Design and production of a measurement device; which measures temperature, pressure and flow rate inside of an air conditioning unit.

1. 1
TABLE
OF
CONTENTS
TABLE
OF
CONTENTS
.......................................................................................................
1
1.
OBJECTIVE
.........................................................................................................................
2
2.
INTRODUCTION
.............................................................................................................
3
3.
EXPERIMENTAL
SETUP
.............................................................................................
4
4.
INSTRUMENTS
...............................................................................................................
7
4.1
Arduino
Uno
R3
...........................................................................................
7
4.2
QRD1114
Reflective
Object
Sensor……….…………………………..
8
4.3
BMP180
Pressure
Sensor….……………………………………………….
9
4.4
LM35
Temperature
Sensor…………………………………………………
10
5.
DESIGN
...............................................................................................................................
11
6.
CODES………………………………………………………………………………………………
12
6.1
Code
for
BMP180
pressure
Sensor
……………………………………
12
6.2
Code
for
LM35
Temperature
Sensor
…………………………………
13
6.3
Code
for
QRD1114
Reflective
Object
Sensor.…………………….
14
7.
CALIBRATION
..................................................................................................................
15
7.1
Calibration
of
LM35
Temperature
Sensor
…………………………
16
7.2
Calibration
of
BMP180
Pressure
Sensor
……………………………
17
7.3
Calibration
of
QRD1114
Reflective
Object
Sensor.…………….
18
8.
PROCEDURE
.....................................................................................................................
19
9.
ACCURACY
ANALYSIS
..................................................................................................
19
10.
CONCLUSION
.................................................................................................................
21
11.
REFERENCES
.................................................................................................................
22

2. 2
1. OBJECTIVE
The
main
objective
of
this
experiment
is
to
measure
the
temperature,
pressure,
velocity
and
mass
flow
rate
of
the
air
in
an
air
conditioning
unit.
To
do
this,
the
measurement
sensors
that
recognize
the
changes
in
system
and
provide
output
are
used.
The
other
aim
is
to
analyze
the
measured
data
in
terms
of
averages,
minimums
and
maximums,
etc.
Lastly
it
is
purposed
that
the
uncertainty
analysis.

3. 3
2. INTRODUCTION
For
this
project,
different
sensors
are
used
for
temperature,
flow
rate
and
pressure
measurements.
QRD1114
reflective
object
sensor
is
used
to
measure
the
flow
rate.
By
using
this
sensor,
rotation
number
of
the
propeller
in
an
air
conditioning
unit
is
measured
and
converted
in
to
mass
flow
rate
by
the
formulas
in
the
code.
To
make
the
propeller
reflective
the
propeller
is
painted
in
to
white.
The
other
sensor
used
to
measure
temperature
is
LM35
precision
centigrade
temperature
sensor.
The
sensor
gives
voltage
output,
which
is
linearly
proportional
to
the
temperature
in
centigrade.
The
pressure
sensor
that
is
chosen
as
BMP180
and
the
signal
is
received
as
a
function
of
pressure
to
sensor.
The
sensor
measures
the
barometric
pressure.
By
using
these
sensors,
the
temperature,
pressure
and
flow
rate
are
measured
for
the
project.

4. 4
3. EXPERIMENTAL
SETUP
Three
type
of
sensors
are
used
in
this
experiment
LM35
Temperature
Sensor,
BMP180
Pressure
Sensor
&
QRD1114
Reflective
Sensor.
Their
wiring
diagrams
of
these
sensors
are
drawn
in
fritzing
software
and
shown
below.
(Fig.1-­‐2-­‐3)
Fig.1
Wiring
diagram
of
LM35
Two
LM35
are
used
in
this
system
in
order
to
measure
the
temperature
difference
between
the
back
and
front
side
of
serpenter
in
the
air
conditioner
unit.
Lm35
has
three
legs,
which
are
connected
to
5V,
Ground,
A0
&
A1
(two
sensors,
two
outputs).

5. 5
Fig.2
Wiring
diagram
of
QRD1114
QRD1114
reflective
sensor
is
used
in
this
system
in
order
to
measure
the
velocity
and
the
mass
flow
rate
of
air
in
the
system.
This
sensor
uses
5v
input.
It
has
4
legs
and
these
legs
are
connected
to
5V,
Ground,
A0
&
A1
pins
on
the
arduino.

