Early semi-automated arc detection for utility lines
Faculty
Departments
Students
Locations
Project Topics
Funding Sources
Abstract
The intent of this project is to investigate the efficacy in detecting radio frequency interference (RFI) emitted from overhead power lines and combining this data with an automated mapping system via GPS. The basic system design will include three primary components: a radio front end, a processor, and a global positioning system (GPS). The radio front end that is used is the HackRF One, the processor used is the Raspberry Pi Model 3B, and the GPS used is the Gumstix PreGo PPP using the U-Blox Neo-7P GNSS. The HackRF One and the GPS unit both feed in their information into the processor. The Raspberry Pi will be operating on linux and running GNU Radio Companion while the GPS module’s update rate will result in inputing decimeter-level accuracy.
Inspired by work supported by the TREE Fund and the Center for Environmental Inquiry.
Results
| Title | Format | Download | Students |
|---|---|---|---|
| PLAD: Power Line Arc Detector | website with report | PLAD: Power Line Arc Detector | Ian Furniss, Kenneth Kleinsmith |
Key Terms: environmental technology, antenna, noise floor, FFT, maximum route layer, pin drop resolution, battery, spark gap