Download Condition Monitoring of Electrical Machines ABB MACHsense Solution

Condition Monitoring of Electrical
Machines
ABB MACHsense Solution
Overview
Typical failures in motor
Traditional condition monitoring methods
Shortfall
Solutions
ABB MACHsense service
© ABB Group
July 26, 2012 | Slide 2
Typical Problems in Electrical Machines
Rotating components
Cage rotor
defects
Deliverables
Bearing
problems
Installation
problems
15000
10000
5000
Voltage [V]
Power
supply
quality
0
0
0.02
0.04
0.06
-5000
-10000
-15000
Time [s]
© ABB Group
July 26, 2012 | Slide 3
0.08
0.1
0.12
Existing Condition Monitoring Systems
For Motor health assessment
Many plants
have In-house
condition
Monitoring
team
Vibration Analysis
(identifying mechanical condition like bearing, installation quality
etc)
Measures overall vibration
Time domain analysis & FFT
Specialized methods like demodulation, phase analysis etc
Motor Current Signature Analysis
(identifying rotor winding defect)
Uses Fast Fourier Transformation of Current spectrum
Either single phase or three phase
© ABB Group
July 26, 2012 | Slide 4
Rotor Damage
Significance
Percentage of failure less than 5%,
but…
Broken Rotor Bars can
Cause Sparking-Safety Hazard for Ex
motors
Healthy Bars carry more currentFurther damage
Torque & Speed Oscillation-Premature
failure of bearings
Centrifugal forces causes bars to lift
from slots-Hits stator windings to
cause serious damage
Customer Need:
To have advance intimation to prevent
catastrophic failure.
© ABB Group
July 26, 2012 | Slide 5
Present Day Condition Monitoring Methods
Rotor Bar Damage MCSA-Motor Current Signature
Analysis
FFT(Fast Fourier Transformation) of Current Signal
Identifies 2x slip frequency sideband in spectrum
Severity based on sideband height from center frequency
2x slip frequency
sidebands
© ABB Group
July 26, 2012 | Slide 6
Rule of Thumb: faults are detected
when these sidebands meet or
exceed -35dB (often referred to as
'35 dB down').
54-60 dB = Excellent
48-54 dB = Good
42-48 dB = Moderate
36-42 dB = Cracked rotor bars or
other source of high resistance.
30-36 dB = Multiple sources of high
resistance.
< 30 dB = Severe damage
Case using Traditional Methods : False Positive: Rotor
Bar Cracks
Motor Rating: 750 kW, 1490 rpm, 50 Hz, Application: Chipper, Plant: Pulp & Paper Mill
- 20 dB
Test Conditions:
Loading: 33.9%
Operating Slip:0.229 Hz
Operating freq: 49.194Hz
© ABB Group
July 26, 2012 | Slide 7
This is indicative of rotor bar cracks as per standard
analysis
The rotor was checked visually, with a dye penetrant
No crack or defect in the rotor bar was detected
Pulsating torque had resulted in observed sidebands
Case using Traditional Methods : False Negative: Rotor
bar Cracks
Motor Rating: 210 kW, 2982 rpm, 50 Hz Application: BFP, Plant: Chemical
Using the slip from
the nameplate
(MCSA) does not
indicate rotor bar
cracks
- 40 dB
- 57 dB
Test Conditions:
Loading: 76.7 %
Operating Slip:0.23 Hz (MCSA-nameplate slip
based)
Operating Slip: 0.27 Hz (Vibration)
Operating freq: 49.713 Hz
© ABB Group
July 26, 2012 | Slide 8
Slip from vibration indicative of rotor bar cracks as per standard
analysis
Using the slip from the nameplate does not indicate rotor bar
cracks
Cracks in the rotor were observed
What is Required ?
10
2
Automatic Slip &
1
Side Band
10
Identification
10
0
5 2 .3 9 9 6
10
10
10
-1
6 5 .2 3 7 1
-2
0.018
0.018
0.016
0.016
0.014
0.014
0.012
0.012
0.01
0.01
0.008
0.008
0.006
0.006
0.004
0.004
0.002
0.002
-3
0
45
48
4 8 .5
49
4 9 .5
50
5 0 .5
51
51.5
0
46
47
48
49
50
Hz
51
52
53
54
55
0
1
2
3
4
5
Hz
6
7
8
9
10
52
Normalization of
Load
Not to use Name
plate slip
information as
variation can be
upto 20% as per
IEC
© ABB Group
July 26, 2012 | Slide 9
•Reduced
Spectral Leakage using Adaptive Filtering
Processes
•Does Mathematical mapping to identify peak(correct
amplitude and frequency)
On Line condition Monitoring
ABB Offering
ABB MACHsense-P
Portable condition monitoring system used widely by all Local
service centers.
