Tuesday, May 31, 2011

High productivity fault detection

Written by  Douglas John Bowen, Managing Editor

The proverbial ounce of prevention is worth more than any cure when it comes to keeping heavy tonnage on track.

Railroads and several key suppliers several years ago embarked on the ATSI (Advanced Technology Safety Initiative), under the auspices of the Association of American Railroads and its subsidiary, Transportation Technology Center, Inc. (TTCI). ATSI was envisioned, through technology and detector result trending, to identify mechanical faults before they become critical and to engage in preventive maintenance—literally, “fix it before it breaks.”

Mechanical problems such hot or warm bearings, dragging equipment, flat spots on wheels, or truck hunting were recognized as having a tremendous impact on productivity because defective equipment causes, at the very least, cars and locomotives being pulled from service, bad-ordered, and/or set out for repair, thus delaying train movements and impacting network velocity. At worst, equipment failures cause derailments and wrecks, impacting operations far worse—and far more costly—than delays.

How has the railway supply community responded? Two companies—L.B. Foster’s Salient Systems and Progress Rail Services—offer examples.

L.B. Foster Co.’s Salient Systems

The use of heavy axle load (HAL) equipment and the resultant increased tonnage on North American railroads has reduced overall operating costs significantly, but such equipment also has accelerated the wear and damage to railroad infrastructure. L.B. Foster Co.’s Salient Systems says it has sought to significantly reduce that damage and improve railway safety and productivity by implementing various performance monitoring detectors based on the WILD (Wheel Impact Load Detector). Systems such as the Truck Hunting Detector (THD), Weigh in Motion (WIM) Detector, and Overload and Imbalance Detector (OID) allow railways to improve productivity as well as operate more safely.

Salient says it started the modern day performance monitoring portfolio with the WILD system in 1984. Since then, more than 250 WILD systems have been installed worldwide, with roughly 80% of those in North America. Instead of coping with in-service wheel failures and miles of track damage due to severe impacts, railroads now can use WILD data to schedule wheel maintenance prior to it becoming an in-service failure scenario. “This means that we can see a wheel failing and schedule the repair at a time and location that is the most productive for everyone involved,” a Salient spokesperson says.

The Salient WIM/OID system (billed as an inexpensive addition to a WILD) enables railroads to monitor their fleet in real-time, therefore preventing improper loading or en-route load-shifting caused derailments. The WIM/OID detector identifies vehicles that are unbalanced left to right as well as front to rear, and also correlates the UMLER database information that specifies the maximum carrying capacity.

The high-speed Weigh-in-Motion (WIM) systems, developed by Salient in 1992, capture static and dynamic weight data for wheels, trucks, and vehicles. By analyzing the weight information from the WIM systems against the maximum weight limit in UMLER, the railways quantify and correct improper or overloaded conditions, thus improving their operational efficiencies and improving safety.

WIM spots cargo overloading, off-center loading, or load shifting en route due to poor loading and securing procedures that can cause weight distribution problems. Such changes can cause excessive stress on the vehicle’s structure, in turn causing equipment degradation and infrastructure damage. Overloads can also increase lateral track stress, and can increase gage spreading. Excessive wheel/rail contact stresses caused by dynamic and high impact wheels have a direct influence on the development of corrugations and rolling contact fatigue (RCF) defects.

The loadings that are applied to the rails by the wheels have a direct influence on the wear rate as well as the noise levels observed. Imbalanced load can also contribute to a flange climb derailment scenario. WIM/OID systems provide railroads a method for detecting and preventing improper or shifted loads that may result in unsafe operating conditions and even derailment, Salient says.

Progress Rail Services

Tom Tougas, commercial leader, Progress Rail Inspection and Information Systems, says Progress provides technology to improve productivity and increase overall traffic velocity by identifying defects in wheels, bearings, and mechanical problems, and reporting these defects to both the train crew and dispatching center.

He notes that though these types of defect detectors have been around for many decades, in the past five years the use of advanced technologies and increased communications bandwidth has provided better information about each train as it passes a detector site.

Such information can then be used to analyze changes in the train data, or trends, from detector to detector, allowing the railroad to be more proactive in identifying potential defects before they cause significant impacts on velocity, or worse yet, cause derailments.