6. 6
Fig.3
Wiring
diagram
of
BMP180
BMP180
digital
pressure
sensor
is
used
in
this
system
in
order
to
measure
the
pressure
in
front
of
the
fan.
This
sensor
uses
5v
input.
It
has
4
holes,
which
are
connected
to
5V,
Ground,
A4,
&
A5
pins
on
the
arduino.

7. 7
4. INSTRUMENTS
1. Arduino
UNO
R3
2. Breadboards
(x
2)
3. Jumper
Wires
4. QRD1114
5. BMP180
Pressure
Sensor
6. LM35
Temperature
Sensor
(x
2)
7. A
propeller
with
12
cm
diameter
8. Resistors
(200
Ohm
5.6
kOhm)
1. Arduino
UNO
R3:
Arduino
Uno
R3
is
a
board
which
is
micro
controlled
by
ATmega328.
Arduino
UNO
has
6
analog
output,
14
digital
input
and
output
pins.
Moreover,
for
the
connection
it
has
a
power
jack
and
a
USB
connection.
It
has
a
32
KB
flash
memory,
ICSP
header,
and
a
reset
button.
It
is
really
easy
to
use,
everything
is
ready
to
use
so
to
get
started
you
only
need
to
connect
it
to
a
computer
with
a
USB
cable
or
you
can
use
a
battery
or
an
adapter
to
power
it.
Arduino
Uno
R3
is
the
latest
product
of
the
arduino
series,
which
is
faster
than
the
previous
versions.
Fig.4
Arduino
Uno
R3

8. 8
2. QRD1114
Reflective
Object
Sensor
QRD1114
is
a
device
that
consists
of
an
IR
Emitter
and
a
phototransistor.
It
has
a
sensing
distance
up
to
3cm.
The
phototransistor
responds
to
radiation
emitted
from
the
diode
when
a
reflective
object
passes
by
in
front
of
the
detector.
In
order
to
create
a
reflective
surface,
the
propeller
is
painted
into
white
color.
Moreover,
this
sensor
has
a
daylight
filter
so
it
distinguishes
the
reflected
light.
Fig.5
QRD1114
reflective
object
sensor
This
sensor
is
used
to
measure
the
wind
speed
in
the
air
conditioner
unit.
When
the
propeller
passes
in
front
of
this
sensor,
the
sensor
gives
a
voltage
output.
This
voltage
output
is
converted
in
to
RPM
by
using
the
formula
written
in
the
code.

9. 9
3. BMP180
Pressure
Sensor
BMP180
is
a
digital
pressure
sensor
based
on
piezoresistive
technology.
It
measures
temperature
and
barometric
pressure.
Moreover
it
consists
of
3.3V
regulator,
pull-­‐up
resistors
and
I2C
level
shifter.
This
sensor
measures
pressure
values
between
the
range
of
30000
to
110000
Pa.
It
has
a
pressure
accuracy
of
+-­‐
200
Pa.
Also,
it
has
a
temperature
range
of
-­‐40
to
+85°C
and
temperature
accuracy
of
+-­‐2°C
.
This
device
could
be
used
as
a
temperature
sensor
in
the
system
but
LM35
is
preferred
due
to
its
better
accuracy
which
is
+-­‐0.5
°C.
Fig.6
BMP180
Pressure
sensor

10. 10
4. LM35
Temperature
Sensor
LM35
is
a
temperature
sensor,
which
gives
voltage
output
that
is
linearly
proportional
to
the
temperature
in
Centigrade.
(Better
than
sensors
calibrated
in
Kelvin)
It
has
an
operating
range
of
−55°C
to
+150°C
and
accuracy
of
±0.5°C
(at
25°C)
Fig.7
LM35
temperature
sensor
and
the
functions
of
its
legs.
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have been corrupted. Restart your computer, and then open the file again. If the red x still appears, you may have to
delete the image and then insert it again.