Measures vibration, current, voltage to identify health condition
of Motor from point of
Rotor Condition
Bearings
Installation
Power quality
Automated report generated by ABB Software
Engineer carries unit around plant to collect data-4 to 6 motors
a day
ABB MACHsense-R
Remote condition monitoring system, will be launched in April
‘12
Works with same technology and software as MACHsense-P.
Periodic and detailed report given as per service contract
Transfers data wireless to web portal which can be accessed
by customer through internet.
© ABB Group
July 26, 2012 | Slide 10
ABB MACHsense-P
Overview
•A
walk around
condition monitoring
service
POWER
SUPPLY
•Periodic
measurements
•Machine
in operating
condition
•Detection
of defects
and evolution over
the time by periodic
measurements
CAGE
ROTOR
•Preventive
maintenance plan
based on projected
time of defect
criticality (over a
period of 6 months)
ANTI-FRICTION
BEARING
© ABB Group
July 26, 2012 | Slide 11
INSTALLATION
Alignment, soft foot, air
gap
ABB MACHsense-P
Measurements
Measurement
Either 4 vibrations channels
or 6 electrical(3 current & 3
voltage) channels
simultaneously
High resolution data
collector for quick & high
speed data acquisition
© ABB Group
July 26, 2012 | Slide 12
Case Studies
Broken Rotor Bar
Client-Petrochemical
Motor-4.5MW, 4 Pole, 1500RPM, Sleeve bearings
Motor was driving compressor, having no stand by.
Highest amplitude 7.76mm/sec DE, Vertical direction
© ABB Group
July 26, 2012 | Slide 13
The Analysis
Automated Report
Current Spectrum
Traditional Method
After Normalizing
signal with respect
to load
© ABB Group
July 26, 2012 | Slide 14
Confirming Rotor winding damage
Verifying sources of Torque Oscillation
© ABB Group
July 26, 2012 | Slide 15
Cage Rotor Damage
Broken Short Circuiting Ring
• COG Plant
• 14900 KW
• Load-Compressor
August 11
September 11
© ABB Group
July 26, 2012 | Slide 16
Rotor Bar Damage
At low Load
Essar Steel Vizag
Cooler Fan-32
550KW
990 RPM
© ABB Group
July 26, 2012 | Slide 17
0
-20
Current [dB]
-40
-60
-80
-100
-120
-140
47
48
49
50
frequency [Hz]
© ABB Group
July 26, 2012 | Slide 18
51
52
53
Air Gap Eccentricity
The solution
Vibration
signals from
motor core
are a
measure of
electromagn
etic forces.
Unique
sensor
mounting
location to
pick up
electrical
related
signals from
vibration
© ABB Group
July 26, 2012 | Slide 19
.
Traditional methods vs ABB MACHsense-P
Advantage of using ABB MACHsense-P
2
10
1
10
0
10
52.3996
-1
10
65.2371
-2
10
-3
10
48
48. 5
49
49.5
50
50.5
51
© ABB Group
July 26, 2012 | Slide 20
51. 5
52
Traditional methods (MCSA)
Cannot differentiate torque
oscillation of rotor bar damage from
that of load (compressor, crusher
etc) or power supply
Common norms used to confirm
severity of defect irrespective of
load
Uses name plate slip
Mechanical faults not identified or
identified at later stage after fault
initiation.
Does not consider rotor design and
construction of motor (cannot
accurately determine the severity of
the fault or even identify the defect)
ABB MACHsense-P
Simultaneous measurement of
current and voltage makes it
possible to confirm and distinguish
reason of torque oscillation
Normalizes data according to load to
confirm defect of rotor bar , air gap
eccentricity etc.
Automated slip detection
Vibration data gives mechanical
condition and confirms findings of
MCSA
ABB consider rotor design and
construction of motor which give an
unique index to estimate the fault
severity.
Number of rotor bar, speed etc.
Other Faults
Uses traditional Vibration analysis methods
Mechanical Problemso Unbalance
o Misalignment
o Loosensess
Installation-Soft foot
Shaft Eccentricity
Unbalanced electromagnetic pull, mechanical problems
can lead to bearing damage.
Customer Need:
To identify presence of such problems to plan maintenance action.
© ABB Group
July 26, 2012 | Slide 21
Unbalance-Spectrum
Traditional Analysis methods
© ABB Group
July 26, 2012 | Slide 22
Signature
What is the problem here?
