3.4 Use of Flow Sensors
While pressure sensors are still cheaper than flow sensors, the price difference has
considerably lowered over the past years. For example, collecting flow data is now
possible via insertion sensors using through bore hydrants (which, however, typically have lower accuracy than the full bore electromagnetic flow sensors normally
used at a DMA inlet). Through the use of insertion sensors, the costs for excavation,
pipe cut-out, installation of valves, backfilling and pavement work and the potential
need to temporary decommission parts of the WDS can be avoided. Bearing this in
mind, flow and pressure sensors in WDS work differently. Flow measurements are
sensitive to all downstream changes, while pressure measurements are sensitive to
additional head loss on the flow route to them – thus generally more sensitive to
events local to the instrument, both up and down stream of the instrument. Flow data
is also generally via pulse counting systems providing an average value over a time
period (e.g. 15 min) generating smoothed data with good confidence, while pressure
data is generally an instantaneous value including noise and variability
[14, 90]. Therefore, using additional flow instrumentation should hypothetically
improve the performance of optimal sensor placement methods that only use additional pressure sensors. However, in the literature there has been less analysis of the
simultaneous optimisation of the locations of both pressure and flow sensors for
leak/burst event detection and localisation.
In the above context, worth of mention is the work by Imschoot et al. [91]. The
authors utilised an approach very similar to that presented in Farley et al. [30, 33] for
event detection and in Farley et al. [11, 34] for achieving selective sensitivity.
However, they incorporated data from not only pressure but also flow sensors to
detect and localise leaks/bursts. The authors populated two sensitivity matrices, one
for flow and one for pressure, used an absolute error rather than a chi-squared
formulation (as the latter is not applicable to simulated flow measurements that
could be null or negative) and considered a more conservative (than using an
uncertainty band) safety factor that simply shifts the threshold (the mean of the
values in each sensitivity matrix) used to binarise the matrices to a higher limit. They
then performed a complete enumeration search of these matrices using a fitness
function that aims at finding optimal solutions for the placement of one or two
additional sensors that results in similarly sized subdivided areas. The authors tested
their method on two UK DMAs assuming a perfect model and no measurements
uncertainty and found that (as a general tendency) placing optimal flow sensors plus
the inlet flow sensor seems to provide better results than the flow sensor at the DMA
inlet with optimally placed pressure sensors.
Findings similar to those reported by Imschoot et al. [91] have also been recently
presented in Raei et al. [92] whereby the authors observed that, despite the use of
pressure sensors having clear benefits in improving leak/burst detection rates, the
impact of pressure sensors in improving those rates diminishes quickly as the
number of flow sensors increases. Overall, these initial findings seem to suggest
that further development of sensor placement methods that attempt to
44
M. Romano
While pressure sensors are still cheaper than flow sensors, the price difference has
considerably lowered over the past years. For example, collecting flow data is now
possible via insertion sensors using through bore hydrants (which, however, typically have lower accuracy than the full bore electromagnetic flow sensors normally
used at a DMA inlet). Through the use of insertion sensors, the costs for excavation,
pipe cut-out, installation of valves, backfilling and pavement work and the potential
need to temporary decommission parts of the WDS can be avoided. Bearing this in
mind, flow and pressure sensors in WDS work differently. Flow measurements are
sensitive to all downstream changes, while pressure measurements are sensitive to
additional head loss on the flow route to them – thus generally more sensitive to
events local to the instrument, both up and down stream of the instrument. Flow data
is also generally via pulse counting systems providing an average value over a time
period (e.g. 15 min) generating smoothed data with good confidence, while pressure
data is generally an instantaneous value including noise and variability
[14, 90]. Therefore, using additional flow instrumentation should hypothetically
improve the performance of optimal sensor placement methods that only use additional pressure sensors. However, in the literature there has been less analysis of the
simultaneous optimisation of the locations of both pressure and flow sensors for
leak/burst event detection and localisation.
In the above context, worth of mention is the work by Imschoot et al. [91]. The
authors utilised an approach very similar to that presented in Farley et al. [30, 33] for
event detection and in Farley et al. [11, 34] for achieving selective sensitivity.
However, they incorporated data from not only pressure but also flow sensors to
detect and localise leaks/bursts. The authors populated two sensitivity matrices, one
for flow and one for pressure, used an absolute error rather than a chi-squared
formulation (as the latter is not applicable to simulated flow measurements that
could be null or negative) and considered a more conservative (than using an
uncertainty band) safety factor that simply shifts the threshold (the mean of the
values in each sensitivity matrix) used to binarise the matrices to a higher limit. They
then performed a complete enumeration search of these matrices using a fitness
function that aims at finding optimal solutions for the placement of one or two
additional sensors that results in similarly sized subdivided areas. The authors tested
their method on two UK DMAs assuming a perfect model and no measurements
uncertainty and found that (as a general tendency) placing optimal flow sensors plus
the inlet flow sensor seems to provide better results than the flow sensor at the DMA
inlet with optimally placed pressure sensors.
Findings similar to those reported by Imschoot et al. [91] have also been recently
presented in Raei et al. [92] whereby the authors observed that, despite the use of
pressure sensors having clear benefits in improving leak/burst detection rates, the
impact of pressure sensors in improving those rates diminishes quickly as the
number of flow sensors increases. Overall, these initial findings seem to suggest
that further development of sensor placement methods that attempt to
44
M. Romano