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Part 5: Maintaining Optimal Wheel and RailPerformance

Written by Mr. Michael D. Roney, member of the IHHABoard of Directors and Professor Willem Ebershn, memberof the Technical Review Committee.

5.1 Maintaining Optimal Wheel and RailPerformance

Rail is the single most expensive element of the track structure.On many railways, it is behind only labor and fuel as anexpense item. The tonnage carried by a rail before it iscondemned can range from less than 100 million gross tons toclose to 2.5 gigga gross tons.

As an example of the value of rail maintenancemanagement, assume that a single kilometre of rail costs$180,000 to install. Track engineers decide that the rail has abadly fatigued surface and has reached the end of its servicelife. They call for it to be replaced, gaining a salvage value of$18,000.

But now assume that instead of replacing the rail, they didsome corrective rail grinding costing $1800 and left the rail intrack. The railway then invested the $180,000 $18,000 -$1,800 = $160,200 in the construction of a new customerfacility at a rate of return of 20%. This earned $160,000 * 20%= $32,000 in its first year.

The next year, the track engineers see that their rail isapproaching allowable wear limits and schedules a railreplacement, now costing $187,200 due to cost escalation of4%. But they have made for the railway $32,000 ($187,200 180,000) = $24,800 by deferring replacement of rail in thatkilometre, without consequence, for an extra year. And that iswhy they collect a salary.

There is significant money to be made by deferring railreplacement as much as possible without incurring risk.Certainly it is a major responsibility of the track engineer toensure that he gets the most out of his rail, and rail profilemaintenance and rail testing are his most important tools to dothis.

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The catch is that the above statements assume that theaging rail does not have a direct impact upon other expenses,such as wheel wear or fuel consumption. Furthermore, theremust not be a significant increase in risk of rail fracture.

To optimize rail and wheel life cycle, it is imperative thatthese two components are managed jointly, as it is thewheel/rail interaction that determines the performance of eachcomponent.

In the case of wheel and rail, rail maintenance holds thekey, as rail is static in its location along the track layout andmore accessible for maintenance. Although the wheelrequirements of a vehicle is more variable in the sense that itmoves over a variety of rail layouts and conditions, itsrequirements must match those of the rail to ensure optimalwheel rail interaction.

The joint strategies of rail re-profiling, frictionmanagement (lubrication), control of gauge, and rail conditionmeasuring can protect rail-caused cost impacts.

Rail re-Profiling: Rail and wheel life is reduced if thewheel/rail contact conditions deteriorate through migration ofthe contact band or flattening of the rail. Regular metalremoval can also control surface fatigue, which is ultimatelyassociated with internal rail defects. Both are controllablethrough regular re-profiling.

Friction Management: Maintaining the rail surface frictionwithin specified limits on the rail gauge face, but also on thetop of rail, can reduce rail and wheel wear and improve fuelconsumption.

Gauge Control: As the gauge face wears, widening gaugewill change wheel/rail contact locations, which can acceleratewear and fatigue. If the rail is allowed to spread (rollover)under dynamic gauge widening, rail contact fatigue can result.Lubrication and attention to fastener condition act together tocontrol these cost impacts.

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Rail Condition Measuring: Rail fatigue under high axle loadscombined with the rail section reductions through wear andgrinding is an ideal environment for condition basedmaintenance practice with the measuring devices availabletoday. The rate of occurrence of some internal rail defectsincreases and can be detected with a rail defect-measuring plan.The cost impact does not need to be high, however, as long assuch occurrences are detected, rail defects can be changed outin a production fashion behind the rail testing operation.Technology advances have made rail profile measuringaccurate and repeatable to the extent that rail wear rate can bereliably determined and used for maintenance planning.

In the same manner, wheel profile and to a certain extentdefect detection technology is also at the point wheremaintenance can move from a routine based maintenancepractice to a condition based maintenance practice.Unfortunately, wheel risk management and maintenancepractices are not at the same level as rail risk management. Asan example, one heavy haul railway reports that for the year2000 track related failures accounted for 23% of all accidents,where wheel failures represented 5% of the accidents. Butwheel related accidents are characteristically more severe and isreflected by the cost of these accidents as being 31% of thetotal accident costs. (FRA reported Safety Statistics shows aratio of 36% track vs. 3% wheel related accidents with 11% ofthe track-related derailments due to broken rails1).

Considering the high cost of wheel related derailments, itseems that there is a discrepancy in our management of failurerisk of rails versus wheels. As typically indicated, a wheel thatlasts 5 years on a 30 mgt line would likely be tested andprofiled 2 times, whereas a rail in the same period would likelybe re-profiled and ultrasonically tested 16 times.

