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Laboratory of Control Process

Experiment (2)
Calibration of The Liquid in glass, Gas (vapor) Pressure
and Bi – metal Devices

Objective:
1. To understand the working principle of the Platinum Resistance
Thermometer (PRT) and correctly connect it to the TD400 Temperature
Measurement and Calibration Apparatus.

2. To demonstrate the linearity and accuracy of the PRT as a reference

temperature sensor for calibration purposes.

3. To evaluate the performance of various temperature measurement devices,

such as K-Type Thermocouple, liquid-in-glass thermometers, gas
thermometers, and bimetal devices, by comparing their readings with the
reference sensor.

4. To perform interpolation calculations from the K-Type Thermocouple

Standard Table to accurately determine the temperature from Electromotive
Force (EMF) in microvolts (µV).

a) To show how the platinum resistance thermometer works and how to

connect it correctly.
b) To show the linearity of the platinum resistance thermometer (PRT).
c) To prove that the platinum resistance thermometer is good for use as a
reference temperature sensor for all the other experiment.

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Introduction:
In this experiment, the Temperature Measurement and Calibration Apparatus
(TD400) was used to investigate the behavior of various temperature measurement
devices and to understand the concept of calibration using a reference sensor.
The K-Type Thermocouple, which is a widely used sensor for measuring
temperature based on the Seebeck Effect, was utilized to measure the
Electromotive Force (EMF) in microvolts (µV). The Platinum Resistance
Thermometer (PRT) was used as a reference temperature sensor due to its high
accuracy and linear response to temperature changes.
The experiment aimed to evaluate the linearity and accuracy of the K-Type
Thermocouple by comparing the EMF readings to the K-Type Standard Table and
performing interpolation calculations to accurately determine the temperature.
Unlike the standard procedure, Tap
Water was used instead of Distilled
Water, which slightly increased the
boiling point due to the presence of
impurities and minerals. This allowed
us to understand the impact of
different mediums on temperature
measurement.
By analyzing the relationship between
the temperature (T), the reference
temperature (TR), and the Ohm
Resistance (R), the accuracy and
reliability of the K-Type
Thermocouple as a temperature sensor
were assessed.

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 Theory:
Temperature measurement is crucial in many industrial and scientific applications.
Different sensors are used to measure temperature, each with varying accuracy,
linearity, and response times.
Platinum Resistance Thermometer (PRT)
The Platinum Resistance Thermometer (PRT) operates based on the principle that
the electrical resistance of platinum changes with temperature in a predictable
manner. Due to its high accuracy and stability, it is commonly used as a reference
temperature sensor for calibration purposes.

K-Type Thermocouple
The K-Type Thermocouple is a widely used temperature sensor that operates based
on the Seabecks Effect, where a voltage (EMF) is generated due to the temperature
difference between two dissimilar metals. The generated voltage is measured in
microvolts (µV) and is used to determine the temperature by referring to the K-
Type standard table.

Temperature Deviation and Error Calculation

Since no temperature sensor is perfectly accurate, deviations occur between the
measured and reference temperatures. The deviation temperature and percentage
error help evaluate the accuracy of the tested sensor.

 Temperature Deviation:

∆ T =T indicated−T reference

% Error= (T ∆T
reference
) ×100 %
These calculations are essential in assessing sensor performance and reliability.

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Experimental Procedure:
1. Setup: The TD400 Temperature Measurement and Calibration Apparatus
was set up, and the PRT was connected as the reference temperature sensor.

2. Heating Process: Tap water was used as the heating medium, and the
heater was turned on until boiling point.

3. Data Collection:
Readings were taken at different temperature intervals.
The reference temperature (T R) and indicated temperature (T i) were
recorded.
The deviation (∆ T ) and percentage error were calculated.

4. Cooling Process: The heater was switched off, and the readings were taken
as the system cooled

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Results and Analysis:
The collected data was analyzed to evaluate the accuracy of the measuring devices.
A table summarizing the reference temperature, indicated temperature, deviation,
and percentage error was constructed.
Table 1: Calibration Data

