Doosoo Hyun

Detection of Eccentricity Faults in Induction Machines Based on Nameplate Parameters

Eccentricity-related faults in induction motors have been studied extensively over the last few decades. They can exist in the form of static or dynamic eccentricity or both, in which case it is called a mixed eccentricity fault. These faults cause bearing damage, excessive vibration and noise, unbalanced magnetic pull, and under extreme conditions, stator-rotor rub which may seriously damage the motors. Since eccentricity faults are often associated with large induction machines, the repair or replacement costs arising out of such a scenario may easily run into tens and thousands of dollars. Previous research works have shown that it is extremely difficult to detect such faults if they appear individually, rather than in mixed form, unless the number of rotor bars and the pole-pair number conform to certain relationships. In this paper, it is shown that the terminal voltages of induction machines at switch-off reveal certain features that can lead to the detection of these faults in individual form, even in machines that do not show these signatures in line-current spectrum in steady state, or to the detection of the main contributory factor in case of mixed eccentricity.

Detection and Classification of Rotor Demagnetization and Eccentricity Faults for PM Synchronous Motors

Condition monitoring of rotor problems such as demagnetization and eccentricity in permanent magnet synchronous motors (PMSM) is essential for guaranteeing high motor performance, efficiency, and reliability. However, there are many limitations to the off-line and on-line methods currently used for PMSM rotor quality assessment. In this paper, an inverter-embedded technique for automated detection and classification of PMSM rotor faults is proposed as an alternative. The main concept is to use the inverter to perform a test whenever the motor is stopped, to detect rotor faults independent of operating conditions or load torque oscillations, which is not possible with motor current signature analysis (MCSA). The d-axis is excited with a dc+ac signal, and the variation in the inductance pattern due to the change in the degree of magnetic saturation caused by demagnetization or eccentricity is observed for fault detection. An experimental study on a 7.5kW PMSM verifies that demagnetization and eccentricity can be detected and classified independent of the load with high sensitivity.

Reliable Detection of Induction Motor Rotor Faults Under the Rotor Axial Air Duct Influence

Axial cooling air ducts in the rotor of large induction motors are known to produce magnetic asymmetry and can cause steady-state current or vibration spectrum analysis based fault detection techniques to fail. If the number of axial air ducts and that of poles are identical, frequency components that overlap with that of rotor faults can be produced for healthy motors. False positive rotor fault indication due to axial ducts is a common problem in the field that results in unnecessary maintenance cost. However, there is currently no known test method available for distinguishing rotor faults and false indications due to axial ducts other than offline rotor inspection or testing. Considering that there is no magnetic asymmetry under high slip conditions due to limited flux penetration into the rotor yoke, the detection of broken bars under the start-up transient is investigated in this paper. A wavelet-based detection method is proposed and verified on custom-built lab motors and 6.6-kV motors misdiagnosed with broken bars via steady-state spectrum analysis. It is shown that the proposed method provides the reliable detection of broken bars under the start-up transient independent of axial duct influence.

Detection of Airgap Eccentricity for Induction Motors Using the Single-Phase Rotation Test

The single-phase rotation test (SPRT) is a simple and reliable offline test frequently used for detecting problems in the rotor cage of induction motors without motor disassembly. Airgap eccentricity due to bearing degradation, shaft flexing, etc., is another problem that is difficult to detect, which can cause catastrophic motor failure. In this paper, the feasibility of using the SPRT for detecting eccentricity, which has not been reported before, is investigated. The variation in the inductive component as a function of rotor position and time under static, dynamic, and mixed eccentricity conditions is analyzed. It is shown that airgap eccentricity can be detected in addition to rotor cage problems with the SPRT. An experimental study on a 7.5-Hp induction motor under controlled eccentricity and broken bar conditions shows that airgap eccentricity can be reliably detected with high sensitivity and distinguished from broken rotor bars.

Automated Monitoring of Magnet Quality for Permanent-Magnet Synchronous Motors at Standstill

Demagnetization of permanent magnets (PMs) used in synchronous motors can occur due to a combination of thermal, electrical, and/or environmental operating stresses. Since PM demagnetization results in degradation of motor performance, efficiency, and reliability, it is important to monitor the quality of PMs regularly. However, there are many limitations to the offline and online methods currently used for magnet quality assessment. In this paper, a new inverter-embedded technique for automated monitoring of magnet quality for permanent-magnet synchronous motors (PMSMs), which overcomes the limitations of existing techniques, is proposed. The main concept is to use the inverter to perform a standstill test whenever the motor is stopped to detect local or uniform PM demagnetization. The machine is excited with a pulsating field at different angular positions, and the change in the current peaks caused by the change in the degree of magnetic saturation due to demagnetization is observed. An experimental study on a 10-hp PMSM verifies that local and uniform PM demagnetizations can be detected with high sensitivity.