Nevertheless, over the past decade, railways have increasedtheir control of wheel/rail contact, although not always in anintegrated manner, between the wheel shops and the trackmaintenance teams.

If rail sees frequent maintenance attention, as discussedabove, how long can it stay in track? Depending on operating

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conditions, costs can certainly be minimized when the rail isultimately removed for loss of railhead, as opposed to anyother cause such as fatigue. This gives rise to seriouslyrethinking the maximum allowable rail wear limits.

Whereas rail limits in the past have been associated withthe ultimate contact of a high wheel flange with the joint bar,continuous welded rail has virtually eliminated this barrier.Another concern in the past, particularly for railways with 30-ton and greater axle loads and/or standard carbon rails, hasbeen that the rail would be misshapen by the time such limitswere being approached, as a result of plastic flow that thewhole track structure would be suffering from the poor vehicletracking.

In an environment where dynamic wheel/rail interactionand profiles are controlled, railway engineers can start to workto get the full life potential from the yield strength of the railsection.

The achievement of full utilization of rail generally requiresa deliberate plan to put the following supporting strategies inplace:

1. Develop target rail profiles that are seen to achievelow fatigue and wear. Because of the heavy influenceof contact fatigue on rail, these target profiles wouldtypically incorporate some conformity with wheelprofiles. A mechanical representative should be onthe team to advise on implications for wheels, and toexplore the potential for joint optimization of wheeland rail profiles. This part is addressed in previouschapters.

2. Measure rail and wheel conditions to determinemaintenance needs.

3. Develop rail and wheel wear projection methodology.4. Develop rail and wheel fatigue life projection

methodology.5. Perform economic evaluation of different premium

rail options based upon condition monitoring andexecute plans to progressively balance rail strength

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with service environment. Determine the use ofpremium and intermediate rail steels in differenttonnage and curvature classes based on minimum lifecycle costs. Perform analyses to determinetransposition and re-use policies.

6. Perform extensive rail re-profiling to the target profileand to correct existing rail spalling, corrugations, andhead checks.

7. Re-profile wheels to target profile.8. Install lubricators in locations with past history of

higher gauge face wear rates.9. Develop new rail wear limits and supply new design of

joint bar to support extended wear limits in secondarylines.

10. Develop new wheel wear limits.11. Implement regular and frequent ultrasonic rail

inspection as well as regular rail wear and profilecondition measurement. Quality assessment is animportant part of this strategy. Correlate raildeterioration with track geometry condition and gaugewidening to develop joint strategies.

12. Implement regular and frequent wheel flaw inspectionas well as regular wheel profile conditionmeasurement.

13. Implement frequent maintenance rail re-profiling(grinding) on regular cycles. The objective should beto move to single pass rail grinding, with speedsadjusted to grind as fast as possible to control rail flowand fatigue occurring between grinding cycles.

14. Adjust profiling standards and rail-testing intervals tomatch needs of rails approaching extended wear limits.

15. Implement a condition based maintenance plan forwheel re-profiling.

Not all of these steps have to be in place to achieve majorsavings in costs. It is suggested, however, that quantumimprovements in rail and wheel life require some attention toeach of the steps. Critical to the implementation of thisstrategy is that all people involved clearly understand both the

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end objective and the role of each of the elements. This willundoubtedly require some education of track managersthrough senior engineering managers of such aspects as role ofrail and wheel profile designs, fatigue mechanisms, and wearrates.

5.2 Rail Structural Deterioration5.2.1 Management of Rail Testing to Control Risk of

Rail FractureThe occurrence of internal defects in rails is an inevitableconsequence of the accumulation of fatigue under repeatedloading. To maximize rail life, heavy haul railways live withcontrolled rates of defect occurrences, relying on regularultrasonic or induction rail testing and strategic renewal of railthat is obviously showing evidence of fatigue.

The consequences of internal flaws can be serious. Anunrecognized defect can result in rail breakage withinterruption of service and the potential risk of catastrophicconsequences. At the least, an isolated case means a repaircost and introduces two unwanted welds, while a series ofdefects can condemn a whole rail length.

FRA Reported Safety Statistics for 1999 1 shows 11% of theaccidents were rail and joint bar related. Figure 5.1 shows thedistribution of accidents for rail and joint bar defect types for1999.