Time(min) TR V (mv) V
20 ( )
V
20
×1000
T (exp) %Error

0 23.2 2.3 0.115 115 2.9 0.875

2 31.8 5.4 0.27 270 6.82 0.785534591
4 37.15 13.3 0.665 665 16.7 0.550471063
6 45.3 17.8 0.89 890 22.27 0.508388521
8 53.8 25.1 1.255 1255 31.26 0.418959108
10 60.9 29.7 1.485 1485 36.9 0.39408867
12 67.4 35.7 1.785 1785 44.21 0.344065282
14 73.9 40.8 2.04 2040 50.41 0.317861976
16 80.5 44.7 2.235 2235 55.12 0.315279503
18 85.9 49.6 2.48 2480 61.05 0.289289872
20 91.6 54.4 2.72 2720 66.83 0.270414847
22 96.8 57.1 2.855 2855 70.09 0.275929752
24 98 58.1 2.905 2905 71.3 0.27244898
26 98 58.1 2.905 2905 71.3 0.27244898
28 98 58.1 2.905 2905 71.3 0.27244898
AVG = 0.410842008

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 80

70

60
(𝑽/𝟐𝟎)×𝟏𝟎𝟎𝟎

50

40

30

20
Table 2: NTC Sensor Calibration Data
10
Time(min) TR V (mv) R( R(ohm)ohm) T (exp) %Error%
0 00 23.2
500 2.3
1000 1500128.3 2000 18.32500 0.211207
3000 3500

𝑻_(𝐞𝐱𝐩)
2 31.8 5.4 98.6 25.44 0.2
4 37.15 13.3 75.7 33.23 0.105518
6 45.3 17.8 58.6 40.96 0.095806
8 53.8 25.1 45.8 48.8 0.092937
10 60.9 29.7 36.6 56.17 0.077668
12 67.4 35.7 30.2 62.83 0.067804
14 73.9 40.8 24.8 70 0.052774
16 80.5 44.7 20.9 76.26 0.052671
18 85.9 49.6 18 82.01 0.045285
20 91.6 54.4 15.7 87.45 0.045306
22 96.8 57.1 14.1 91.8 0.051653
24 98 58.1 13.3 94.04 0.040408
26 98 58.1 13.3 94.04 0.040408
28 98 58.1 13.3 94.04 0.040408
AVG = 0.081324

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 100

90

80

70

60
(𝐑_(𝒐𝒉𝒎)

50

40

30

20

10

0
0 20 40 60 80 100 120 140

𝑻_(𝐞𝐱𝐩)

Discussion:
By analyzing the data obtained from the experiment, we can clearly see a noticeable
difference in measurement accuracy between the two calibration methods used.
Comparing the tables, we find that the average percentage error in Table 1 (0.4108) is
significantly higher than in Table 2 (0.0813), indicating that the method used in Table 2
provided more accurate temperature measurements.
Why does this difference exist?
The primary reason lies in the calculation method used. In Table 1, the calibration was
based on voltage values, whereas in Table 2, it was based on resistance values.
Resistance tends to have a more stable and direct correlation with temperature, while
voltage readings can be affected by several factors, such as electrical noise, interference,
and non-linearity in sensor response.
Several other factors contributed to measurement errors:
1. Using Tap Water Instead of Distilled Water
Regular tap water contains minerals and impurities that alter its boiling point,
causing slight variations in the recorded temperature compared to theoretical
values.
2. Instrumental and Calibration Errors
While the PRT sensor is highly accurate, every measuring device has inherent
errors, such as response time delays or calibration drift over time.

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 The K-Type thermocouple relies on the Seebeck Effect, where the generated
voltage may be influenced by electrical noise or oxidation at the metal junctions.
3. Heat Loss During Measurement
Some heat dissipates into the surrounding environment, especially during the
cooling phase, which introduces slight discrepancies between the measured and
actual values.
4. Non-Linearity in Thermocouple Data Tables
The standard K-Type thermocouple tables require interpolation to convert voltage
readings into temperature values. This process can introduce minor errors,
especially at higher temperatures where the thermocouple response becomes less
linear.

Conclusion:
This experiment demonstrated the significant impact that measurement methods
have on accuracy. The results showed that calibration using electrical resistance
(Table 2) provided more reliable readings compared to voltage-based calibration
(Table 1), as it resulted in a much lower percentage error.

However, this does not mean that voltage-based calibration is invalid; rather, it
requires optimization to reduce measurement errors. Possible improvements
include:
1) Using distilled water instead of tap water to eliminate boiling point
variations.
2) Applying thermal insulation techniques to minimize heat loss during the
experiment.
3) Enhancing calibration methods with more accurate reference tables or
devices that automatically compensate for errors.

Overall, this experiment highlighted the importance of selecting the right sensor
and calibration method for precise temperature measurements in industrial and
scientific applications, as even small measurement errors can significantly impact
thermal process decisions.

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