Power System Fault: Detection and Prevention

1. Power System Fault: Detection and Prevention Ryan Habib Wilkes University Huy Tran Richland College

2. Purpose • Construct a simple data acquisition system to mimic the measuring of an arc flash incident

3. 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

4. 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

5. Arc Flash Experimentation Fiber Optic Internet Connection Slug calorimeters and Pressure sensors NI cRio: 16 Differential AI 16 TTL Compatible DI/O AD210 + MOV Analog Devices 7B-47-K-04-1 (Build-in CJC) Experimental DAQ System

6. Arc Flash Simulation

8. SCADA (Supervisory Control And Data Acquisition) Systems • Versatile industrial control system • Components • Sensor • Remote terminal unit • Central computer

9. Sensors • Reads a signal from a physical property and converts it into one usable by a control system Photoresistor Hall effect sensor

10. Thermocouple • Type K thermocouple • Produces output voltage dependent on temperature • Made of two metals with different conducting properties • Temperature range of -200⁰C to 1350⁰C

11. Types of Thermocouples

12. Analog to Digital Conversion • 7B47 Signal Conditioning Module • Successive Approximation ADC

13. Data Logger • Records digital data from the sensors • Easily connected to other machines to display information in real time

14. GL800 • Simultaneously displays and records data from up to 20 inputs

15. LabVIEW • Large quantity of functions for data acquisition, signal conditioning, and data analysis purposes • Extensive support for accessing instrumentation hardware

16. 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

17. 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

18. Setup

20. Results: Change from Air to Hot Water

21. Results: Change from Air to Hot Water (Average)

22. Results: Change from Air to Cold Water

23. Results: Change from Air to Cold Water (Average)

24. Results: Change from Hot Water to Air

25. Results: Change from Hot Water to Air (Average)

26. Results: Change from Cold Water to Air

27. Results: Change from Cold Water to Air (Average)

28. Results: Change from Hot Water to Cold Water

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

30. Results: Change from Cold Water to Hot Water

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

32. Results: Change from Adding Hot Water to Cold Water

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

34. 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

35. 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

36. 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

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