Low cost on-line non-invasive sewer flow monitoring
Andy Nichols, Kirill Horoshenkov, Simon Tait, Simon Shepherd
and Yanmin Zhang
a.nichols2@bradford.ac.uk
Collaborators:
•
Open University
•
Cardiff University
•
Stanford University
•
Yorkshire Water Services
Funding:
•
Yorkshire Water Services
•
EPSRC grant EP/G015341/1
Andy Nichols | a.nichols2@brad.ac.uk
‘Traditional’ flow monitor (submerged acoustic Doppler)
Operates from within the flow.
Estimates flow depth and velocity
Main disadvantages:
• Permanent obstruction to the flow
• Accumulation of debris – maintenance requirements
• Backscatter approach – power requirements
Andy Nichols | a.nichols2@brad.ac.uk
Airborne Doppler flow monitor
Operates from above the flow
Estimates flow depth and velocity
Main advantages:
• Minimal obstruction to the flow
– only when surcharged
• Minimal accumulation of debris
– minimal maintenance
Main disadvantages:
• Backscatter approach
– power requirements
• Assumption of surface pattern
behaviour
•
•
•
•
The free surface pattern does not simply travel
along like a car on a motorway.
Features may appear, fluctuate, oscillate, merge,
separate, dissipate.
The vertical motion can cause a Doppler shift
comparable to that of the horizontal motion.
Above all, the behaviour is not understood, so
precisely what the device measures cannot be
defined.
BUT: Perhaps the surface fluctuation behaviour can be used….
Andy Nichols | a.nichols2@brad.ac.uk
Measuring temporal surface fluctuations at a point
– forward scatter
Wave probe
2
1
1. An ultrasonic beam is fired toward
the dynamic surface.
2. The signal is reflected to a receiver.
3. The phase of the received signal
fluctuates according to the surface.
Normalised Amplitude
3
Sent signal
signal
Sent
Received signal
signal
Received
11
0.5
0.5
0
-0.5
-0.5
-1
-1
00
3
0.1
0.1
0.2
0.3
0.4
0.5
0.6
Time (s)
0.7
0.8
0.8
0.9
0.9
11
-4
-4
-4
xx 10
10
Andy Nichols | a.nichols2@brad.ac.uk
Tracking surface fluctuations
•
Multiple receivers allow a
fluctuation time series to be
recorded from multiple known
locations on the free surface.
•
Time series from nearby
points can be quite different
(hence the issues with the
Doppler approach),
BUT similar enough to
estimate the temporal lag
(by cross-correlation), and
hence the surface velocity.
•
Depth (mm)
Time series
two distance
wave probes seperated by 30mm
2 wave series separated
by a from
small
75
74
73
114
115
116
117
118
119
Time (s)
120
121
122
123
124
Andy Nichols | a.nichols2@brad.ac.uk
Field prototype development
1
6
(Assume 𝑈 𝑈∞ = [0.2] )
Andy Nichols | a.nichols2@brad.ac.uk
0.4
0.2
0
0
0.2
0.4
0.6
Mean flow velocity, U (m/s)
0.2
0.4
h x Bed Slope, DS 0 (mm)
0
Surface characteristic period, L (mm)
RMS wave height, h
0.6
350
300
250
200
150
100
50
0
0
0.2
0.4
Depth x Bed Slope, DS 0 (mm)
0
0
Surface characteristic period, L (mm)
0.8
rms
(mm)
1
Surface characteristic period, L (mm)
But can we do more?
- Measuring the spatial evolution of the surface pattern
So we can measure advection velocity
between pairs of reflection points, and
300
can use a time-of-flight technique to
250
measure flow depth, and hence estimate
200
flow rate.
350
150
BUT
100
50
0
We can also cross correlate between
pairs of reflection points to obtain a
spatial correlation function
0
20
40
Roughness coefficient, k s (mm)
350
300
250
W ( )  e
  2 / 2 w2
cos(2L01  )
200
150
100
50
0
0
20
40
Roughness coefficient, k s (mm)
This describes the nature of the free
surface pattern and relates to the
underlying turbulence, which is governed
by the flow conditions, allowing a number
of empirical relationships to be drawn.
Andy Nichols | a.nichols2@brad.ac.uk
Conclusions
•
Forward scatter airborne acoustics allow unambiguous measurement of flow surface
behaviour.
•
Tracking the free surface pattern in this manner allows velocity estimation.
•
Time-of-flight measurements can provide depth data, in order to estimate flow rate.
•
Further information regarding the flow conditions is encoded in the free surface pattern.
Thank You
Low cost on-line non-invasive sewer flow monitoring
Andy Nichols, Kirill Horoshenkov, Simon Tait, Simon Shepherd
and Yanmin Zhang
a.nichols2@bradford.ac.uk