Tougas says Progress Rail offers Micro Hot Bearing Detector (MicroHBD) and Micro Hot Wheel Detector (MicroHWD) systems. Each utilizes infrared scanners attached to the rail that monitor bearing and wheel temperatures of each axle as a train passes.

Multiple samples are collected for each wheel/bearing, and then using patented algorithms, the data is analyzed to determine if the train should be stopped immediately for inspection. The data can then be sent to a central office system where trends in the train data from detector to detector can be analyzed to determine if the train should be inspected in order to prevent an impending failure.

Tougas also says its Dragging Equipment Detector (DED) can be mounted to adjacent ties or attached directly to the rail. The DED detects train defects that can cause damage to the rail infrastructure such as low hoses and derailed cars.

“High/Wide load detectors that scan passing trains can determine if the train is too high, too wide, or has a shifted load that could damage key infrastructure such as bridges or tunnels. Using infrared beams attached to the detector bridge structure, the system is activated when a train is present and will issue an alarm if any part of the train breaks the beam,” Tougas says.

The core fault detection technology advancements contributing to improved velocity and productivity reside in the MicroHBD electronics itself. The MicroHBD processing platform and core software architecture has evolved in the past six years, with significant reductions in false-positive alarms accomplished by implementing patented “real-time” algorithms to filter bearing heat samples while the train passes. With these improvements, railroads have seen a decrease in “No Trouble Found” train stops by more than 50%, says Tougas.

Tougas says other advancements have been made in the MicroHBD software to identify potential equipment and maintenance issues that could ultimately lead to unnecessary train stops.

Identifying potential issues such as loose connections, scanner misalignments, and saturated sensors let railroads perform preventive maintenance on the detector system before the system generates integrity failures.

Often, railroads are required to reduce train speed if an integrity failure is announced, so preventing these failures from occurring further increases overall velocity, Tougas says. Hybrid freight train economics Channels: Freight cars, locomotives

Hybrid streetcars, aided by batteries, are now being marketed to North American operators. Can such a concept work for rail freight transport?

By Mark Sisson, PE, Senior Analyst, AECOM, for Railway Age, Senior Analyst, AECOM, for Railway Age

Moving cargo via rail is one of the least polluting and most fuel-efficient modes of transport. After more than 150 years of technological evolution, it may seem that rail transport in the U.S. has little room for further improvement. One significant opportunity may yet remain, however: capturing the massive potential energy from trains at the top of long grades and using it to charge large on-board batteries (as opposed to simply dissipating that energy via braking friction).

This article examines the potential economics of a hybrid freight train that attaches a large battery car to a standard train. This battery car would be initially charged from the power grid, and then recharged as often as possible via regenerative braking during the downhill portions of each journey. The train will run on electric power whenever it is available. When the battery car is depleted, the train will run on diesel power (as trains do today).

Discharging and recharging en route

In these example calculations I have analyzed a unit container train—one equipped with a battery railcar—traveling between Los Angeles and Chicago. I have assumed a gross weight of 100,000 kg (220,000 pounds) for the battery car, which consists of a 10,000 kg (22,000 pounds) tare weight for the structure of the car and 90,000 kg (198,000 pounds) of batteries. I have selected lead-acid batteries for these example calculations. Lead-acid batteries are mature, robust, and cheap, and their relatively heavy weight and low energy density do not represent a great handicap in a rail environment. New developments in battery technology may change the economics of our example considerably, so I have analyzed a future example with more favorable battery parameters as a sensitivity case.

According to the website at allaboutbatteries.com, lead-acid batteries cost $170 per Kw-hr and have an energy density of 0.041 Kw-hr per kg of battery. A 90,000 kg battery would therefore be able to store 3,690 Kw-hr of electric power and cost $627,300 to purchase. Assuming a life span of five years and an interest rate of 6%, the annual cost for a battery railcar will be approximately $150,000. If each car makes 75 one-way trips between Los Angeles and Chicago per year, the capital cost of the car per trip is approximately $2,000.

