Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
Browse
2 results
Search Results
Item Vibration Data and Analysis of A Large rating Induction Motor with Bent Shaft: Some Aspects(Institute of Electrical and Electronics Engineers Inc., 2020) Sadda, A.; Punekar, G.S.Operation of many equipment in an energy intensive industry are very critical. The no-provision of standby can increase this criticality multi-fold. The motor under study for this paper is one such equipment where the development of bend in rotor shaft was observed during diagnosis of a breakdown event due to high bearing temperature protection. This is a 1.7 MW Induction Motor of a petrochemical industry. Due to non-availability of spare motor, the motor with developing bentshaft-problem was kept under operation with increased monitoring. The incipient stage detection of the motor vibration due the bent-shaft lead to additional condition monitoring. The vibration data sampled over a period of nearly four and half years with changed bearings is analyzed and reported in this paper. Attempt is made to monitor the defect in the motor with the change in vibration levels as a function time of operation of the motor with the help of vibration trends. Over the period of observation, the average vibrations showed an increasing trend in the range of 0.2 mm/s to 0.6 mm/s with the bent shaft, although these values are well within the acceptable upper limit. Finally, the vibration data is compared with those of replaced (new) motor. © 2020 IEEE.Item Vibration Signal Analysis of Induction Motor Bearing Faults: Some Aspects(Institute of Electrical and Electronics Engineers Inc., 2023) Bhaumik, D.; Sadda, A.; Punekar, G.S.Vibration monitoring and analysis techniques are among the most commonly used methods in identifying defects in induction motors. Motor defects like bent shafts and bearing defects are analyzed, focusing on twice-line-frequency (100 Hz) components for the vibration data of an induction motor belonging to a petrochemical industry. The motor defect in this case was a bent shaft. A marginal correlation between the vibration data and the 100 Hz component could be seen. A similar study is attempted using another data set collected from web resources. The tracking twice-line-frequency data reveals progressive deterioration of the motor condition with time; this is in spite of the motor exhibiting vibrations within the acceptable limits as per ISO 10816-3. As the vibration signals are non-stationary, the second data set is analyzed using discrete wavelet transform (DWT). The sub-band D4 of DWT showed a definite correlation with the ball-bearing faults. © 2023 IEEE.