive method for estimating motor efficiency using vibration signature analysis, Int. J. Electr. Power Energy Syst. vol. 45, no. 1, pp. 384–390, 2013.
  • [7] A. Adamkowski, A. Henke, and M. Lewandowski, Resonance of torsional vibrations of centrifugal pump shafts due to cavitation erosion of pump impellers, Eng. Fail. Anal. vol. 70, no. Supplement C, pp. 56–72, 2016.
  • [8] X. Wang, T. Li, and L. Zhao, Vibration analysis of large bulb tubular pump house under pressure pulsations, Water Sci. Eng. vol. 2, no. 1, pp. 86–94, 2009.
  • [9] W. Fiebig and M. Korzyb, Vibration and dynamic loads in external gear pumps, Arch. Civ. Mech. Eng. vol. 15, no. 3, pp. 680–688, 2015.
  • [10] D. Siano, E. Frosina, and A. Senatore, Diagnostic Process by Using Vibrational Sensors for Monitoring Cavitation Phenomena in a Getoror Pump Used for Automotive Applications, Energy Procedia, vol. 126, no. Supplement C, pp. 1115–1122, 2017.
  • [11] R. S. Beebe, 6 - Vibration analysis of pumps - basic, in Predicitive Maintenance of Pumps Using Condition Monitoring, R. S. Beebe, Ed. Amsterdam: Elsevier Science, 2004, pp. 83–100.
  • [12] I. Bravo-Imaz, H. D. Ardakani, Z. Liu, A. García-Arribas, A. Arnaiz, and J. Lee, Motor current signature analysis for gearbox condition monitoring under transient speeds using wavelet analysis and dual-level time synchronous averaging, Mech. Syst. Signal Process. vol. 94, no. Supplement C, pp. 73–84, 2017.
  • [13] V. F. Pires, M. Kadivonga, J. F. Martins, and A. J. Pires, Motor square current signature analysis for induction motor rotor diagnosis, Measurement, vol. 46, no. 2, pp. 942–948, 2013.
  • [14] C. Kar and A. R. Mohanty, Monitoring gear vibrations through motor current signature analysis and wavelet transform, Mech. Syst. Signal Process. vol. 20, no. 1, pp. 158–187, 2006.
  • [15] P. W. Wessels and T. G. H. Basten, Design aspects of acoustic sensor networks for environmental noise monitoring, Appl. Acoust. vol. 110, no. Supplement C, pp. 227–234, 2016.
  • [16] P. Maijala, Z. Shuyang, T. Heittola, and T. Virtanen, Environmental noise monitoring using source classification in sensors, Appl. Acoust. vol. 129, no. Supplement C, pp. 258–267, 2018.
  • [17] D. G. Albert and S. N. Decato, Acoustic and seismic ambient noise measurements in urban and rural areas, Appl. Acoust. vol. 119, no. Supplement C, pp. 135–143, 2017.
  • [18] A. V. Vasilyev, New Methods and Approaches to Acoustic Monitoring and Noise Mapping of Urban Territories and Experience of it Approbation in Conditions of Samara Region of Russia, Procedia Eng. vol. 176, no. Supplement C, pp. 669–674, 2017.
  • [19] Y. Peng et al., A hybrid search-tree discriminant technique for multivariate wear debris classification, Wear, vol. 392–393, no. Supplement C, pp. 152–158, 2017.
  • [20] H. L. Costa, M. M. O. Junior, and J. D. B. de Mello, Effect of debris size on the reciprocating sliding wear of aluminium, Wear, vol. 376–377, no. Part B, pp. 1399–1410, 2017.
  • [21] Y. Peng, T. Wu, S. Wang, and Z. Peng, “Wear state identification using dynamic features of wear debris for on-line purpose,” Wear, vol. 376–377, no. Part B, pp. 1885–1891, 2017.
  • [22] C. K. and A. K. Srivastava, Investigation on power aspects in impressed current cathodic protection system, J. Corros. Sci. Eng. vol. 20, p. 10, 2017.
  • [23] S. Raadnui and S. Kleesuwan, Electrical pitting wear debris analysis of grease-lubricated rolling element bearings, Wear, vol. 271, no. 9, pp. 1707–1718, 2011.
  • [24] S. Feng, B. Fan, J. Mao, and Y. Xie, Prediction on wear of a spur gearbox by on-line wear debris concentration monitoring, Wear, vol. 336–337, no. Supplement C, pp. 1–8, 2015.
  • [25] D. Bose and A. Bose, Electrical Power Generation with Himalayan Mud Soil Using Microbial Fuel Key Words. Nat. Environ. Pollut. Technol. vol. 16, no. 2, pp. 433–439, 2017.
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