Detection of Stator-Slot Magnetic Wedge Failures for Induction Motors Without Disassembly

The recent trend in large ac machines is to employ magnetic stator-slot wedges for improving the motor efficiency, power factor, and power density. The mechanical strength of magnetic wedges is weak compared to the epoxy glass wedges, and many cases of loose and missing wedges have recently been increasingly reported. Magnetic wedge failure deteriorates the performance and reliability of the motor, but there is no method available for testing the wedge quality other than visual inspection after rotor removal. Monitoring of the overall wedge condition without motor disassembly can help reduce the cost of maintenance and risk of degradation in performance. In this paper, a new offline standstill test method for detecting magnetic wedge problems for ac machines without motor disassembly is proposed. An experimental study on 380-V 5.5-kW and 6.6-kV 3.4-MW motors with magnetic wedges is performed to verify the effectiveness of the new test method. It is shown that the new method can provide reliable monitoring of magnetic wedge problems over time, independent of other faults or motor design.

Offline Monitoring of Airgap Eccentricity for Inverter-Fed Induction Motors Based on the Differential Inductance

The monitoring of airgap eccentricity for induction motors is important for guaranteeing motor reliability, since eccentricity can eventually lead to motor failure due to stator-rotor contact. However, there are many limitations to applying existing test methods such as the motor current signature analysis in the field, particularly for variable frequency applications. In this paper, a new inverter-embedded test approach for detecting eccentricity for induction motors is proposed. The main concept is to use the inverter to perform a standstill test whenever the motor is stopped, to extract information on motor eccentricity. The motor is excited with a low-frequency pulsating ac field superimposed on different levels of dc fields, and the variation in the differential inductance pattern due to the change in the degree of magnetic saturation caused by eccentricity is observed. An experimental study on a 7.5-Hp induction motor under controlled eccentricity conditions verifies that the sensitivity of eccentricity detection can be significantly improved compared with existing methods.

Automated monitoring of airgap eccentricity for inverterfed induction motors under standstill conditions

There are many limitations to applying on-line spectrum analysis techniques for diagnosis of closed loop inverter-fed induction motors due to variable load or frequency operation, and the masking effect of the current regulator. In this paper, a new automated approach for testing inverter-fed induction machines for airgap eccentricity is proposed. The main concept is to use the inverter to excite the machine with a pulsating field at multiple angular positions to observe the variation of equivalent impedance due to eccentricity, whenever the motor is stopped. It is shown that the increase in the value of the equivalent (leakage) inductance under standstill excitation can be used as an indicator of increasing airgap eccentricity. Standstill testing can provide reliable assessment of eccentricity that is independent of variations in operating conditions, load interferences, or motor type. An experimental study on a 7.5hp induction motor verifies that eccentricity can be detected with high sensitivity and reliability without additional hardware.

Pole pair and rotor slot number independent frequency domain based detection of eccentricity faults in induction machines using a semi on-line technique

Eccentricity related faults in Induction motors have been studied extensively over the last few decades. They can exist in the form of static or dynamic eccentricity or both, in which case it is called a mixed eccentricity fault. These faults cause bearing damage, excessive vibration and noise, unbalanced magnetic pull (IMP) and under extreme conditions stator-rotor rub which may seriously damage the motors. Since eccentricity faults are often associated with large induction machines, the repair or replacement costs arising out of such a scenario may easily run into tens and thousands of dollars. Previous research have shown that it is extremely difficult to detect such faults if they appear individually, rather than in mixed form, unless the number of rotor bars and pole pair number conform to certain relationships. In this paper, it is shown that the terminal voltages of induction machines at switch-off reveal certain features that can lead to the detection of these faults in individual form, even in machines that do not show these signatures in line current spectrum in steady state.

Detection and classification of rotor demagnetization and eccentricity faults for PM synchronous motors

Condition monitoring of rotor problems such as demagnetization and eccentricity in permanent magnet synchronous motors (PMSM) is essential for guaranteeing high motor performance, efficiency, and reliability. However, there are many limitations to the off-line and on-line methods currently used for PMSM rotor quality assessment. In this paper, an inverter-embedded technique for automated detection and classification of PMSM rotor faults is proposed as an alternative. The main concept is to use the inverter to perform a test whenever the motor is stopped, to detect rotor faults independent of operating conditions or load torque oscillations, which is not possible with motor current signature analysis (MCSA). The d-axis is excited with a dc+ac signal, and the variation in the inductance pattern due to the change in the degree of magnetic saturation caused by demagnetization or eccentricity is observed for fault detection. An experimental study on a 7.5kW PMSM verifies that demagnetization and eccentricity can be detected and classified independent of the load with high sensitivity.