Measuring the flow velocity is an important task in the field of
environmental monitoring of water resources.
Such data are necessary
for the design and construction of hydraulic structures, for studying the
dynamics of water flow, mechanisms of erosion and sediment movement, analysis
of the ecological situation.
There
are numerous methods and technical means for studying the water flow structure based
on various physical principles, for example, acoustic Doppler profilometers ADCP,
designed to study the spatial and vertical currents’ structure [1], which can
be applied both in a stationary position and in the tow mode [2, 3], devices
using ultrasonic measurement technologies [4, 5], meters based on
electromagnetic induction [6] and others that are analyzed in detail in this
article [7]. The most common instruments
for rivers are those whose
operation is based on the registration of the number of turns of the blade
rotor - hydrometric turntables [8]. They make it possible to measure the speed
and direction of the current at different horizons. It is possible to distinguish
among
the express methods a method based on registering the speed of a floating body
using various floats [9], having the simplest technical implementation.
However, despite the variety of means for measuring the flow velocity, the
development of new methods and modification of the existing ones remains
relevant, which will allow avoiding some restrictions in their application, as
well as to obtain more information about the water flow dynamics.
Currently, it is becoming more and more relevant to study flows using
scientific visualization methods, one of which is the PIV method (Particle
Image Velocimetry). This method is widely used in many areas, such as the
automotive and aircraft industry, power engineering, in various scientific
problems, for example, when modeling the processes of gas flows on the surface
of solids [10], to measure the velocity in a selected flow section in hydro-
and aerodynamic experiments. [11, 12, 13], to study the dynamics of velocity
vector
fields and flow vorticity using the method of the smoke image velocimetry (SIV)
[14, 15, 16]. However, due to the complex technical implementation, in most
cases, its use is limited to laboratory conditions.
The main goal of the work is to show the capabilities of the measuring
instruments developed by the author based on the PIV method for studying the
water flow in natural conditions.
Measurement of the flow rate using the PIV method is based on the
analysis of the movement of particles located in the cross- section plane over
a fixed time interval.
Particle images are illuminated using a pulsed illumination system and
recorded on a digital camera.
Subsequent image processing makes it
possible to calculate the displacements of particles during the time between
the light source flashes and to construct a two-dimensional vector velocity
field [17].
Cross-correlation
of two consecutive images divided into fragments is used
to
determine the particle velocity. The cross-correlation function (1) is
calculated for each fragment, and its maximum is sought.
,
|
(1)
|
where
C(m, n)
– cross-correlation value for a pixel
(m, n);
I1
(i,
j)
– pixel
intensity
(i, j)
of the first image fragment;
I2'(i+m,
j+n)
– pixel
intensity
(i+m, j+n)
of the second image fragment;
The standard fast Fourier transform algorithm is used to calculate the
correlation function.
For the two images fragments that are
identical in coordinates, taken at a certain point at time
Δ
t, their frequency representations
are found using the fast Fourier transform. Next, a complex multiplication of
the transformation results is performed, after which the inverse Fourier
transform is performed. Then the maximum of the cross-correlation function is
found [18]. For a more accurate determination of the
maximum coordinates , the
standard Gaussian interpolation procedure for the main peak is used [19].
The direction is determined by the coordinates of the maximum relative to
the fragment center and the value of the displacement of the pixels D, and then,
knowing the time delay between frames
Δ
t, the speed of particles movement is calculated [20]:
,
|
(2)
|
where S is the scale factor for recalculating the speed in m/sec.
Technically, the classical scheme of the PIV method is implemented using
high-power pulsed lasers (1–10 MW) and synchronous video shooting of specially
used PIV cameras [21].
However, the implementation of such
schemes in natural conditions is difficult, and therefore the PIV method is mainly
used in laboratory conditions.
A
meter was specially developed
to study the dynamics of water flow
in natural conditions, consisting of a backlight device, a digital video
camera, attachment / positioning elements and data processing software. The scheme
and the photo are shown in Figure 1.