Train Accidents Reported for Rail and Joint Bar Defect Type (%)

1%

1%

1%

2%

3%

3%

3%

4%

4%

12%

13%

15%

17%

21%

Joint Bolts Broken or Missing

Bolt Hole Crack or Break

Mismatched Rail-head Contour

Head and Web Seperation (inside joint)

Worn Rail

Joint Bar Broken

Horizontal Split Head

Broken Field Weld

Other Rail and Joint Defects

Detaied Fracture from Shelling

Head and Web Seperation (outside joint)

Verrtical Split Head

Broken Base of Rail

Transverse/compound Fissure

Figure 5.1: Distribution of Accidents Per Rail andJoint Bar Type

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The challenge is to avoid the occurrence of service failuresdue to undetected defects. Service failures are more expensiveto repair and can lead to costly line disruptions or evenderailments. The role of rail defect testing is therefore toprotect service reliability while avoiding overly conservative railrenewals. To illustrate the scope of rail testings contribution,consider that North American heavy haul railways detect anaverage of 0.4 defects per track km. (0.6 rail defects/mi) eachyear while inspecting at intervals of 18 mgt (20 mgt) andexperience 0.06 service failures/km (0.1 service failures/mi.).One service defect in two hundred leads to a broken railderailment. Rails are typically replaced when total defects areoccurring at a sustained rate of 1-2/rail km (2-3/mi.).2

In controlling risk, the most basic control variable is thetest interval. A railway administration must decide upon thefrequency of passage of the rail testing equipment that willbalance the cost of testing and rail change-out with theexpected derailment cost to minimize the net cost of the risk.In this delicate equation, the reliability and operating speed ofthe testing system play an important role.

5.2.2 The Framework for Risk ManagementThe practice of rail testing has a simple objective of reducingthe annual costs incurred as a result of broken rails. But thereare many variables involved. Figure 5.2 shows the mostimportant of these.

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Figure 5.2: Factors Controlling the Risk ofBroken Rail Derailments

The direct cost of undetected rail breaks is the differencebetween the cost of replacing broken rails on an emergencybasis, and the cost of the orderly replacement of detecteddefects. The cost of derailments caused by undetected brokenrails is an indirect cost of poor inspection reliability. Thederailment cost is the annualized cost of the rare but high costoccurrence of a derailment. As the probability would bederived statistically from past records, the annualizedderailment cost is also called the expected derailment cost.This cost is also related to specific characteristics of the railway

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such as the remoteness of the routing, the severity of theterrain, the type of lading, and the size and speed of the trains.

The number of service failures is intimately related to theeffectiveness of the inspection. In a risk managementapproach, high inspection reliability is required where longtrains are travelling fast along a watercourse in proximity topopulation centers. While heavy haul lines typically have longtrains and high derailment costs, train frequencies may be lessthan on mixed freight lines, defect growth rates may be moreuniform, and tonnage is easier to track for the purpose ofplanning test intervals. Many heavy haul operators havededicated rail-testing vehicles, which they may use at frequentintervals, even monthly.

To ensure an effective rail testing program, the testequipment must be properly designed and calibrated to reliablyindicate defects, the equipment logic must present to theoperator only those indications that could be a rail defect, andthe operator must be experienced and diligent.

In addition, test frequencies must be matched to thegrowth rate of critical defects so that at least one test, andpreferably more inspections, are made in the interval betweenthe development of a rail defect to a minimum detectable sizeand its growth, to a size that represents a significant rate ofrapid fracture.

In practice, the growth rate of rail defects is both highlyvariable and rarely known with any certainty. Rail testing onheavy haul operations often presents some specific problems,for as traffic loading is high, defect growth is accelerated andthe time scale for intervention is compressed. The tendencyfor each wheel passage to stress the rail in a similar pattern canincrease defect growth rates. At the same time, heavy axleloads can lead to a fatigued rail surface that may presentconfusing indications from testing equipment. The use of railof various metallurgical qualities further complicates the task.

Most heavy haul operators attempt to control risk bymonitoring of the reliability of the test through evaluation offailures occurring soon after testing and by comparing ratios ofservice to detected rail defects.

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5.2.3 Defect Occurrence RatesThe driving factor determining the risk of rail fracture is therate at which a population of internal flaws develops in the rail.Internal flaws in rail have a period to initiation and a periodduring which a crack will propagate. The risk is introducedwhen cracks remain undetected during their growth to criticalsizes. This occurs when the period between the times thecrack reaches detectable size is significantly shorter than thetesting interval. Figure 5.3 presents the example of a rail flawwith a long period of exposure before failure and one with ashort exposure time. An example of a long exposure timemight be a transverse fissure, which is detectable at a small sizedue to its central location in the head, and which may growslowly. At the other extreme might be a defective weld withpoor fusion in the web area. The web cracks would typicallybe large at first detection and could be expected to propagaterapidly.

In revenue service, rail in a given routing would beexpected to have a broad population of defects of differentsizes, each growing at a different rate.