© ABB Group
July 26, 2012 | Slide 23
What is required?
PRINCIPLE COMPONENT ANALYSIS
Vibration
data
IS O - R MS
ISO standards
G et S PEED
G et H AR MO NICS
H arm onic RM S to
Total Harm . Distortion
Other fault:
non -synchronou s
Principal
Components
Classification
Fa ult classification
+
Severity
Model Based Analysis
ABB MACHsense Solution
© ABB Group
July 26, 2012 | Slide 25
Principal Component Analysis
Torque Oscillation
COG Plant
Recirculation Pump
370 KW
© ABB Group
July 26, 2012 | Slide 26
Eccentric Rotor
Workshop-Taloja
Motor-2040KW, 3000RPM, Sleeve Bearing
Client reported high vibration in motor
Measurements made in Taloja Service Center
Decoupled condition
Overall vibration 4.85mm/sec DE H, 10.5mm/sec NDE H
© ABB Group
July 26, 2012 | Slide 27
Phase Measurement
Motor No Load, Decoupled state
Magnitude 1X
2X
3X
4X
Phase
1X
2X
3X
Channel 1
0.011462 0.000356 0.000881 0.001477 Channel 1
-116.638 42.91414 141.1764 35.86918
Channel 2
0.003896 0.002198
-12.3934 35.60742 144.8034
-25.6252
Channel 3
0.013151 0.008774 0.000652 0.001888 Channel 3
35.63641 156.9605
-159.302
Channel 4
0.012856 0.000357 0.000986 0.001642 Channel 4
54.55921 11.70966
0.00149
0.00082 Channel 2
Recommendations:
Concentricity of bearing with respect to housing.
Run out of rotor.
Unbalance in rotor
Concentricity of Stator with respect to core.
Findings:
Run out of rotor up to 0.8mm.
Bearing Changed.
Rotor Balanced
Present Vibration 2.7mm/sec.
© ABB Group
July 26, 2012 | Slide 28
4X
-74.4833
98.6241 24.32922
Rolling Element Bearing
Causes of Bearing Failure
Lubrication
High Vibration-Misalignment, Unbalance.
Installation Faults
Soft Foot
Air Gap eccentricity
© ABB Group
July 26, 2012 | Slide 29
Sensitivity of different methods to detect bearing
faults
Failure
Early detection
Severity of
the fault
Smoke**
Change in bearing
temperature**
Significant change in high frequency
RMS value**
Significant change in crest
factor**
ABB BeAM®
A spall has been
developed
Lubricant debris
monitoring*
ABB BeaCon automatic
autocorrelation timedomain
Off-line envelope method and an
experienced analyser*
•Commonly used methods for bearing faults analysis
** Non-specific methods
© ABB Group
July 26, 2012 | Slide 30
Time
Off-line envelope method and an
inexperienced analyser*
Bearings Vibration Analysis : BeAM®
ABB Approach
Common analysis methods use for the
envelope method for bearing fault
detection
The envelop method uses the
envelope of high frequency signals
generated by defects and compares it
to bearing defect frequencies.
0.4
0.3
0.2
0.1
0
-0.1
-0.2
-0.3
-0.4
0.56
© ABB Group
July 26, 2012 | Slide 31
0.565
0.57
0.575
0.58
0.585
0.59
The ABB BeaCon automatic analysis
uses:
the auto-correlation time-domain
method to filter out the noisy signals
more effectively that traditional
method
Bearings Vibration Analysis : BeAM®
Data sequences that
contain only noise
3
2
Unfiltered
vibration signal.
1
0
-1
-2
-3
0
10
20
30
40
Time [ms]
50
60
70
80
3
2
Above signal after
proper filtering.
1
0
-1
-2
-3
0
10
20
30
40
Time [ms]
50
60
Data sequences that
contain shock pulse + noise
© ABB Group
July 26, 2012 | Slide 32
70
80
The ABB BeAM® in addition to the ABB
BeaCon automatic autocorrelation timedomain analysis:
Perform early shock pulse detector
analysis which only extract the
shock pulses related to bearing
defects using special signal
processing methods such as
adaptive filtering and likelihood
ratios to improve the signal
sensitivity.
Estimates the following parameters
to evaluate the condition of the
bearing:
Kurtosis , high frequency
RMS, maximum energy per
shock pulse & integrated
energy calculations
ABB Condition Monitoring
Case study - Bearings
Vibration measurement were taken for two identical Boiler Feed Pump
motors. Both measurements were taken for 50 % of machine load.
