Freight-train derailment shows temp sensing woes
Article By : Bill Schweber
Reliably detection of excessive temperatures of railcar wheel bearings is a technically difficult undertaking.
You may have followed the story of the February 3, 2023 derailment in East Palestine, Ohio, involving 35 cars of a freight train, some of them carrying hazardous substances. The accident has prompted serious concerns for area residents and the surrounding environment. Although the formal analysis and report on the cause are not complete, it seems pretty certain that the cause was an overheated journal bearing—called hot box—on one of the wheels.
The train passed temperature sensors—usually called hot-box or hot-bearing detectors—that showed components of a hopper car getting warmer as it traveled. The detector that showed the bearing had reached a critical temperature was about 20 miles away from the prior detector. Crews worked to stop the train after receiving an alarm about the temperature reading but couldn’t stop the train before the bearing failed. Unlike cars, a freight train traveling at moderate-to-high speed can take a few miles to stop, as there’s so much mass and momentum.
Of course, pundits and politicians are insisting that the railroads “do something” or “do more” to prevent another such accident. However, on-the-ground reality is that checking for overheated bearings and other impending problems is being already handled. While more could be done, it’s a difficult problem technically.
A senior engineer told me some years ago that when it comes to temperature, “measuring is easy, but sensing is hard.” In other words, the physical circumstances of the arrangement often make it hard to “get in there” for accurate, consistent readings, especially in harsh operating circumstances or when the target is moving, as railroad cars are.
Railroads use temperature detectors based on infrared thermal sensors to measure the heat emitted from bearings, wheels, axles, and brakes (Figure 1 and Figure 2). About 6,000 of these temperature hot-box detectors are in place on the North American freight-rail network, with an average spacing of about 15 miles (~25 km). Optical filters ensure that the detector is only looking at infrared radiation in the desired band, and the entire system is activated only when a train approaches, so it’s not “looking at the sky” the rest of the time.
Figure 1 The bearing is the most likely source of problems, but other components of the wheel/axle assembly can also pose concerns. Source: University of Texas Rio Grande Valley
Although specifics vary from railroad to railroad, train crews are supposed to receive an alert to stop and inspect equipment if sensor readings are between 170°F (~75°C) and 200°F (~°93°C) above the ambient temperature, or if the difference between bearings on the same axle is at or above 115°F (~46°C), as shown in Figure 2.
Figure 2 A hot-box detector must scan the bearing, axle, and brake assembly. Source: University of Texas Rio Grande Valley
What more can or should be done? Would closer spacing of detectors make a difference? Maybe, but how many more would make a meaningful difference? Alternatively, would lowering the temperature-alarm threshold help? Again, maybe, but that might also cause more false alarms. That will not only be costly and affect schedules, but also lead to the well-known “just ignore it” syndrome. Furthermore, in the harsh operating conditions of a railroad, there are genuine considerations of any safety systems going bad and being knocked out of service due to many causes.
The problem has been studied extensively in academic and field settings, as seen in one research project from the University of Texas, titled “An Analysis of the Efficacy of the Wayside Hot-Box Detector Data.” At the same time, new technologies are being tested and deployed to measure other parameters. For example, acoustic sensors are being used, consisting of sets of microphone arrays spanning about 25 feet of track length (“Wayside detection of faults in railway axle bearings using time spectral kurtosis analysis on high-frequency acoustic emission signals”). By analyzing the acoustic emissions generated by the passing car’s bearing components, the system can identify which of the car’s component has an impending fault (Figure 3).
Figure 3 Researchers are investigating use of acoustic emissions to assess bearing and other impending problems, but it’s an environmentally harsh and acoustically noisy measurement environment. Source: Sage
Among the possible defects an acoustic-based system can identify—at least in theory—are bearing spalling or brinelling, loose, cracked or broken components, peeling or smearing, wheels with flat spots, and lubrication failure. Without a doubt, it’s a long list of acoustic signatures to analyze and characterize in a challenging setting. It’s a lot more difficult than trying to assess bearing problems in a fixed-in-place industrial setting.
These schemes are not just for the rolling stock, as problems can occur beyond the wheels and bearings. There are sensors which check for problems with static components such as cracked rails. This can be done via measurement of injected current and resistance, magnetic field variations, and advanced photo-optical and fiber-optic methods which are under evaluation.
Moreover, the sensing side is only part of the problem. With an array of sensors strung out over miles of track, there are also connectivity issues and associated reliability considerations. Fault reports are sent via radio link to the train engineer, modem, LAN, or GSM cellular. But how do you ensure that reporting scheme is working properly? Ambient temperature extremes, unavoidable vibration, and overall abuse can easily create faults in the connectivity scheme.
One possible solution being suggested is to abandon or supplement the rail-side in-place measurement and instead place sensors on the bearings and wheelsets of each car. That could eliminate some problems but create new ones. Each car would need instrumentation, power, and connectivity in a rugged package. That’s tough to achieve given in the realities of railroad-freight cars, even if cost is not a concern (and it certainly is).
Have you ever been involved with sensing of temperature or another physical parameter which seemed easy in principle but was difficult to execute adequately in reality? To what extent were you or others surprised by this situation?
This article was originally published on Planet Analog.
Bill Schweber is an electronics engineer who has written three textbooks on electronic communications systems, as well as hundreds of technical articles, opinion columns, and product features. In past roles, he worked as a technical website manager for multiple EE Times sites and as both Executive Editor and Analog Editor at EDN. At Analog Devices, he was in marketing communications; as a result, he has been on both sides of the technical PR function, presenting company products, stories, and messages to the media and also as the recipient of these. Prior to the marcom role at Analog, Bill was Associate Editor of its respected technical journal, and also worked in its product marketing and applications engineering groups. Before those roles, he was at Instron Corp., doing hands-on analog- and power-circuit design and systems integration for materials-testing machine controls. He has a BSEE from Columbia University and an MSEE from the University of Massachusetts, is a Registered Professional Engineer, and holds an Advanced Class amateur radio license. He has also planned, written, and presented online courses on a variety of engineering topics, including MOSFET basics, ADC selection, and driving LEDs.
