Conference Papers
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Item Investigation into effect of mixed air gap eccentricity on dq components of currents in induction motor(2011) Rajalakshmi Samaga, R.; Vittal, K.P.dq components of currents are extensively used in the controller applications of industrial drives as they are dc quantities. In this paper, it is shown that these components will no longer remain as dc quantities, if they are extracted from the induction motor suffering from mixed air gap eccentricity. A dynamic model of an induction motor suffering from mixed air gap eccentricity is developed and simulated to show the presence of eccentricity characteristic harmonics in dq components of the stator currents in synchronous reference frame. In this paper, it is also shown that the frequency analysis of dq currents helps in the detection of air gap non uniformity in the machine. The results obtained by modeling and simulation are also validated experimentally. © 2011 IEEE.Item Effect of unbalance in voltage supply on the detection of mixed air gap eccentricity in an induction motor by Motor Current Signature Analysis(2011) Rajalakshmi Samaga, B.L.; Vittal, K.P.; Jhunjhunwala, V.K.Condition monitoring units are employed in industries to monitor the health of the machines continuously. Air gap eccentricity fault is one of the asymmetrical faults which can result in the machine failure. Motor Current Signature Analysis and Vibration Analysis are the two most popular methods used for eccentricity fault detection in the induction motor. In this paper, a study conducted on an induction motor to analyse the effect of supply voltage unbalance on the method of eccentricity fault detection by Motor Current Signature Analysis is presented. A dynamic model of the induction motor suffering from air gap eccentricity and has the capability to take unbalance supply voltage is developed and the results obtained by simulating this model are validated by the experiments conducted on an induction motor suffering from inclined mixed eccentricity and fed with unbalance voltage supply. © 2011 IEEE.Item Inclined mixed air gap eccentricity detection method for an induction motor(IEEE Computer Society, 2014) Rajalakshmi Samaga, B.L.; Vittal, K.P.Significant number of research articles on axial uniform mixed air gap eccentricity detection methods in three phase squirrel cage induction motor are reported in literature. Most often, machines suffer from non uniform axial air gap eccentricity. In this paper, a study conducted on a three phase squirrel cage induction motor suffering from inclined mixed air gap eccentricity is presented and a new parameter is introduced to detect the inclined eccentricity fault. Experiments were conducted on 3 phase squirrel cage induction motor to show the impact of inclined mixed air gap eccentricity on dq components of stator currents. To validate the experimental results, mathematical expressions and modeling and simulation results are presented. The paper concludes with a note that an eccentricity detection unit with dq components of stator currents in synchronous reference frame as detection parameters can be embedded in the controller circuit to monitor the health of the machine. © 2014 IEEE.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.Item Detection of Industrial Motor Fault using Signal Processing Algorithms(Institute of Electrical and Electronics Engineers Inc., 2024) Bhaumik, D.Induction motors are the most commonly used motor in petrochemicals, agrochemicals, pharmaceuticals, cement, steel, and many other process industries. A failure of any single component or sub-components of the induction motor can result in a plant shutdown. Hence, it is crucial to diagnose different types of faults in induction motors. The current study overviews a vibration-based condition monitoring method for detecting bent shaft failures in large industrial induction motors. This four-pole, 1.7-MW induction motor is primarily utilized in the petrochemical sector. A bent shaft is a typical problem with the motor's rotational portion. A bent shaft creates excessive vibration in a machine depending on the extent and position of the bend. This present study uses vibration data samples collected during the last four years. The data is collected from the deteriorating status of the induction motor. As the vibration signal of the corresponding data sets is non-stationary time-frequency domain analysis is mainly used. Several types of failures happened in various frequency sub-bands of an induction motor. As a result, the discrete wavelet transform is primarily utilized to detect defective frequency ranges. The objective of this study is to use discrete wavelet transform based vibration analysis to check if there is a trend in percentage energy and, if so, to identify the frequency range of the bent shaft issue of an induction motor. In discrete wavelet transform analysis, the detail sub-band-1 shows the deteriorating condition of an induction motor. The frequency range of detail sub-band-l is 1280 Hz to 2560 Hz. On the time-frequency plots, more precise detection of frequency range may be obtained. If the vibration is increased from the lowest to highest peak value in a time-frequency plot, the corresponding energy likewise attempts to locate compactly in discrete bits. © 2024 IEEE.