Technology Solutions for the Power Transmission Industry

Over the recent decades, the survey industry has undergone great leaps in technology for collecting real Earth data and making analysis of the same data. Two of the most significant changes have been in the fields of LiDAR data collection and affordable unmanned aerial drone systems that are capable of converting high-resolution photographs into survey grade data. These two systems have allowed geospatial professionals to map structures and existing conditions quickly and more accurately.

The power transmission industry is uniquely suited to take advantage of both technologies. Data collection that used to take days and sometimes weeks can now be captured in hours. Close inspection of powerline assets can be completed safely and accurately so that industry personnel do not need to put themselves in harm’s way. So what are these technologies, and how can they be used in the power transmission industry?

LiDAR (Light Detection and Ranging) uses high-speed lasers that can capture 1 million data points per second and build a data set in precise 3-D. The resulting data can be used and analyzed in multiple types of software including PLS Cadd, AutoCAD and Bentley products. Lasers can be mounted on multiple platforms including fixed wing aircraft, helicopters, tripod mounts, as well as moving vehicles including cars, trucks or watercraft. These systems can facilitate hundreds of miles of powerline mapping in a fraction of the time required only a few years ago.

LiDAR can also be very effective for vegetation management. When used with precise survey control, the instruments can accurately collect existing conditions of assets, including towers, substations as well as the existing conditions in the surrounding corridor. By using various photographic sensors in addition to LiDAR, the quality of the power connections to the towers can be analyzed safely. Additionally, the systems build a 3-D map of the terrain and the vegetation in the area adjacent to the corridor. Owners can use this information to determine if there are potential hazards with trees impacting the towers and lines. The data can be processed and inserted into PLS Cadd, the standard system in the industry.

Currently, the majority of inspections conducted use LiDAR mounted on helicopters and fixed wing aircraft. The advances in the unmanned aerial systems or “drone” technology is quickly evolving as another option. These relatively small systems can collect the same quality of data at a fraction of the cost of a standard manned aircraft. Piloted drones can currently complete a 40-mile flight line; however, within the next 12 months, that distance should start approaching 100 miles per day.

Drones are safer and cheaper and can get much closer to lines and towers without risking the pilot or aircraft. The relative cost per mile is extremely low compared to manned aircraft, and they can now be equipped with a variety of sensors that can take close-range color video, thermal images, and infrared images. Corona cameras can be added to detect arching on worn or storm damaged connectors.

Courtesy of Leica Geosystems

Many drones use close-range photography to produce LAS or point cloud data. Larger platforms can also collect LiDAR data from much closer than conventional aircraft. Manned aircraft must be at least 500 feet above ground level for helicopters and 1,000 feet for airplanes.  The current ceiling for drones is 400 feet; however, they can fly 50 or 100 feet above a transmission line and safely collect high-quality data.

The combination of LiDAR and drones can do in hours the work that only a few years ago would have taken days. Fortunately, the software required to produce the proper analysis has also kept up with the technology. For that reason, the time from data collection to finished product has continuously shortened.

LiDAR and drone technology are changing the way that data is captured. At the same time, they are reducing the cost of mapping important power transmission line assets and providing quality analytic data.