If each train in this example is powered by three locomotives of 4,000 hp (2,984 Kw) each, and operates at a mean load factor of 30%, the train will be using an average of 2,700 Kw of power. One battery car can therefore power a train in purely electric mode for approximately 1.4 hours. If we assume a mean speed of 60 kph, each train could cover approximately 50 miles in purely electric mode at the start of each journey. This is a substantial benefit when compared to conventional operations, because the most heavily populated areas are found at the start of each journey. Affected residents of Los Angeles and Chicago would surely be thrilled at the prospect of having zero-emission trains replace some of the conventional freight trains that roll through their communities.

I have assumed that the hybrid train would run on pure battery power for as long as possible at the start of the journey. Trains traveling eastward to Chicago, for example, would depart Los Angeles on battery power. Then the depleted batteries would be fully recharged through regenerative braking on the descent from the mountains at the California-Nevada border. Somewhere before reaching the peak of the Rocky Mountains, the train would deplete the batteries again by running on electric power. The batteries would then be recharged a second time during the descent from the Rockies, and depleted a third time during the approach to Chicago. The depleted batteries would be recharged from grid power at the end of each trip. I have assumed a grid power cost of $0.10 per Kw-hr for these example calculations.

Three battery cycles at 3,690 Kw-hr per cycle allows for approximately 11,000 Kw-hr of electric power per journey. One third of this must be purchased from the electrical grid in order to begin the journey with a fully charged battery. The remaining two-thirds of this electric power is provided free of charge by regenerative braking on the descent through the two major mountain passes. This is a conservative calculation; there may be other opportunities to capture braking energy along the way.

The 11,000 Kw-hr of electric power used on each trip represents more than 7% of the total energy requirement for the journey between Los Angeles and Chicago. This would save approximately 700 gallons of diesel fuel per trip, even taking into account the extra fuel required to lift the 100-ton battery car over the mountains. And in our example scenario, nearly seven metric tons of CO2 emissions would be saved per trip.

Cost tradeoffs are weighed, compared

A battery car setup will impose some additional operating costs; the railroad will have to remove the car from the train and plug it into a recharging system at each end of the route. However, this may be accomplished with little or no extra cost if switch engines that are already used for placing a train into a working yard have any spare time available for this additional assignment. For the purpose of calculating these example system costs, I have assumed $100 of extra handling costs per trip.

I have analyzed the battery car with today’s parameters, and also with a series of hypothetical future scenarios. In the Future A case, the price of diesel rises from $3 to $4 per gallon. (Recall that diesel exceeded $4 per gallon in 2008).

In the Future B case, I have further assumed that batteries are able to store 50 percent more energy per unit weight than today’s lead-acid batteries, but for the same cost. With so many industries focused on research and development of better batteries, it seems safe to assume that batteries will soon become considerably more efficient. If properly designed, the battery railcar frame should be able to incorporate ever more efficient batteries in the same way a digital camera can work with increasingly powerful memory chips of the same physical size and configuration.

Our Future C case adds a carbon tax of $30 per metric ton of CO2 emitted. This tax level is consistent with what utilities in Europe are currently paying for emissions. In the long run, such taxes may apply to the transportation industry in the United States as well.

In the table, a cost saving is shown as a positive number, whereas a cost increase is shown as a negative number (contained in parentheses). The cost of electricity and the increased cost of propelling the additional weight of the battery car are offset against the overall savings on diesel fuel; these elements are combined to reflect net energy savings per trip. The calculations used in the table are shown in the leftmost column.

As the above calculations show, the use of a battery car as part of a hybrid train is unlikely to turn a profit with current input values. Even in the short term, however, the moderate financial cost may well be worthwhile for the public relations value alone; consider the highly visible benefit of producing zero emissions while traveling through the Los Angeles or Chicago metro areas—for over an hour on each trip.

As the future scenarios indicate—and assuming one believes that the price of diesel will inevitably go up, even as batteries become more efficient—battery-powered trains may be viable from a purely financial standpoint in the near future, and will become ever more profitable in the long run. The “benefit” of a potential future carbon tax will probably have only a nominal effect on the financial viability of the proposed system; the price of diesel and the likely improvements in battery technology will drive the cost-benefit equation.