Figure 1 - Scheme and photo of the flow
velocity meter.
A sealed light source - 1 was used as backlight ,with 20 SMD 5730 LEDs
with a total power of 20W, providing a luminous flux of 2200 LM.
The
movement of particles in the flow was recorded using a digital camera YI4K +,
placed in a waterproof box - 2.
The main characteristics
are presented in Table 1 [22].
Table 1 - Main technical characteristics of a digital camera.
Chipset:
|
Ambarella H2 SOC
|
CPU:
|
Cortex-A53 ARM
|
Working temperature:
|
0 — 45 °Ñ
|
Battery life:
|
120
min
|
Matrix type:
|
CMOS
|
Sensor:
|
Sony IMX377
|
Number of matrix pixels:
|
12
megapixels
|
Physical size of the matrix:
|
1/2,3
|
4K video:
|
60 frames/sec
|
1080p video:
|
120
frames/sec
|
720p video:
|
240
frames/sec
|
Universal connector:
|
USB Type-C
|
Memory card support:
|
MicroSD, MicroSDHC
|
Camera mount:
|
1/4 screw
|
Battery Type:
|
removable,
1400 mA/h
|
The use of this camera is due to its compact size, high resolution and
maximum frame rate of 240 fps for this class of cameras.
The
standard lens was replaced with a specialized one with improved
characteristics, which are presented in Table 2 [23]. Its main advantage is
high resolution, minimization of optical distortion and the ability to obtain
the required focus distance in manual mode.
Table 2 - Specifications of the lens.
Focal
length
|
3,4
mm
|
A
perture
|
f/2,8
|
Optical
resolution
|
20
MP
|
Horizontal
shooting angle
|
90º
|
Lens
material
|
glass
|
Optical
distortion
|
without
distortion ≤ 0,5%
|
Number
of elements
|
8
|
Focusing
|
manual
|
Minimum
focus
distance
|
0 mm, focusing on the lens surface
|
BFL
|
3
mm
|
Filter
|
IR
|
A special blade - plate – 3 was used
for positioning in the
flow direction, which also served as a screen for obtaining more contrasting
images of particles (for this purpose, it was painted in a matte black color).
The technique for performing a full-scale
experiment was as follows: initially, the system was configured ,which included
focusing in a given area
(the size of the recorded area is 150x100 mm), setting the camera operation mode
(chose of shooting parameters: the resolution and frame rate), turning on the backlight
to work in continuous mode with maximum power . A calibration frame was also taken
for the subsequent determination of the scale factor S (2).
Then
the meter was immersed in water at a given horizon using a telescopic rod.
Three horizons were selected for work at each station: the surface, the midpoint
of the station depth, and the bottom area. Thanks to the use of a special plate
(Figure 1), which serves as a weather vane and a swivel located at the base of
the rod, the installation was turned in the direction of the flow, allowing
to
make video shooting in its longitudinal section.
The
physical principle of particles visualization in the developed meter is to
register the light scattered by them.
Special tracer particles
are
used in
the classical PIV method, however, the application of this
technology in the field is difficult and it requires a fairly long time to
prepare and perform each measurement, as well as a large number of consumables.
In accordance with this natural suspended particles already present in the
stream were used as tracers, which made it possible to significantly simplify
the technology of performing the experiment and reduce the cost
of
their implementation. As an example, Figure 2 shows a fragment of single frame
from the video data obtained using the created meter during the expedition
research at the mouth of the Chernaya
river, 2019.
Registration
was performed on the upper horizon in the near-surface area. The figure shows a
special element that is located on the plate for additional calibration during
subsequent analysis.
Figure 2 - An example of a frame of the received video image.
The video data obtained with the help of the developed complex were subjected
to software processing in several stages. At the first stage, preprocessing of
the video file was performed, which included gamma correction, adjustment of
contrast, image brightness, and performing binarization to obtain sharp images
of suspended particles in focus.
Figure 3 shows the result of processing the video frame
shown
above.
Figure 3 - The final frame after
preprocessing.
