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Medium Voltage Induction Motor Protection and Diagnostics
Yi DuPinjia Zhang
Prof. Thomas G. Habetler
School of Electrical and Computer EngineeringGeorgia Institute of Technology
Atlanta, GA
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Medium Voltage Facilities
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Medium Voltage Supply
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Medium Voltage Laboratory
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• Introduction• Heat transfer inside Motors• Thermal Model-Based Approaches• Parameter Model-Based Approaches• Other Approaches
Outline
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Medium voltage induction motors
Mostly used in the petroleum, chemical, mining and other industries,
Rated from 2300 V to 13200 V, They are rotor limited during
starting, and stator limited under overload.
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Overload Protection
Malfunctions of these motors are very costly due to loss of productivity,
The winding insulation failure is a typical malfunction, which is often caused by overload.
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Conventional Overload Relays
Stator Temperature
Ambient Temperature
Current Unbalance Bias
Overload Curve
Current Measurement
Voltage Measurement
Thermal Capacity Check
Alarm/Trip
Alarm/Trip
Cooling Time Constant
Motor Parameters Conventional overload
relays utilize simple thermal models and embedded temperature sensors.
Simple thermal models can not estimate the rotor temperature.
Disintegration of the connection, noise interference, and large time constant of the sensors often result in false alarm or trips.
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Requirements
Track the thermodynamic behavior of the motor's stator and rotor under steady and transient state conditions.
It should also take into account the important differences in the thermal behavior due to the motor size and the type of construction and ventilation.
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Possible Approaches
Higher order thermal model-based approachesModel the thermal behavior of the motor. The thermal parameters are calculated from the motor dimensions and offline experiments. This approach is robust, but measurements need be made for each motor.
Parameter-based approachesEstimate the temperature from the variation of the resistance of the stator and rotor. This method can respond to changes in the cooling conditions, and is accurate, but it is generally too sensitive.
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• Introduction• Heat Transfer inside Motors• Thermal Model-Based Approaches• Parameter Model-Based Approaches• Other Approaches
Outline
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Motor Losses
The temperature rise inside a motor is caused by the losses accumulated in the motor.
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Loss Segregations
Wcopper Wcore Wf&w Wstray
2 Pole 53 9 29 9
4 Pole 55 15 18 12
6 Pole 62 13 12 13
Wcopper Wcore Wf&w Wstray
2 Pole 29 15 36 20
4 Pole 35 18 24 23
6 Pole 37 23 18 22
Compared with low power motors, high power motors have larger percentage of core loss and stray loss, and smaller percentage of copper loss.
Therefore, the thermal model only considering copper loss is not suitable for large motors.
Loss segregation for 15Hp motor
Loss segregation for 200~2000Hp motors
losses s r core fw LLW W W W W W
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Heat Transfer
The heat transfer inside a motor can be classified into
Conduction - transfer of heat due to the temperature difference.Shaft – rotor iron – rotor winding, Stator winding – stator iron – Frame, …
Convection - transfer of heat due to the fluid motion.Frame - external air, stator/rotor– airgap, rotor – endcap air, ...
Radiation - transfer of heat by electromagnetic radiation.Radiation is ignored since the motor temperature is relatively low.
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Thermal resistance and thermal capacitance
Thermal behavior of the motor can be analyzed byFinite element methods (Time consuming)Lumped-parameter thermal network, composed of thermal resistors, thermal capacitors and heat sources.
Some thermal resistances and thermal capacitances can be calculated directly from the motor dimensions.Other thermal resistances are complex and can only be measured online.
Stator core to frame conduction resistanceEndwinding cooling resistanceFrame to ambient convection resistance
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Thermal Network
Given the difficulties to calculate certain thermal parameters, detailed thermal models can not guarantee good accuracy.Simplification of the thermal network is preferred for online monitoring.On the other hand, the thermal network should be complex enough to estimate the hot spot temperature.
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• Introduction• Heat Transfer inside Motors• Thermal Model-Based Approaches• Parameter Model-Based Approaches• Other Approaches
Outline
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Thermal Model-based Approaches
Use thermal network to model the thermal behavior of the motor.The Motor is divided into homogenous components wherein each part has a uniform temperature and heat transfer coefficients.The heat flow paths are determined and thermal resistors are added between the nodes.Losses and thermal capacitors are allocated to each node.
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First - order Thermal Model
Used in conventional relays for its simplicity,Do not consider the rotor winding temperature,The stator winding temperature is given by,
0( ) (1 )th th th th
t tR C R C
s loss th s At P R e e
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First - order Thermal Model
Thermal resistance Rth and thermal capacitance Cth can be directly calculated from the trip class t6x and the service factor SF.