11. 11
9. DESIGN
The
design
and
the
size
specification
of
the
system
can
be
seen
below.
(Fig.9-­‐
10)
Fig.8
3D
modeling
of
the
design
Fig.9
2D
Technical
drawing
of
the
design

12. 12
10. CODES
1. Code
for
BMP180
pressure
sensor
#include
"Wire.h"
#include
"Adafruit_BMP085.h"
Adafruit_BMP085
mySensor;
float
maxi=0;
float
mini=999999999;
float
avgp=0;
//sets
the
initial
average
to
0
float
tempC;
float
pressure;
float
i=0;
//sets
the
counter
value
to
0
void
setup(){
Serial.begin(9600);
mySensor.begin();
}
void
loop()
{
pressure=mySensor.readPressure();
if(pressure
>
maxi)
{maxi
=
pressure;}
//
set
max
temperature
if(pressure
<
mini)
{mini
=
pressure;}
//
set
min
temperature
if(pressure
>16.0)
;
i=i+1;
avgp=avgp+pressure;
//adds
the
new
pressure
into
the
average
Serial.println("t");
Serial.print("Average
Pressure:
");
Serial.print(avgp/i);
Serial.print("t");
Serial.print("Max
Pressure:
");
//prints
max,min,
average
pressure
Serial.print(maxi);
Serial.print("t");
Serial.print("t");
Serial.print("Min
Pressure:
");
Serial.print(mini);
Serial.print("t");
Serial.println("t");
delay(800);
//the
outputs
are
shown
with
a
delay
}

13. 13
2. Code
for
LM35
temperature
sensor
float
maxi=0,mini=100;
//sets
the
initial
maximum
and
minimum
float
i=0;
//sets
the
counter
value
to
0
float
avgt=0;
//sets
the
initial
average
to
0
void
setup()
{
Serial.begin(9600);
}
void
loop()
{
int
rawvoltage=
analogRead(A1);
//gets
the
voltage
output
from
A1
float
millivolts=
(rawvoltage/1024.0)
*
5000;
//converts
the
output
into
milivolts
float
T1=
(millivolts/10)-­‐0.45;
//converts
the
millivolts
into
celcius
int
rawvoltage2=
analogRead(A2);
float
millivolts2=
(rawvoltage2/1024.0)
*
5000;
float
T2=
(millivolts2/10)+1.51;
i=i+1;
avgt=avgt+T1-­‐T2;
//adds
the
new
temp.
difference
into
the
average
if(abs(T1-­‐T2)
>
maxi)
{maxi
=
T1-­‐T2;}
//
sets
max.
temp.
difference
if(abs(T1-­‐T2)
<
mini)
{mini
=
T1-­‐T2;}
//
sets
min.
temp.
difference
if(abs(T1-­‐T2)
>16.0)
Serial.println("t");
Serial.print("T1:
");
Serial.print(T1);
Serial.print("t");
Serial.print("T2:
");
Serial.print(T2);
Serial.print("t");
Serial.print("T1-­‐T2:
");
Serial.print(abs(T1-­‐T2));
//prints
max,min,
average
temp.
difference
Serial.print("t");
Serial.print("MAX:
");
Serial.print(abs(maxi));
Serial.print("t");
Serial.print("MIN:
");
Serial.print(abs(mini));
Serial.print("t");
Serial.print("AVG:
");
Serial.print(avgt/i);
//devides
the
sum
to
number
of
data
Serial.println("t");
delay(500);
//the
outputs
are
shown
with
a
delay
}