Then the video file was split into successive frames using the
application software.
The time interval between frames was
4 MS in accordance with the characteristics and settings of the equipment. As a
result, an array of images in * jpg format was formed. The next step was the
cross-correlation processing of pairs of sequential images, described above.
In order to increase
the accuracy of measurements, an
iterative procedure was used. Its essence was as follows: in the first
iteration, relatively large fragments were used to calculate the offset more
accurately (the larger the fragment, the better the signal-to-noise ratio and
the more stable the cross-correlation).
However, large fragments give low vector resolution. Therefore, in the
next iterations, a fragment was taken twice as small. The fragment displacement
information in the first pass was used to calculate the displacement in the
second iteration, and so on. This procedure provides high vector resolution and
a good signal-to-noise ratio, resulting in accurate measurements.
Fragments of 256 × 256 pixels in the first iteration and 128
× 128 pixels in the second iteration were used for processing the images
obtained in the course of the experiments.
As a result, instantaneous
flow velocity fields were constructed for each horizon. As an example, Figures
4–6 show images with the constructed instantaneous current velocity field for
three horizons (surface, middle and bottom layers) of station No. 8, section
No. 4, obtained in expeditionary studies at the mouth of the Chernaya river,
Sevastopol in 2019.
Research was carried out in the field
of mixing sea and river water, which is characterized by an unstable flow
structure. The highest velocity values were observed in the
surface layer. In addition, the flow periodically changed direction to the
opposite, which was recorded during measurements in the middle layer, Figure 5.
In addition, the current periodically changed direction to the opposite, which
was recorded when performing measurements in the middle layer, Figure 5.The
bottom layer is characterized by the presence of turbulent processes, which can
be visualized and described using the developed meter (Figure 6).
The bottom layer is characterized by the presence of turbulent processes,
which can be visualized and described
thanks to the use of the
developed meter (Figure 6).
Figure 4 - Constructed instantaneous current velocity field
in the surface layer.
Figure 5 - Constructed instantaneous flow velocity field in
the middle layer
Figure 6 - Constructed instantaneous field of current velocity
in the bottom layer.
Statistical averaging of the obtained fields makes it possible to obtain
the average value of the current velocity for each horizon, which is necessary
for solving various problems of environmental monitoring.
Figure 7 shows a histogram of the distribution of the average flow
velocity of the water flow for the bottom layer.
According to the results
of calculations, the average speed was 0.05 m/s.
Figure 7 - Histogram of the distribution of the average water
flow velocity.
To verify the data obtained, similar experiments were carried out in
parallel to determine the flow rate using the Condor biophysical complex (NPP
Aquastandard, TU 431230-006-00241904-2015; EAEU code 9027 50 000 0. Declaration
of conformity of the EAEU N RU D-RU.EM03.A.00096 / 19) [24, 25], which includes
a hydrometric spinner.
The research results using both methods are similar, the discrepancies do
not exceed 9%. This confirms the reliability and sufficiently high accuracy of
the data obtained.
Thus, the developed meter allows performing field experiments to
determine the flow velocity and obtain data on the dynamics of the water flow
with velocity amplitudes up to 2 m/s.
The use of standard
components in its composition makes it easier to maintain and operate. The
field tests
carried out as part of the expedition research at the
mouth of the Chernaya
river, Sevastopol, showed good
results.
Thanks to the use of modern visualization methods, the created meter has
a number of advantages over other instruments for studying flows.
In
particular, it
makes it possible to obtain
instantaneous and averaged distribution fields of the current velocity in a
wide spatial and temporal range, due to which it can be used to study complex
turbulent flows, processes of bottom sediment transfer, which in turn makes it
possible to obtain a more detailed understanding of the nature of the natural processes
and their peculiarities.
The work was carried out within the framework of the state assignment on
the topic No. 0827-2019-0004 "Comprehensive interdisciplinary studies of Oceanological
processes that determine the functioning and evolution of ecosystems in the
coastal zones of the Black and the Azov Seas."
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