Assume the loss Ploss equals the stator copper loss2
6 2 2
6/[ln( )]6th th xR C t
SF
Cth is calculated using the trip class and the winding insulation class.
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First - order Thermal Model
Temperature rise is a complex combination of distributed thermal capacitances and resistances, single time constant is not enough.Therefore, large margin is needed for safety and the motor is over protected.The rotor temperature can not be monitored.
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Second - order Thermal Model
Stator and rotor are modeled separately,Model B eliminate the node while maintaining the same function.Parameters are calculated from offline experiments
Model A
Model B
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Second - order Thermal Model
Model C simplifies the rotor side, and less parameters are needed.Second-order thermal model is a good tradeoff between accuracy and complexity.
Model C
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Higher - order Thermal Model
Model the hot spot, such as end windings, seperately. The thermal model becomes complex and it is difficult to identify the parameters.
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• Introduction• Heat Transfer inside Motors• Thermal Model-Based Approaches• Parameter Model-Based Approaches• Other Approaches
Outline
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Estimate the temperature from the variation of the stator winding resistance and the rotor bar resistance.
Parameter-based Approaches
It is an online method and can respond to changes in the cooling conditions.
1
1)(ktktRR
a
bab
k1 is 234.5 for 100% IACS conductivity copper
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•Rotor resistance can be calculated in the synchronous reference frame with the d-axis aligned with the stator current. Under the steady state, the rotor resistance, which is independent of the stator resistance, is given by
Rotor Resistance
•Rotor resistance can also be calculated in the stationary reference frame and rotor reference frame.•By these methods, the rotor resistance is independent of the stator resistance and is less sensitive to the parameter variations.
22ˆ ( ) [ ]s m
r s r rqs
s ss
LR s L LVL
I
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•Stator resistance is generally calculated based on rotor resistance.•In the synchronous reference frame with the d-axis aligned with the stator current, the stator resistance is given by,
Stator Resistance
2 ˆˆˆ
e eds e m dr
s e eds r ds
V s LRi R i
•Rotor speed can be calculated from the stator current harmonics.
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• Introduction• Heat transfer inside Motors• Thermal Model-Based Approaches• Parameter Model-Based Approaches• Other Approaches
Outline
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Neural Network - based Approaches
•Neural networks have been proposed to estimate the stator resistance and rotor resistance.•The advantages are that they do not require the motor parameters and can be easily implemented.
•The drawbacks are they are still sensitive to the parameter changes since the network is trained using the data based on certain parameters.
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Hybrid Approaches
•Combine thermal model – based approaches with parameter – based approaches,•Rotor temperature is estimated by parameter –based approaches since it is less sensitive to the parameter variations,•Stator temperature is monitored by thermal model – based approaches.
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Signal Injection-based Approaches
, , ,
, , ,
2 2ˆ3 3
as dc ab dc sw dcs
as dc as dc as dc
V V VR
i i i
•The stator resistance is estimated from the dc components of the voltage and current.•Relatively accurate since it is not affected by the inductance of the motor.•It is intrusive and introduces torque oscillation.
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Overview of Fault Diagnostics for MV Motors
Distribution of MV Induction Motor Failures
Induction Motor Fault Categories
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OUTLINE
Overview of Fault Diagnostics for MV Motors Bearing Failure and its Diagnostic Stator Winding Inter-turn Fault and its Diagnostic Rotor Fault and its Diagnostic
– Broken Rotor Bar & End-Ring Faults and their Diagnostic– Rotor Eccentricity and its Diagnostic
Conclusions
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Overview of Fault Diagnostics for MV Motors
Distribution of MV Induction Motor Failures
Induction Motor Fault Categories
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Analysis of Fault Diagnostics for MV Motors
Main differences between MV motors and small low-voltage motors:
High Insulation Requirement for Stator Winding: stator winding inter-turn fault
Large Output Torque: rotor and bearing-related mechanical faults
High Thermal Stress: stator insulation failure and rotor-related faults
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Bearing Failure Monitoring
Bearing failure is the most common fault for MV motors.
Reasons for Bearing Failure Electrical Stress:
Stator, rotor or input voltage unbalance causes unbalanced magnetic flux, which induces shaft current, and potential voltage between bearing and ground.
Mechanical Stress:– Friction and rotor eccentricity can cause
mechanical failure of bearings. Thermal Stress:
– Overheat causes the failure of lubricant, which lead to friction.
