I wonder how this is done, exactly. Sound is applied, and the resulting frequency is measured. If it doesn't match the freq tolerance range, the wheel is rejected? Or, can the sound sensing locate the actual flaw? Like a sonar technique.
I used to know a few people that repaired industrial equipment, including train wheels. Mostly welding fractures or breaks back together. How would repairs work with this system. It almost seems like a waste to throw out a whole wheel.
This is an important step forward. Bearing hot boxes have been used forever. I can remember them being used in the '70s, and they were mostly good for spotting existing problems, rather than heading off potential issues.
In the early seventies I started work with a previous employer and inherited the engineering responsibility for their line of cylindrical roller freight train bearings. Many bearing failures were spotted by hotbox indicators, and after quite a few of these, the failure mode was established. The thin walled, straight Inner Races would turn on the axle journals and wear against the fillet ring and end cap that doubled as thrust flanges. This reduced the tension on the 3 bolts that screwed into the axle ends, holding the whole bearing assembly together. The bolts unscrewed even though they were supposed to be "locked" by bent tabs of a large triangular washer for all 3 bolts. The axle cap would then fall off, and since the bearing's inner race was turning on the axle journal, it would also fall off. Next, the bearing's outer race and rollers only had to drop down 3/8" (thickness of the inner race) and run directly on the axle journal. Grease would be lost and the axle being relatively soft resulted in a bad bearing making heat that was picked up by the hot box indicators. Sometimes, when a maintanence crew would go to the car, they would find the whole end of the axle worn off. This fiasco resulted in the company abandoning the railroad bearing business.
The original bearing method for railcars was poured babbit, hand scraped and lubricated with oil-soaked rags stuffed into a metal box above the outboard end of the axle. The failure detector was the brakeman in the caboose looking for smoke as the babbit melted out and the steel-to-steel created molten metal that ignited the oil-soaked rags. Hot-boxes are still an issue even with modern roller bearings and yearly we fight fires along the rail tracks because a bearing failed and spewed molten metal along 10 miles of track igniting ties, brush and debris along the trackside. Thermal detection methods work to detect failed bearings but a method of finding incipient failures would be a significant improvement. A 120 car train with 2 two wheel trucks per car is nearly a thousand bearings. Swapping out a car with a defective bearing in the middle of a train is nearly impossible so early detection is important.
Being a geeky engineer and a railfan, I know a little about this stuff.
Here in the USA, railroads primarily employ three types of defect detection.
- Hot box/bearing detectors where thermal detectors look at wheel bearing temperatures.
- Dragging equipment detectors where sensors detect if anything on the equipment is dragging or hanging too low.
- Wheel Impact Load Detectors (WILD) where they measure the acoustics / impact of the passing equipment.
All of these detectors can be interfaced to a AEI reader which reads the RFID tags present on all rail equipment, and I think all of the equipment is equipped with a computerized radio transmit system which transmits the status of the train to the engineer/conductor after the train passes. (If you have a radio scanner, it's interesting to listed to the train speed and axle count as a train passes.)
I find that the WILD systems are the most interesting, as the data is used to predict when wheels will start to cause a problem. Most rail cars are owned privately, but there are standard repair agreements that let a host railroad perform maintenance on a car if it's needed. Replacing wheels are expensive and obviously car owners wish to avoid this, but out of round wheels (we've all heard a freight train with a banging wheel) cause major damage to the railroad infrastructure and can cause derailments.
In addition to the three primary system types mentioned above, there are a few (about sixteen nationwide I believe) Trackside Acoustic Detection Systems (TADS) installed. Similar to the system in the article, TADS uses acoustic signatures to indentify potential wheel bearing problems. Neat stuff!
I don't think many people are aware the railroads were probably the earliest adopter of RFID technology with their AEI system. Much better than the old ACI system which used colored bar codes, which failed miserably in the dirty railroad environment.
As to wheel repair as mentioned by a previous poster, the feds limit what type of work that can be done to wheels. I think that certain failures such as cracking, can condemn a wheelset.
There is a long history of a variety of bearing failure detection methods in the railroad industry. In the 1980's, I was working for a railroad supplier and was heavily involved in bearing failure detection methods. We developed and manufactured a line of trackside heat detection systems (called 'hot box detectors') which, with a variety of sophisticated computer algorythms, were quite successful at detecting bad bearings on trains as they rolled by the hot box detector. There were two downsides to the hot box detector system - you needed a detector every couple of miles and they only detected a bearing that had already gone bad - when they go, they go quick.
We also dug into the audio detection scheme. Our company spent a considerable amount of time trying to come up with a reliable way of acoustically detecting bad bearings but was unsuccessful so congratulations to RailBAM for their success. Our project was started when our client(s)(i.e. the railroad companies) noted that their track crews could detect, by just listening as trains rolled down the hump yard tracks, a failing bearing. Then they could shunt the bad car and have the bearing fixed before it got out on the road and failed (with usually nasty consequences).
So they suggested we try to come up with a product to automatically achieve the same results. We spent many, many hours at track side recording the trains as they rolled by (digitally) and attempted to correlate what the computer picked up with reports from the crews on 'bad' wheel sets. Unfortunately we were never able to come up with a solid and reliable way to do the detection.
The entire subject is quite fascinating - well, at least to me!
Hi, Cabe. I bet the sensor system looks for a specific pattern of sound frequencies within a certain bandwidth. Various filtering techniques or a fast Fourier transform would let software "look" for activity at those frequencies.
I remember as a kid, seeing a train go by me spewing sparks and glowing debris from the wheel. I thought it was cool at the time. (I was standing right next to the tracks.) Now, that concept frightens me. It is 2012, and 100 year old ways of "doing things" does have to step aside. Innovations like this are so important.
Digital healthcare devices and wearable electronic products need to be thoroughly tested, lest they live short, ignominious lives, an expert will tell attendees at UBM’s upcoming Designers of Things conference in San Jose, Calif.
Focus on Fundamentals consists of 45-minute on-line classes that cover a host of technologies. You learn without leaving the comfort of your desk. All classes are taught by subject-matter experts and all are archived. So if you can't attend live, attend at your convenience.