In a typical heavy haul line, the population of flaws ofdifferent sizes can be assumed to be distributed according toan exponential distribution (Figure 5.4), where there are manyvery small flaws, but very few large defects. As fatigue cyclesaccumulate in the rail from high contact stresses, more flawsare initiated and those already present continue to grow.Critical to the risk of a rail break is the number of defects inthe right tail of the distribution. The area of the right tail ofthe distribution would represent the number of rail flaws thatare of sufficient size that they could fracture suddenly. It is afact that the distribution of internal defects by size varies fromlocation to location. A highly stressed track segment or onelaid with a dirtier steel, will have a population distributionshifted to the right and should, in theory, be tested morefrequently to achieve the same risk level.

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Figure 5.3: Size Distribution of Flaws inRails in a Typical Line

Figure 5.4: Transverse Defect Growth RatesMeasured under 39-Ton Axle Loads at

FAST/Heavy Tonnage Loop

Because rail flaw detection is quite effective at detectinglarge defect sizes, the distribution of defects in track at any onetime is skewed to the smaller sizes. The critical objective of railtesting programs is to both eliminate the right tail high riskdefects in the distribution at the time of testing while

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attempting to detect all defects from the distribution which,through growth, will have reached the high risk level by thetime of the next rail test.

Hence both testing reliability and test intervals areimportant. But most importantly, test reliability and testingintervals must be matched.

Presently, there is little hard evidence on either the growthrates of different defects or their critical sizes. One notableexception is the defect growth relationship determined instudies by the Transportation Technology Center, Inc. (TTCI)a subsidary of the Association of American Railroads (AAR) atthe Facility for Accelerated Service Testing Facility (FAST),Pueblo, Colorado USA. By monitoring the growth oftransverse defects under the controlled conditions of a unittrain cycling over the test loop, TTCI measured a wide rangeof different growth rates.

Figure 5.5 plots the progression of transverse defects thatdeveloped under a consist with 35 ton (39 Ton) axle loads.3,4The tonnage required to initiate a defect was found to be verydifficult to predict, but once initiated, transverse defects werefound to grow non-linearly with tonnage, as would bepredicted from fracture mechanics theory. Under the uniformheavy loading conditions of the FAST consist, some defectgrowth rates were found to be quite rapid. Rapid growth ratescould also be expected where tensile residual stresses arepresent in the railhead, and in low temperatures in continuouswelded rail where the rail is again in tension.

Part 3, Appendix A presents Canadian Pacific rail systemcriteria for the protection of defective rail in track.

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Figure 5.5: Transverse Defect Growth Rates Measured Under39-Ton Axle Loads in Fast Heavy Tonnage Loop

5.2.4 Critical Defect SizesExperience has shown that rail can fracture suddenly fromtransverse defects as small as 10% of the railhead. Generally,risk is significant when a transverse defect is larger than 35%of the head. A bolt hole crack is known to start to growrapidly when the length exceeds about 13 mm (in.), and rapidfracture can usually be anticipated from a 25 mm (1 in.) crack.In general, railways have relied upon experience to distinguishbetween fractures which present a substantial risk and thosewhich may safely remain in track for a specified period of time.For example, Part 3, Appendix A: Canadian Pacific RailDefects5 presents the mandatory Protection Codes imposed byCanadian Pacific Rail System on trains passing over detectedrail defects prior to their removal from track. This tablepresents one heavy haul railways assessment of the riskassociated with different sizes and types of defects.

A study of dynamic fracture of rails conducted at QueensUniversity at Kingston, Canada,6 has shed some more light onthe dynamic load capacity of rails, and hence the risk offracture under heavy axle loading. The study involveddropping dynamic impact loads typical of those imposed byshelled wheel treads, out-of-round wheels or wheel flats onrails, which had been removed from track because of detecteddefects of different types. The rail specimens were pulled

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longitudinally to simulate tensile stresses from lowtemperatures, and some specimens were tested at down to 20C.

It was found that:

1. Impact loading was far more likely to fracture defectsin the transverse plane;

2. The tensile stresses imposed by temperaturessubstantially less than the neutral temperature wereimportant in causing rail fracture;

3. Where the rail is shelling excessively, sudden railfracture will occur at lower, more frequent impactlevel;

4. The residual, thermal and dynamic stresses imposed bytraffic contributed equally to total stress intensity;

5. The size of the flaw is a more important risk factorthan the percent of the railhead that has fractured. Infact, a larger railhead may fracture more easily underdynamic loading. Because a greater rail mass must berapidly moved aside under a high frequency impact,i.e. has greater inertia, a larger railhead is lesscompliant and may absorb more energy in impact.