Outer raceway
Inner raceway
Ball
Cage
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Bearing Failure Monitoring
Classification of Bearing Failure:
Single Point Defects:– Outer raceway– Inner raceway– Ball– Cage
Generalized Roughness
Existing Methods:•Standard vibration sensor method•Chemical analysis method•Temperature monitoring•Acoustic emission method•Sound pressure method•Current signature spectra method
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Current signature spectra methods
1.Single point defects: Wavelet method Neural network clustering method Adaptive time-frequency method Park vector trajectory method Other methods2.Generalized roughness: Mean spectrum deviation methodFundamentally: monitor the E-M torque harmonics corresponding to
the mechanical vibration frequencies
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Bearing Failure Monitoring
is the power supply frequency; is the vibration frequency;is the corresponding stator current signature frequency.
Challenges for MV motorsFor single point defects: Poor Signal/Noise Ratio
Due the large output torque, the torque vibration caused by bearing failure is more difficult to observe. So the low signal/noise ratio is a potential problem for current-based bearing diagnosis of large MV motors.
For generalized roughness: Separate measurement noise and bearing failure-related vibration
noise
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Stator Winding Inter-turn Faults
Reasons for Stator Inter-turn Fault Electrical Stress:
– High voltage causes winding insulation failure Thermal Stress
– Motor life is reduced by 50% for every 10°C above limit Mechanical Stress
– Friction between stator and rotor caused by rotor eccentricity Other Stress
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Stator Winding Inter-turn Faults
Stator Inter-turn Fault
Existing Methods:• Negative Sequence Current• Negative Sequence Impedance• E-M Torque Harmonics• Current Spectrum• Current Park Vector Trajectory• Artificial Intelligent MethodsFundamentally: Monitor the unbalance of stator winding
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Stator Winding Inter-turn Fault and its Diagnostic
Coupling between Negative-Sequence and Positive-Sequence models due to
stator winding asymmetry
Stator Inter-turn Fault Indicator (function of
slip frequency)Challenges:• How to consider voltage unbalance in power supply• How to consider original stator winding unbalance• How to set threshold for negative-sequence impedance
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Rotor-related Failures
Rotor-related faults can be classified into: Broken Rotor Bar Broken Rotor End-Ring Rotor Eccentricity (shaft misalignment)
Reasons for rotor-related faults: Mechanical stress: including rotor eccentricity, and stator-rotor
friction Thermal stress: overheat in rotor can cause rotor deterioration Electrical stress: frequency starting and overload operations
can cause thermal stress due to large current; unbalanced flux can induce unbalanced magnetic pull.
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Broken Rotor Bar and End-Ring Faults
Broken rotor bar fault can cause unbalanced magnetic flux, and thus torque oscillation and stator current harmonics.
• Due to large output torque, and large rotor current, broken rotor bar fault is more common on large MV motors than small motors
• The effects of broken rotor end-ring are the same as broken rotor bar, in the sense that the rotor flux is asymmetric, and induces harmonics in the stator current.
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Broken Rotor Bar and End-Ring Faults
Existing methods: Signature current analysis EM torque harmonics monitoring Slot harmonic methods Starting current analysis Pattern recognition-based methods Artificial intelligence-based methods Other methods
Fundamentally: monitor the signature harmonics and slot harmonics in stator current
Broken Rotor Bar-related current harmonics
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Rotor eccentricity is a possible reason for many kinds of motor faults, such as stator insulation failure, broken rotor bar and end-ring, and even shaft crack.
Rotor Eccentricity
• Rotor eccentricity is mainly caused by shaft misalignment, when the geometric center of the rotor does not coincide with the center of the stator.
• The current harmonics related to rotor eccentricity are
Rotor Shaft Crack
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Rotor-related Faults
For MV motors, due to the high thermal stress on rotor, and the large output torque, especially the starting acceleration torque, rotor-related faults are quite common.
The fundamental methods for rotor-related faults are current signature analysis, as the signature frequencies related to broken rotor bar or eccentricity are well-known.
Challenges for MV motors Separating signature harmonics from load oscillation
– The signature harmonics in stator current are caused by the unbalanced rotor flux, but the same harmonics can also be caused by the load oscillation.
Diagnostics for drive-connected motors– the low-frequency harmonics can be cancelled or reduced by the controller.
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Conclusions
Motor faults diagnostics: Stator Inter-turn Fault
monitor the unbalance of stator winding
Bearing Faultmonitor the current harmonics caused by bearing-related torque vibration
Rotor Fault– Broken Rotor Bar/End-ring– Rotor Eccentricity
monitor the current signature harmonics caused by unbalanced rotor flux
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Conclusion of Motor Faults and their Diagnostics for MV Motors
Challenges for fault diagnostics of MV motors Compensate for the effect of power supply
and original motor unbalance Cancel the effect of load oscillation on
diagnostics Reliable diagnosis even with low SNR Fault diagnostics for drive-connected
systems Remote condition monitoring
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QUESTIONS?
