Key Takeaway: Railroads follow rigorous inspection regulations and leverage well-trained inspectors, sophisticated equipment, and data-driven analysis to identify and address potential issues with equipment and tracks proactively. These efforts will continue to help reduce Class I railroads’ train and equipment-caused accident rates.
Across the network, railroads employ thousands of well-trained inspectors — qualified per Federal Railroad Administration (FRA) regulations — who monitor and assess the health and safety of the equipment that moves essential goods and materials and the track that spans nearly 140,000 miles.
There are prescribed training standards for any employee who inspects or performs tasks covered by a federal rule, including those who inspect such things as signals, tracks, railcars, locomotives and bridges. In addition to conducting the various inspections required by FRA, railroads have, for decades, voluntarily invested in testing, implementing and advocating for advanced inspection technology to supplement manual inspections.
Every day, around the clock, thousands of sensors throughout the rail network collect billions of data points that generate alerts for issues that require immediate attention. Furthermore, advanced computer programs, machine learning and AI analyze the data, identifying patterns and predicting what network elements may soon need repair or replaced days, even months, in advance. These elements include tracks, wheels, bearings, locomotive components and more. This information helps give railroads lead time to proactively schedule maintenance and fix issues before they become dangerous.
ATI measures how track structure performs under a train’s weight.
Automated Track Inspection systems use lasers and cameras mounted onto locomotives or railcars to inspect track as a train travels across the network. The system tests each foot of track, which detects issues that may not be visible when a track is not occupied. The data from the inspection devices transmits to a centralized location where employees verify and schedule maintenance as necessary. ATI speeds up safety inspections and safeguards employees.
Track inspection vehicles, or “track geometry cars,” can measure hundreds of thousands of track miles yearly. The cars travel along the tracks, measuring every inch for track alignment, elevation in curves, gauge (the distance between the two rails) and many other track geometry measurements. An advanced algorithm can analyze track alignment of more than 1,500 curves in track in just a few hours, whereas it would have taken a team of four people 10 months to complete the same task manually.
Ultrasound looks for flaws inside tracks and ties.
As a train travels over any track segment, energy is transmitted through the track and into the ground below. This energy can be measured as a series of sound waves by ultrasound, collectively called an acoustic signature. The acoustic signature of a track is different depending on the health of the track. Going further down, ground-penetrating radar looks inside track foundation — known as ballast — to see water damage or deterioration.
Drones inspect track, ballast and bridges.
Loose or missing fasteners in track or soft spots in ballast could cause more stress on the track structure and lead to signal problems. Railroads use drones most frequently after weather events to look for washouts, downed trees, misaligned track and other conditions caused by weather. This technology provides trending data because railroads can analyze older snapshots with newer ones.
Regular inspections of railroad bridges by inspectors or drones are vital for trains safely transporting goods across bodies of water. Sonar also identifies increased erosion around the piers, which can compromise a bridge’s integrity. Sonar sends sound waves that bounce off the bridge piers and the ground surface below the water. Then, based on the nature of the echo, railroads determine whether there are any concerns with the stability of the bridge piers.
Signal inspectors look at active grade crossings.
Railroad employees also help ensure safety at the points where trains cross roads, known as grade crossings. Signal inspectors climb up on the lights to ensure they are pointed in the right direction, open the bungalow and check everything in the case, and look at the timing and distance between the train coming into the crossing circuit and the crossing protection coming down.
Locomotive sensors monitor individual components.
While a train is on the move, hundreds of sensors throughout the locomotive continually gather data on the performance of individual components. Sensors transmit the data to analysts using real-time software to identify equipment needing maintenance. Locomotives also have fuel management systems that use sensors that provide engineers with real-time recommendations on how to operate the train to maximize fuel efficiency, but also sense when an engine is getting too hot or when oil is contaminated.
Machine visioning inspects passing trains.
Machine visioning technology uses cameras that collect 40,000 images per second of trains as they pass by at up to 60 MPH. This technology reduces inspection times to mere seconds. A series of algorithms then analyze the images to identify any anomalies, allowing railroads to resolve issues faster than they could with manual inspections alone. The technology helps railroads look at many elements simultaneously, providing a comprehensive view of locomotives, trains and their components.
Lasers, scanners and more inspect moving wheels.
Additionally, hot bearing detectors are strategically placed along the right-of-way to sense overheating bearings, alerting engineers to stop a train when necessary. Some detectors transmit temperature data, allowing proactive tracking and replacement of bearings. Wheel impact load detectors greatly reduce broken rails and prevent wheel and bearing failures by identifying heavily pounding wheels so they can be removed from service.
Additionally, hot bearing detectors are strategically placed along the right-of-way to sense overheating bearings, alerting engineers to stop a train when necessary. Some detectors transmit temperature data, allowing proactive tracking and replacement of bearings. Wheel impact load detectors greatly reduce broken rails and prevent wheel and bearing failures by identifying heavily pounding wheels so they can be removed from service.
