AUTOMATICALLY IDENTIFY CHANGES TO ELECTRIC POWER LINES, TRANSFORMERS, ETC. TO BETTER PRIORITIZE AND ALLOCATE RESOURCES FOR IN-DEPTH INSPECTIONS

AF CIVIL ENGINEERING

AUTOMATICALLY IDENTIFY CHANGES TO ELECTRIC POWER LINES, TRANSFORMERS, ETC. TO BETTER PRIORITIZE AND ALLOCATE RESOURCES FOR IN-DEPTH INSPECTIONS.

Identify changes in infrastructure (power-lines, etc) using automated aerial, space, and other data analyses to better prioritize and allocate resources for in-depth inspections.

Background: 

We want to build extremely large, wide-area models of electric power lines, and to use these models to simulate the electric and magnetic fields produced by the voltages and currents on the lines. Being linearly related to the voltages and currents, these fields carry a lot of information about the grid and can be used for a number of applications. Low-SWaP-C electric- and magnetic-field sensors are readily available and can be incorporated into ground- and air-based sensing systems. These models will help in the development of new algorithms that use these measurements. Constructing these models requires accurate, high-resolution dimensional data of terrain elevation, the power lines (e.g., poles and other structures, lines, substations, transformers), and other infrastructure over very large regions (e.g., 100 km2). We are looking for automated methods for collecting this data.

Use case example: Why it’s important

Gaining this capability will enable defense users to improve stability, balance loads, conserve power, and reduce outages on national grids and tactical microgrids. Additionally, this capability will help detect sagging lines and encroaching tree lines ready for trimming, as well as map downed or damaged lines and transformers during disaster recovery or nation building.