CONDITION MONITORING
Figure 1, below, displays the extent of
vibration in motors. Figure 2a, immediate
left, is motor M3’s vibration spectrum.
Figure 2b, far left, is M2’s spectrum. Figure
3, inset, shows bearing raceway pitting
rail (such as London’s Docklands Light
Railway, pictured) to high-speed train
eets and freight. One example of a
light metro system demonstrates how
vibration monitoring can be used to
detect an early deterioration in motor
condition, enabling maintenance to be
planned. Although this example shows
a traction motor, the method has been
extended to the gearbox and axle box.
DATA COLLECTION SET-UP
A wheel lathe was used to rotate the
wheelset and vibration measurements
obtained from the traction motor
housing. The wheel tread diameter was
715mm and rotated at nominally 100m/
min, giving a wheel rotational speed of
44.5rpm (0.74Hz). The overall reduction
ratio of the gearbox was 6.745:1, giving a
motor speed of 300rpm (5Hz). The input
and output gear mesh frequencies were
125Hz and 52.54Hz respectively.
Vibration measurements obtained at
a rotational speed of 300rpm from the
NDE of the traction motor housing are
shown in Figure 1, below. This shows the
characteristic vibration parameter Dsel
(0-1kHz) obtained from eight traction
motors (M1-M8) on a train. Some of the
motors had completed around 530,000
miles. Notice how the traction motor M3
had signi cantly higher vibration levels
than the other motors.
To obtain a more accurate picture of
the motor condition, vibration analysis
was carried out to give a more detailed
diagnosis of what may have deteriorated.
Figure 2a, above, shows the vibration
spectrum obtained from motor M3,
which is dominated by vibration at
harmonics of 52.20Hz, which matches
closely with the calculated BPFO
(ball pass frequency outer
raceway) for the motor
cylindrical roller bearing
of 51.20Hz. A large
discrete peak is present
at the ninth harmonic of
BPFO (9fb/o = 470.33Hz),
with high amplitudes of
vibration present at the
seventh and eighth harmonic
of BPFO. In comparison to motor M3,
the vibration spectrum from motor M2,
Figure 2b, shows no signi cant vibration
related to the BPFO or any other defect
frequencies related to the cylindrical
roller bearing.
From this, it was concluded that some
major damage was present on the bearing
outer ring raceway of motor M3, and all
four motors (M1 to M4) were removed
from the train.
The higher vibration was associated
with a signi cant deterioration in bearing
condition; that was used to initiate a
replacement before a potentially serious
failure occurred in-service.
After the motors had been removed
from the bogie, the bearings were
examined for signs of wear and
deterioration (Figure 3, inset). Damage
was present around a 90º-arc of the outer
ring raceway, which took the form of
surface depressions which could be easily
felt with a ngernail. A further detailed
analysis of the damage showed the cause
to be electrical erosion.
Although some electrical erosion was
found on the outer ring raceway of the
bearing from motor M2, it was only visual
and had not penetrated the surface. No
signi cant surface deterioration had
occurred and continued operation would
have been possible.
CONCLUSION
The complexity and cost
of modern-day trains
means that condition
monitoring is now
becoming a much more
cost-e ective option.
Vibration monitoring is
still probably the most
widely-used predictive
maintenance technique and, with
few exceptions, can be applied to a wide
variety of equipment.
This example has demonstrated how
vibration measurements can be used
to e ectively assess the condition of
traction motors and identify faults before
they lead to catastrophic failure resulting
in high repair costs, service outage and
loss of reputation. This technique has
been successfully applied to traction
motors from light rail to high-speed trains.
Vibration monitoring allows
the condition of equipment to be
determined as it operates, and detects
those elements which start to show
signs of deterioration before they fail,
sometimes catastrophically. With this
type of approach, unplanned downtime is
reduced or eliminated, thereby increasing
availability and e ciency.
Depot-based condition monitoring
o ers the potential to detect equipment
faults and deterioration at an early stage,
enabling maintenance to be planned and
costs reduced. Optimum intervals for
scheduling can be achieved, resulting
in reduced costs and improved train
availability, as well as predicting early
failures enabling repairs to be planned.
64 www.operationsengineer.org.uk Winter 2021
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