Chemical Engineering September 2020 - 36

Inlet
Pump
1
Q1 = 0.12 m3/s
P1 = 100 kPa
Inlet
2
D
4
N3 = 3,580 rpm
Electrical
driver
Figure 6. This diagram shows a pump/electricaldriver
system with volumetric flow (Q), suction
pressure (P) and rotational speed (N) as system
boundary conditions
which corresponds to higher adaptations
for the model parameters.
Moreover, the sensor data of the
evaluated timestamp, indicate that
the pump performance is deviating
(18% for efficiency and 5% for
head) from the nominal expected
behavior. Increasing deviation over
time can be an indication of performance
degradation.
Additional constraints can be
added to the system, by increasing
the number of available sensors
and the complexity of the pumping
system. This leads to a problem
closer to the scale of modern
pumping systems and data reconciliation
is proven an appropriate
method for reducing measurement
and model uncertainties.
Every timestamp is evaluated folmethodology,
lowing
the
above
Start of operation after major
maintenance action
Time
Train model with
healthy data
Predict failure
using trained model
Period in advance of failure
marked by model as
anomalous
Train healthy model from
operation data
2,200
2,100
2,000
1,900
1,800
1,700
1,600
1,500
700 800 900 1,000 1,100 1,200 1,300
Corrected flow, m3/h
2,200
2,100
2,000
1,900
1,800
1,700
1,600
1,500
700 800 900 1,000 1,100 1,200 1,300
Corrected flow, m3/h
Outlet
Table 2. siMulaTion paraMeTers for saMple puMp - elecTrical driver sysTeM
Variable
Q1
P1
I2
N3
Np3
Q4
P4
unit
3
m /s
kPa
A
rpm
kW
m3/s
kPa
Nominal
0.120
100
100.18
3,580
383.2
0.120
2,789
and this offers greater confidence
on the collected data set for analysis.
The analysis step will provide a
clear picture of the current and historical
operation of every pump and
the rest of the equipment. For every
component, the validated operating
conditions can be compared to the
nominal and preferred operation. Either
by using API or a vendor's recommended
zones, pump operation
will be evaluated. A visual comparison
between real operating data and
recommended operating regions is
shown in Figure 5.
Conclusions can be drawn concerning
the equipment's performance
and reliability status. Not only
performance, but also the pump's
reliability are influenced by deviating
from best efficiency point (BEP) flowrate,
for example through the damFirst
clear model indication
of anomalous operation
Stop of operation
after failure
Degradation
0.120
100
114.94
3,580
439.7
0.120
2,642
Type
Condition
Condition
Result
Condition
Result
Result
Result
aging effects of part load recirculation
[2]. The impact of historical operation
can be analyzed, providing insights
on operational improvements.
Identify abnormalities
04/03/17 00:00
Measurement
date
11/02/17 00:00
Figure 7. The sequence at the top shown how an unsupervised machine-learning anomaly-detection
algorithm works over time. The benchmark model is trained from healthy data (graph, lower left), which
can then be used to identify operational abnormalities (graph, lower right)
36
Performance and reliability
Greater financial value for the user
can be achieved when predictions
are made concerning the future
equipment operation. Performance
predictions can offer significant
insights about the system
capabilities. The user is able to
test different operational scenarios
and assess their impact. This can
improve the scheduling of future
operation and match demand with
supply requirements more accurately.
The proposed solution offers
performance predictions for
pump systems by leveraging the
derived customized equipment
characteristics, as described in the
previous paragraph. In combination
with the system topology and
specified boundary conditions,
the user shall trigger simulations
to derive the operating conditions
of individual components and of
the complete system. The simulation
process involves the complete
pump system calculation and the
final solution shall fulfill all physical
modeling equations.
As in the previous section, a simulation
example of a simplified pump/
electrical driver system is shown
in Figure 6 and the corresponding
results in Table 2. Comparison
results are provided by both using
the nominal pump-performance
characteristics and by applying the
degradation factors, as calculated
in the previous section. As expected
in comparison to nominal behavior,
the pump discharge pressure is decreased,
whereas the power conChemiCal
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3
Corrected head, m
Corrected head, m

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Chemical Engineering September 2020

Table of Contents for the Digital Edition of Chemical Engineering September 2020