14. 14
3. Code
for
QRD1114
reflective
object
sensor
float
avgf=0;
//sets
the
initial
flowrate
average
to
0
float
i=0;
//sets
the
counter
value
to
0
float
avgrpm=0;
//sets
the
initial
rpm
average
to
0
float
maxiFlow=0;
float
miniFlow=999999999;
//sets
the
initial
maximum
and
minimum
flowrate
void
setup()
{
Serial.begin(9600);
}
void
loop()
{
float
rpm=((30*1000)/(1000000/pulseIn(A0,LOW,100000000)));
//converts
the
voltage
output
in
to
rpm
float
velocity;
velocity=-­‐0.0655*rpm+8.2929;
//converts
the
rpm
into
velocity
float
flowrate;
flowrate=1.184*(velocity*0.290*0.290);
//converts
the
velocity
in
to
flowrate
i=i+1;
avgrpm=avgrpm+rpm;
//adds
the
new
rpm
and
flowrate
data
into
average
avgf=avgf+flowrate;
if(abs(flowrate)
>
maxiFlow)
{maxiFlow
=
flowrate;}
//
sets
max
if(abs(flowrate)
<
miniFlow)
{miniFlow
=
flowrate;}
//
sets
min
if(abs(flowrate)
>0)
;
Serial.println("t");
Serial.print("
Velocity(m/s)
:
");
Serial.print(velocity,4);
Serial.print("t");
Serial.print("
Flowrate(m3/s)
:
");
Serial.print(flowrate,4);
Serial.print("t");
Serial.print("
AVG
Flowrate
:
");
//prints
max,min,
average
flowrate
and
velocity
Serial.print(avgf/i,4);
Serial.print("t");
Serial.print("
MAX
Flowrate
:
");
Serial.print(maxiFlow,4);
Serial.print("t");
Serial.print("
MIN
Flowrate
:
");
Serial.print(miniFlow,4);
Serial.println("t");
delay(800);
//the
outputs
are
shown
with
a
delay
}

15. 15
11. CALIBRATION:
At
first
the
sensors
weren’t
giving
the
desired
results
so
these
sensors
are
calibrated
in
different
ways.
1. Calibration
of
LM35
temperature
sensor
In
order
to
calibrate
these
sensors
we
used
a
kettle
device
which
we
know
that
it
shuts
itself
off
at
100
°C.
The
sensors
put
in
the
hot
water
with
a
thin
plastic
bag
incase
of
the
water
damage
the
sensor.
When
the
kettle
blinks
and
shuts
itself
off,
the
output
temperature
value
is
investigated
if
it
shows
100
°C
or
not.
One
of
the
LM35
was
showing
98.45
°C
while
the
other
was
97.10
°C.
To
calibrate
these
values
the
conversion
formulas
are
edited
with
the
necessary
operations
(sum,
extraction).
The
measurements
are
checked
again
after
the
calibration
and
the
sensors
started
to
Show
the
same
value
with
a
+-­‐0.5
°C
uncertainty.
Fig.10
Calibration
of
LM35

16. 16
2. Calibration
of
BMP180
pressure
sensor:
In
order
to
calibrate
BMP180
pressure
sensor,
first
the
current
altitude
is
learned
by
the
Internet.
After
that
the
atmospheric
pressure
for
this
altitude
is
learned.
Our
device
is
turned
on
and
the
measurements
are
compared
with
that
atmospheric
pressure
value.
Calibration
is
finished
by
applying
the
necessary
operations
on
the
conversation
formulas
in
the
code.
Fig.11
Atmospheric
pressure
at
Yeditepe
University

17. 17
3. Calibration
of
QRD1114
reflective
sensor
In
order
to
calibrate
QRD1114
and
obtain
the
rpm
to
velocity
formula.
It
is
put
in
a
wind
tunnel
device.
In
this
wind
tunnel,
a
pressure
difference
sensor,
which
helps
us
to
calculate
the
actual
air
velocity
in
the
tunnel,
is
placed
also.
The
wind
tunnel
is
turned
on
for
different
frequency
values.
The
velocity
calculated
by
the
pressure
difference
sensor
and
the
rpm
value
shown
by
our
device
are
saved
in
to
an
excel
file.
The
data
are
plotted
and
curve
fitting
is
applied
to
obtain
an
equation.
The
equation
is
found
as
“Velocity=-­‐0.0653*RPM+8.2886”.
The
equation
is
put
into
the
code
and
velocity
values
are
started
to
calculate
by
the
rpm
values.
Fig.12
Calibration
of
QRD1114
in
a
wind
tunnel

18. 18
12. PROCEDURE
1. Connect
the
sensors
to
the
required
5V,
Ground
and
the
analog
output
pins.
2. Power
the
device
with
the
computer
by
using
the
USB
output
of
the
arduino.
3. Put
the
device
in
front
of
the
fan
and
put
the
LM35
cables
back
and
front
of
the
serpenter.
4. Upload
the
code
to
the
device.
5. Turn
on
the
air
conditioning
unit.
6. Apply
different
magnitudes
of
frequencies
in
order
to
observe
the
changes
in
flow
rate,
pressure
and
temperature.

