1 Ryan Habib Wilkes University Huy Tran Richland College.

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Power System Fault: Detection and Prevention

Ryan HabibWilkes University

Huy TranRichland College

Purpose

Construct a simple data acquisition system to mimic the measuring of an arc flash incident

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Arc Flash

A rapid release of energy in the form of an electrical explosion that results from a low impedance connection between lines of different voltage or phases

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Arc Flash damage Most burns from

electrical accidents are a result of arc flash

Temperatures can reach up to 20,000⁰C

Most occurrences are in industrial settings due to required power levels

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Arc Flash Experimentation

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Analog Devices7B-47-K-04-1(Build-in CJC)

NI cRio: 16 Differential AI16 TTL Compatible DI/O

Fiber Optic Internet Connection

AD210 + MOVSlug calorimeters and Pressure sensors

Experimental DAQ System

Arc Flash Simulation

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SCADA (Supervisory Control And Data Acquisition) Systems

Versatile industrial control system Components

SensorRemote terminal unitCentral computer

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Sensors

Reads a signal from a physical property and converts it into one usable by a control system

Photoresistor Hall effect sensor

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Thermocouple

Type K thermocoupleProduces output voltage

dependent on temperature

Made of two metals with different conducting properties

Temperature range of -200⁰C to 1350⁰C

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Types of Thermocouples

Type Materials Traits

B/R/S Platinum-Rhodium Low Sensitivity, High Cost

E Chromel-Constantan High Sensitivity, Non-metallic

J Iron-Constantan Low Range, High Sensitivity

K Chromel-Alumel Inexpensive, Versatile, Reliable

N Nicrosil-Nisil More stable in high-energy environments

T Copper-Constantan Very Stable, especially at lower temperatures

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Analog to Digital Conversion

7B47 Signal Conditioning Module Successive Approximation ADC

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Data Logger

Records digital data from the sensors Easily connected to other machines to

display information in real time

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GL800

Simultaneously displays and records data from up to 20 inputs

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LabVIEW Large quantity of functions for data

acquisition, signal conditioning, and data analysis purposes

Extensive support for accessing instrumentation hardware

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System Setup

Seven thermocouples were each connected to their own 7B47 signal conditioning module

Each module was connected to an input of the GL800

USB/Ethernet cable connected GL800 to computer

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Test Process

Place thermocouple in water to be measured

Send digital pulse to trigger the GL800 data recording

Connect computer to GL800 to record data on the computer

Convert data from GL800 from voltage to temperature

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Setup

Internet (Wireless or LAN)

7B47

7B47

7B47

7B47

7B47

7B47

7B47

7B47

+ - + -+ -+ -+ -+ -+ -+ -

CH1 CH4 CH5 CH6 CH7 CH8CH3CH2

Control & Monitor System

Communication System

Data Acquisition & Logger System

A/D Converter Equipment & Protection System

Industrial & Commercial Power Grid

DAQ System Utilized in Power System

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Results: Change from Air to Hot Water

0 0.5 1 1.5 2 2.5 3 3.5 40

10

20

30

40

50

60

70

Air to Hot Water

Thermocouple 1

Thermocouple 2

Thermocouple 3

Thermocouple 4

Thermocouple 5

Thermocouple 6

Thermocouple 7

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Air to Hot Water (Average)

0 0.5 1 1.5 2 2.5 3 3.5 40

10

20

30

40

50

60

70

Air to Hot Water

average

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Air to Cold Water

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

Air to Cold Water

Thermocouple 1

Thermocouple 2

Thermocouple 3

Thermocouple 4

Thermocouple 5

Thermocouple 6

Thermocouple 7

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Air to Cold Water (Average)

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

Air to Cold Water

average

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Hot Water to Air

0 1 2 3 4 5 60

10

20

30

40

50

60

Hot Water to Air

Thermocouple 1

Thermocouple 2

Thermocouple 3

Thermocouple 4

Thermocouple 5

Thermocouple 6

Thermocouple 7

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Hot Water to Air (Average)

0 1 2 3 4 5 60

10

20

30

40

50

60

Hot Water to Air

average

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Cold Water to Air

0 0.5 1 1.5 2 2.5 3 3.5 40

2

4

6

8

10

12

14

16

18

Cold Water to Air

Thermocouple 1

Thermocouple 2

Thermocouple 3

Thermocouple 4

Thermocouple 5

Thermocouple 6

Thermocouple 7

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Cold Water to Air (Average)

0 0.5 1 1.5 2 2.5 3 3.5 411.5

12

12.5

13

13.5

14

14.5

15

15.5

Cold Water to Air

Average

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Hot Water to Cold Water

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

35

40

45

50

Hot Water to Cold Water

Thermocouple 1

Thermocouple 2

Thermocouple 3

Thermocouple 4

Thermocouple 5

Thermocouple 6

Thermocouple 7

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Hot Water to Cold Water (Average)

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

35

40

45

Hot Water to Cold Water

average

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Cold Water to Hot Water

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

35

40

45

50

Cold to Hot Water

Thermocouple 1

Thermocouple 2

Thermocouple 3

Thermocouple 4

Thermocouple 5

Thermocouple 6

Thermocouple 7

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Cold Water to Hot Water (Average)

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

35

40

45

50

Cold to Hot Water

average

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Adding Hot Water to Cold Water

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

Adding Hot Water to Cold Water

Thermocouple 1

Thermocouple 2

Thermocouple 3

Thermocouple 4

Thermocouple 5

Thermocouple 6

Thermocouple 7

Time (s)

Tem

per

atu

re (

oC

)

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Results: Change from Adding Hot Water to Cold Water (Average)

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

Adding Hot Water to Cold Water

average

Time (s)

Tem

per

atu

re (

oC

)

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Data Analysis

System did a solid, yet unspectacular, job of reading changes in water temperature

Variance in quality of measurements throughout the different tests

Could be attributed to variety of factors, including low sample rate and lack of memory

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Comparisons with LabVIEW

Using LabVIEW would’ve solved the issues with sample rate and memory

Interface is much less intuitive Weeks/months to master skills

necessary for this type of task

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Conclusion

The DAQ system was able to measure changes in temperature in a relatively effective manner

The components in the system are versatile enough to be used in a wide array of situations

For these specific tests, a data logger with a higher sampling rate, along with a sensor with a more narrow range, would have been more effective

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Acknowledgements

Dr. Wei-Jen Lee Zhenyuan Zhang Zhaohao Ding The University of Texas at Arlington National Science Foundation

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