Korea University · 工学
Professor Sang Bin Lee's research lab specializes in condition monitoring and fault diagnosis of electric machines, with a strong focus on sensorless and online diagnostic techniques for induction motors. The lab develops advanced electrical, thermal, and insulation monitoring methods—such as stator resistance-based temperature estimation, turn fault detection via sequence component impedance, and online insulation assessment using leakage current measurements—to enhance motor reliability and predictive maintenance. Their work emphasizes robustness against motor nonidealities, such as voltage unbalance and parameter uncertainty, ensuring practical applicability in industrial environments. The lab also investigates fault prognostics and the mitigation of false positives in motor current signature analysis, aiming to reduce downtime and maintenance costs in critical industries like pulp and paper.
Figures are computed from collected data and may differ slightly.
A simple and robust sensorless technique for online stator winding turn fault detection based on monitoring an off-diagonal term of the sequence component impedance matrix is proposed in this paper. Due to the destructive and rapidly propagating nature of insulation failure, it is critical to detect turn faults in an early stage to prevent further damage to the motor. The motor nonidealities such as the variation in the supply voltage unbalance, slip-dependent influence of inherent motor asymmet
A new technique for stator-resistance (R/sub s/)-based thermal monitoring of small line-connected induction machines is proposed in this paper. A simple device is developed for injecting a small DC signal into line-connected induction machines for estimation of R/sub s/. The proposed DC injection device is capable of intermittently injecting a controllable DC bias into the motor with very low power dissipation. Experimental results under motor startup, load variation, and abnormal cooling condit
The limitations of the thermal, vibration, or electrical monitoring of electric machines such as false indications, low sensitivity, and difficulty of fault interpretation have recently been exposed. This has led to a shift in the direction in research toward applying new techniques for improving the reliability of condition monitoring. With the changing environment, the purpose of this article is to provide an overview of the recent trends in the industrial demand and research activity in condi
In this paper, the feasibility of using an estimate of the stator resistance (R/sub s/) as an indicator of stator winding temperature (T/sub s/) is evaluated. The advantages of resistance-based temperature monitoring over conventional thermal model-based methods are presented. Since obtaining an accurate estimate of R/sub s/ is critical for this approach, an investigation of existing R/sub s/ estimation schemes, and an analysis showing the sensitivity of model-based R/sub s/ estimation due to th
Motor current signature analysis (MCSA) has become an essential part of the preventive maintenance program for monitoring the condition of the rotor cage in medium-voltage induction motors in the pulp and paper industry. However, many cases of false indications due to interference from the motor or the load have been reported. False indications can result in unnecessary inspection and outage costs (false positives) or major repair/replacement costs and loss of production (false negatives). The o
A novel online technique for monitoring the insulation condition of ac machine stator windings is proposed in this paper. The concept is to measure the differential leakage currents of each phase winding from the terminal box in a noninvasive manner to assess the insulation condition during motor operation. The conventional differential CTs used for phase fault protection can be replaced with high performance current sensors to measure the leakage current with higher accuracy. Indicators for ins
An online technique for monitoring the condition of the groundwall (GW) and phase-to-phase (PP) insulation for three-phase ac-machine stator windings is proposed in this paper. Insulation-condition indicators such as capacitance, dissipation factor (tan/spl delta/), and ac insulation resistance are calculated online based on the differential leakage-current measurements for each phase. A model for a three-phase ac-machine insulation system is derived and analyzed for both offline and online test
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