Nameplate details:
Power
Voltage
Current
Speed
Frequency
Poles
2000 kW
6.6 kV
204 A
1487 rpm
50 Hz
4
Overall vibration readings in Motor BFP 3C, serial number: 3991201-1
Velocity: 1.02 mm/s
Acceleration: 0.46 g
Overall vibration readings in motor BFP 3B,Serial Number: 3991201-2
Velocity: 1.3 mm/s
Acceleration: 1.36 g
© ABB Group
July 26, 2012 | Slide 33
ABB condition monitoring
Case studies – Bearings: Early Warning
•
•
•
•
© ABB Group
July 26, 2012 | Slide 34
Machine BFP 3C
Bearing OK
Suggested action:
• action category: preferred
• next measurement: in six months
Machine BFP 3B
Bearing faulty
Suggested action:
• action category: mandatory
• change bearing as soon as possible
but not later than 3 months
ABB Condition Monitoring
Case study – Bearing related energy trend (early warning
detection)
Energy related to
bearing for faulty case
Energy related to
bearing for healthy case
Warning Level
Possibility of comparing the
spectra for each measurement
Vibration signal
in time domain
Vibration signal
after filtration
Bearing related
quantities
© ABB Group
July 26, 2012 | Slide 35
Traditional methods vs ABB MACHsense-P
Advantage of using ABB MACHsense-P
0. 3
Vibration [ g's]
0.2 5
0. 2
0.1 5
0. 1
0.0 5
0
0
50
10 0
1 50
200
25 0
30 0
350
frequ ency [Hz ]
© ABB Group
July 26, 2012 | Slide 36
400
4 50
5 00
Traditional MethodsVibration Analysis
Multi channel data
acquisition but with max
frequency range of 16Khz.
No access to electrical
problems with traditional
way of data collection i.e
from bearing housing
Custom made tools
available for monitoring
bearing condition.
No automated analysis
especially for motors
ABB MACHsense-PVibration analysis
4 channel simultaneous
data collection with
frequency range of 20Khz.
Uses unique sensor
mounting methods to pick
electrical signals i.e from
motor body
Powerful algorithms
identifies bearing damage
at an early stage
Automated report for all
electrical motors
ABB Approach
Combined Vibration & Electrical Data
Single software for vibration and electrical data input
Vibration
Key
Condition
Parameters
Stator
Current
Stator
Voltage
© ABB Group
July 26, 2012 | Slide 37
Automated report
Patented processes for defect detection
used in analysis software
Automated analysis includes slip
estimation, normalization of load effects
and accounts for constructional aspects
Traditional methods vs ABB MACHsense-P
Vibration and electrical
Traditional Methods
© ABB Group
July 26, 2012 | Slide 38
ABB MACHsense-P
Measures vibration and
Measures vibration and
electrical data with individual
electrical data with same
instrument
instrument
Separate software analyzes
Same software gets input of
vibration and electrical data
vibration and electrical data
No correlation in analysis
Correlates data like slip
Common mode of analysis
Unique algorithms
for different electrical type of
developed for different
electrical machines
machines-DOL, VFD, SM
Manual report generation
Automated report
ABB MACHsense-P
The Levels
Deliverables
Cage rotor
package:
Rotor bar defect
Eccentricity
Shaft bow
Internal
misalignment
Bearing Package
Bearing defects
Assembly
defects
Lubrication
issues
Sleeve bearings
Installation
Unbalance
Looseness
Misalignment
Soft foot
Power supply
quality
Voltage
unbalance
Harmonics
© ABB Group
July 26, 2012 | Slide 39
Standard
Advanced
Regular condition
monitoring
Trouble shooting to assess
root cause.
Measurements made at
nominal operating condition
and load
Measurements at nominal
condition and at different
load/speeds.
About 6-8 motors can be
analyzed in a day.
Root cause analysis &
standard deliverables.
Charges can be on a per
machine basis
One or two motors are
analyzed in a day.
Report with standard
deliverables.
Per day charges applicable
Advantages of ABB MACHsense-P
Clear Customer benefits
Combined automated analysis of Current, voltage and vibration
A One Stop
Shop for
Motor health
assessment
Overcomes False Positive and False Negatives involved in
traditional methods
Automated summary status report issued on site
Patented algorithms applicable to each motor type
Application specific preventive maintenance plan with final
detailed report
Can be applicable to any make and size of motor
Early warning provides enough time for corrective action
© ABB Group
July 26, 2012 | Slide 40