Countless commuters and travelers depend on the nation’s railroads every day. However, in 2022 there were 1,164 train derailments across the U.S., according to the Federal Railroad Administration (FRA). That’s an average of about three derailments per day.
This year, the 50-car freight train pileup in Palestine, Ohio, and the passenger train crash that caused a death and multiple injuries in the Netherlands were just two examples of recent derailments that made international headlines.
Looking back over the last decade, Amtrak has recorded an average of 24 derailments annually according to the FRA. The unacceptably high frequency of rail accidents has become a serious public safety concern that begs for a solution. Is there new technology on the horizon that can address this challenge?
Steps for Preventing Rail Accidents
The key to avoiding rail accidents is to continuously track key data throughout the rail system and employ technology that uses this data to detect problems and take action before derailments occur.
For example, consider the problem of overheated wheel bearings, which have been pinpointed as the source of the fire and derailment in the Ohio accident. The nation’s freight rail system has deployed roughly 6,000 “hot box” detectors positioned every few miles along the tracks to measure bearing temperatures and radio personnel, if they detect severe overheating. These detectors capture valuable data, but they are not being fully employed to predict impending issues and prevent accidents.
What’s needed is new technology that can harvest and analyze their data more effectively.
With about 300 Amtrack trains and 500,000 carloads of freight crossing the rails every week, hot box detectors alone can generate mountains of telemetry that need to be quickly correlated and analyzed to spot trends in real time. This analysis can identify likely wheel bearing failures and alert operators to intervene and avoid an accident. Having large teams of personnel perform this task around the clock would not be practical.
How ‘Digital Twins’ Can Help
A software technology called “digital twins” can help address this challenge. Originally created to model complex devices like jet engines, digital twins also can be used for real-time analysis. They can be deployed for every railcar to ingest and analyze data streaming in from hot box detectors and other monitoring devices. With this data, digital twins can continuously look for abnormal trends and alert operators within seconds.
What makes digital twins well suited for monitoring the rail system is that they can independently focus on each railcar and instantly process telemetry to check for problems.
For example, they can monitor temperature changes as the railcar moves from detector to detector to identify overheated wheel bearings before they cause accidents. Using machine-learning techniques from artificial intelligence, analytics code can watch for abnormal temperature patterns, unexpected differences across axles and wheels, and other anomalies.
Digital twins can even keep track of each car’s service history and other known issues specific to the car to provide additional context that aids in the analysis. Running on scalable, cloud-based server clusters, they can simultaneously track the nationwide fleet of railcars. And unlike human analysts, they can maintain constant vigilance without the need for coffee or rest.
How Digital Twins Can Save Lives
In addition to monitoring the safety of railcars, digital twins also can assist in avoiding collisions at rail intersections.
The fatal passenger train incident in the Netherlands was caused by a crane that unexpectedly obstructed the tracks and remained undetected by an approaching passenger train. Cameras and other sensors placed at rail intersections can stream telemetry to digital twins, which monitor the rails at each location for approaching rail traffic.
These digital twins keep tabs on nearby rail traffic using sensors, such as hot box detectors placed along the tracks. If they detect a potential conflict, they can immediately alert personnel to stop approaching trains. They also can collect data about the pattern and frequency of crossing traffic to help predict the likelihood of a conflict as each train nears an intersection.
Ensuring rail safety should be a top priority for both passenger and freight operators, transportation agencies, and local and federal governments. With train derailments occurring frequently each year, it’s crucial that we take proactive steps to mitigate this risk.
One potential solution is the adoption of innovative technologies like digital twins, which can identify potential safety hazards and avoid costly accidents. Proactively deploying new technology has the potential to save both lives and money.
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