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Ground vehicle power line spectral sensing using GIS
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Paper Abstract

The electrical power consumption of an area is indicative of industrial activities of high power-consumption facilities. Research on detection and characterization of loads on AC lines has shown that magnetic field sensors at a fixed point can be used to determine the electrical current flowing through a line as a means of determining power consumption versus time. The relative frequency harmonic power and phase content of the current flow can distinguish between types of electrical loads (i.e., resistive or inductive) and changes in those loads. Coupled with an understanding of the line geometry (conductors and cross-sectional location) in the modeling, we can model the geographic distribution of the fields from a given current source. Experimentally, we collect multiple axis magnetic field data from moving vehicles with GPS time and location data for the data recordings. The collection regions include rural, interstate, and suburban areas with both overhead and buried power lines contributing to the signals. We analyze the data using ArcGIS to visualize the geospatial content and compare qualitatively and quantitatively the power levels to data layers such as the area land use. We examine the 60 Hz fundamental frequency, harmonic and non-harmonic signals, and compare the results to 2-D and 3-D modeling tools using known power line conductors. We discuss the effects of the time-varying presence of vehicles in modifying the detected signals as well as the changes in the spectral information over time.

Paper Details

Date Published: 27 April 2018
PDF: 11 pages
Proc. SPIE 10645, Geospatial Informatics, Motion Imagery, and Network Analytics VIII, 1064502 (27 April 2018); doi: 10.1117/12.2304040
Show Author Affiliations
Mark W. Roberson, Goldfinch Sensor Technologies and Analytics LLC (United States)
Charles E. Bartee, Goldfinch Sensor Technologies and Analytics LLC (United States)
Laura E. Roberson, Goldfinch Sensor Technologies and Analytics LLC (United States)


Published in SPIE Proceedings Vol. 10645:
Geospatial Informatics, Motion Imagery, and Network Analytics VIII
Kannappan Palaniappan; Peter J. Doucette; Gunasekaran Seetharaman, Editor(s)

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