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Ingenuity and innovation at work

March 2020

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Locomotive 7538, a GE Evolution series unit, is the first locomotive equipped with NS’ new autonomous track geometry measurement system. In the photo, taken on an NS mainline in Virginia, the 7538 pulls NS manned test and research geometry cars during testing to verify data recorded by the locomotive-mounted inspection system.

Norfolk Southern achieves a first in autonomous track-inspection technology

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Mike Allran, left, manager track inspection and development, and Scott Hailey, track geometry engineer, inspect wiring connections on an early prototype of NS’ locomotive-based autonomous track inspection system.

Inspecting mainline track to ensure safe and efficient operations is serious business at Norfolk Southern. Now, in an example of how NS is reimagining possible, our railroad has achieved a breakthrough that positions us as an industry leader in track-inspection technology.

Through ingenuity and innovation, our Engineering Department has developed and deployed an autonomous track geometry measurement system that is mounted on a locomotive. This advancement enables us to use an existing asset in revenue service to inspect rail while pulling loaded trains at track speed.

NS is the first North American freight railroad to gain this capability. Competitor railroads are using commercially available track-inspection systems installed on converted rail or passenger cars, which require an external power source to operate and take up space that could be used for a rail car moving revenue freight. Our locomotive-based system is a railroading home run that covers all the bases of our strategic plan: It supports reliable service, increases the efficiency of operations, lowers costs, and enhances safety.

“This is transforming how we inspect track,” said Mike Allran, manager track inspection and development, who helped lead the initiative.  “Anytime this locomotive is out there pulling freight, it’s also testing track.”

Aiming for more frequent and precise track inspections

The autonomous system will supplement track inspections conducted by NS’ existing fleet of track geometry cars and hi-rail trucks. Typically, the company’s two sets of geometry cars, pulled by a dedicated locomotive, are able to inspect the busiest mainline tracks two to four times a year. Engineering employees in hi-rail trucks conduct visual inspections of mainline track at least twice a week as required by Federal Railroad Administration rules.

With our new system, NS will increase both the frequency and the precision of track inspections, said Ed Boyle, vice president engineering. The locomotive-based system eliminates the need to schedule track time, a big time saver and efficiency gain. Further, these inspections will arm NS with more data to use with predictive modeling tools to set track maintenance intervals and help make capital budget decisions.

“Our goal is to have high-quality track inspections done under load at track speed using an existing asset,” Boyle said. “Going forward, we will more readily identify where track work needs to be done and use the track time available to fix locations, not waiting for track time to go find locations. That’s a huge efficiency gain, because the time we’re on the track is spent productively working on track.”

Changing rules of the road with technology advances

As part of a pilot, NS is running the autonomous system on a six-axle GE Evolution locomotive moving freight across mainline track on the Pocahontas Division between Norfolk, Virginia and Portsmouth, Ohio. The route is a good proving ground to show the effectiveness of the autonomous technology, Allran said. It offers a mix of track and operating conditions, including straight track in the coastal plain, curved and hilly track in mountainous terrain, and high-tonnage train loads.

“The current FRA regulations for track inspections have been in effect for 40-plus years and have not kept up with the technology we have out there today,” Boyle said. “With our locomotive-based system, we can enhance the safety and efficiency of operations with more frequent track geometry inspections.”

Building a better mousetrap

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Tim Childress, assistant manager test cars, and Scott Hailey, track geometry engineer, check fittings on a metal box that houses the autonomous track inspection system components. The box is mounted under a locomotive between the snow plow and the first set of wheels

NS’ senior operations leaders challenged Allran’s team to rethink autonomous inspection technology. They wanted something more efficient and less costly to operate than the car-based inspection systems offered by vendors.

“We received a charge to figure out how to do it on a locomotive – so we did,” Allran said.

Work began in the spring of 2018 to develop, test, and perfect the system. They faced the challenge by starting with what they knew.

“We knew the key components used in track geometry systems, and we knew from experience what worked – we called it railroad tough,” said Scott Hailey, track geometry engineer.

NS reached out to some defense industry vendors in search of components available on the commercial market and robust enough for the railroad environment. Two main components make up the autonomous system, Hailey said. One is a system of 2-D laser scanners designed to measure the gauge of track, or the distance between the two rails, ensuring that the rail is stable and not spreading apart. The other is an inertial system composed of gyros and accelerometers. They are attached by cables to the locomotive wheels and record track curvature and elevation, creating a 3-D model of each rail with the pitch and roll of the wheels.

These components are packaged in a ruggedized metal box mounted under the locomotive between the snow plow and the first set of wheels. A computer that powers the system is housed in the locomotive cab inside the electrical locker. Integrated into the machinery is a Global Positioning System that precisely pinpoints potential defects.

As the locomotive moves over the rails, data is analyzed and filtered for exceptions by the on-board computer. The findings are transmitted wirelessly to NS’ track-inspection office in Roanoke for analysis and verification by Allran’s team. Exceptions are forwarded to Engineering Department servers in Atlanta and then passed on to track supervisors who inspect the track and arrange needed maintenance or repairs.

Turning data into actionable information

At computers in Roanoke, members of Allran’s team created the algorithms and software programs that comprise the brains of the system. Using existing track geometry data, they created equations that enable the system to detect, in real-time, conditions that fall outside of certain track geometry parameters.

“We took data off of our geometry cars and reverse-engineered it to come up with the algorithms, or equations, that accomplish the same thing on our system,” Hailey said. To test the calculations, the team connected the system components to an NS geometry car and ran them over track, comparing results with data collected by the car’s inspection equipment.

“Ensuring that our system measured the same values as our geometry car was our golden standard,” Hailey said.

One of the biggest challenges, Hailey said, was deciding how to mount the system on a locomotive. The metal box holding the components is a cube about 2 feet wide, 10 inches tall, and 12 inches long. NS chose the Evolution model because modifications weren’t needed to fit the system underneath the locomotive.

“We took a lot of time measuring and making sure it would not interfere with normal operations of the locomotive,” Hailey said. “The idea was to take a standard locomotive and do as little as possible in changing the locomotive to be able to install the system.”

Achieving NS’ business goals

With the pilot underway, NS is building another autonomous inspection unit to install on a second locomotive. It’s cost-effective: NS engineering calculates that we can equip five to six locomotives with our in-house system at what it would cost to buy one of the car-based vendor systems. In addition, the company might expand the system’s capabilities, such as adding line-scan cameras that take video images of rail and use machine-learning technology to identify defects.

For Allran and his team, the prospects are exciting. It’s extremely rewarding, Allran said, to develop a solution that is helping NS achieve its business goals.

“We’ve got some smart, innovative employees working for us,” he said. “They understand that the company’s leadership wants to get the operating ratio down to 60% – to get expenses down and get the revenues up – and we’re trying to be proactive.

“In our own way,” he added, “the things that all of us are doing internally, like this autonomous track inspection system, go a long way to support our strategic plan.”

To learn more about the innovative ways Norfolk Southern is using technologies to advance freight rail transportation, visit our Rail Tech webpage.