19. 19
7. ACCURACY
ANALYSIS
Standard
deviation
formula:
!
!
(𝑥!
!
!!! − (𝑀𝑒𝑎𝑛))
Uncertainty
formula:
!
!
(𝑥!
!
!!! − (𝑀𝑒𝑎𝑛))
1. Velocity
Calculations:
The
experiment
was
done
at
8.27535255
m/s.
46
data
is
taken
and
calculated
average,
max
min
velocities,
and
it’s
differences
also
standard
deviation
Velocity
Average
Velocity
Max
value
Velocity
Min
value
Max
difference
Minimum
difference
St
deviation
8.27535255
8.27666255
8.27404255
0.00131
0.00131
0.000567247
If
the
standard
deviation
is
divided
by
square
root
of
number
of
data,
it
is
equal
to
8.364x10-­‐5
and
for
our
device
the
velocity
is
equal
to
8.27535255±8.364x10-­‐5
Fig.
13
Velocity
vs.
data
If
we
think
about
Reynolds
number:
𝑅𝑒 =
𝜌𝑑𝑣
𝜇
The
uncertainty
of
the
Reynolds
number
can
be
expressed
as;
∆𝑅𝑒 = (
𝜕𝑅𝑒
𝜕𝜌
∆𝜌)! + (
𝜕𝑅𝑒
𝜕𝑣
∆𝑣)! + (
𝜕𝑅𝑒
𝜕𝑑
∆𝑑)! + (
𝜕𝑅𝑒
𝜕𝜇
∆𝜇)!
y
=
-­‐7E-­‐06x
+
8.2755
8.2735
8.274
8.2745
8.275
8.2755
8.276
8.2765
8.277
0
10
20
30
40
50
Velocity
vs
Data
Velocity
vs
Data
Linear
(Velocity
vs
Data)

20. 20
ρ(
kg/m3
)
v(m/s)
D(m)
μ
(kg/s.m)
1.205±0.008%
8.27535255±8.364x10-­‐
5
0.29±0.0005
1.822x10-­‐5
±0.05%
We
found
Reynolds
number
as
177774
and
its
uncertainty
as
4996
so
we
can
express
Reynolds
number
as
177774±4996.
2. Temperature
Uncertainty
The
experiment
was
done
at
22.5
°C.
49
data
is
taken
and
calculated
average,
max,
min
temperatures,
and
standard
deviation.
TRUE
Temp
Value
Our
Temp
Value(C)
Temp
max
Temp
min
St.
Deviation
22.5
22.28
22.5
22.01
0.243721152
If
the
standard
deviation
is
divided
by
square
root
of
number
of
data,
it
is
equal
to
3.481x10-­‐2
and
for
our
device
the
temperature
can
be
expressed
as
22.28±3.481x10-­‐2

21. 21
8. CONCLUSION:
To
sum
up,
in
our
design
project
our
aims
were,
measuring
the
flow
rate,
measuring
the
pressure
and
measuring
the
temperature
difference
between
two
stage
of
the
air
condition
unit.
When
we
started
to
design
it,
firstly
we
get
a
data
acquisition
card
and
some
temperatures
and
pressure
sensors,
also
after
a
while
we
decided
to
use
an
optical
detector
to
get
rpm
values.
When
we
finished
our
design
we
covered
it
with
a
box
to
avoid
cable
mess.
Moreover,
we
calibrated
all
of
the
sensors
and
made
the
sensors
working
properly.
After
using
this
device,
we
have
observed
that
the
system
is
working
properly
and
we
can
say
that
this
device
can
be
used
at
heat
and
ventilating
systems
with
good
accuracy
and
precision.

22. 22
9. REFERENCES
1. http://maelabs.ucsd.edu/mae171/watdocs/Reynolds%20experiment.ht
m
2. https://www.wmo.int/pages/prog/gcos/documents/gruanmanuals/UK_
NPL/mgpg11.pdf
3. http://www.wikihow.com/Calculate-­‐Uncertainty