Through observation of the conditions under which a railwith a known defect could fracture suddenly, an equation wasdeveloped from this work, which calculates the peak dynamicload at fracture, Pdyn, stated in kilopounds (kips):

s46.638.183.4

-D-= TCIb

Kpdyn (1)

Where:

K is the fracture toughness of the rail steel. Thisvalue IC is typical 38.5 MPa for standard rail steelsand 20% higher for premium rail steels;

DT is the variation of the rail temperature from itsneutral or stress-free temperature in degreesFahrenheit.

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sr is the residual stress determined from the openingthat develops in a saw cut test. A value of 15.7kPa/mm (14.3 ksi) is a good estimate from theQueens University tests.

For example, using the above empirical equation, thefollowing combinations of conditions could cause sudden railfracture:

For a transverse defect covering 8% of the railhead:

a rail temperature of 56 Celsius (100 Fahrenheit)below the neutral temperature and a dynamic wheelload of 356 kN (80,000 lbs).

For a transverse defect covering 10% of the railhead:

a rail temperature of 56 Celsius (100 Fahrenheit)below the neutral temperature and a dynamic wheelload of 311 kN (70,000 lbs).

For a transverse defect covering 18% of the railhead:

a rail temperature of 39 Celsius (70 Fahrenheit)below the neutral temperature and a dynamic wheelload of 311 kN (70,000 lbs).

For a transverse defect covering 40% of the railhead:

a rail temperature of 56 Celsius (100 Fahrenheit)below the neutral temperature without any wheelloading.

See Part 3, Appendix A: Rail Defects (Canadian PacificRail & Spoornet)

5.2.5 Rail Fatigue ProjectionMost railways performing regular projection of rail life use theWeibull methodology for projecting rail fatigue occurrencerates. The Weibull methodology is useful in identifyinglocations where trends are sustained vs. the case where defectshave remained constant. The situation where rail defectoccurrence rates are increasing is more critical, as this maysignal a mature fatigue process. These projections are used toidentify consistent trends in rail defect occurrences that couldbe cause for a rail renewal program.

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Attention to trends identified through regular use ofWeibull projections may guide selection of a strategy to correcta defect trend by tamping up rail joints, building up rail ends bywelding, relieving the gauge corner, or attending to flat wheels.

Rail should be changed out when the annual cost ofrepairing rail defects exceeds the value of deferring the renewalfor another year. At a repair cost of only $2500 per defect, andan annual value of $18000 in interest savings if you leave therail in track, it requires a strong trend line to justify a railreplacement for defect occurrences alone. But if a significantnumber of these rails are failing in service, this introduces thepossibility that leaving the rail in track may incur the high costof line outages during emergency rail replacements and brokenrail derailments.

The key therefore is in maintaining effective rail testing.As shown, service reliability requires both effective testingsystems and frequent rail testing. Attainment of long railservice lives in a heavy haul environment similarly requires astrategy to support rail economics with effective rail testing.

5.2.5.1 Use of Weibull Distribution to Predict RailFlaw Occurrence Rates

( )b

hgb

hg

hb

---

-=

T

eT

Tf1

)( (2)

The Weibull probability density function is given by:

(T) > 0, T > g, b > 0, h > 0, - < g <

Where:

b = Shape parameter

g = Location parameter

h = Scale parameter

T = Time, Tonnage etc.

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The Weibull reliability function is given byb

hg

--

=T

eTR )( (3)

and the Weibull failure function

b

hg

--

-=

-=

T

e

TRTF

1

)(1)(

(4)

The failure function is manipulated into the following form:

( ) ( )hbgb

hg

b

hg

b

hg

b

nTnTF

nn

T

TFn

eTF

eTF

T

T

llll

l

--=

-

-=

-

=-

=-

-

--

)(11

)(11

)(11

)(1

(5)

This linear relationship is used for constructing Weibullprobability paper. ( )hb nl is constant for a given situation.The Weibull failure rate, l (T), is given by

( )1)(

-

-=

b

hg

hb

lT

T (6)

In rail failure analyses one of two avenues for the calculation ofreliability or failure rates can be followed:

1. A maximum number of failures, defects oroccurrences, per distance of track, of a certain naturecan be decided upon beforehand. Once this level offailures has been reached it is assumed that 100% ofoccurrences had been experienced and some actionlike replacing of the rail is taken.

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2. No previous decision regarding the number of defectsthat is allowable in the track has been taken. Here useis made of the so called Median Rank to allocate avalue of F(T) to failures. The Median Rank will, in thiscase, again be based on a unit length of track.

In order to obtain relevant results from a Weibull analysisof rails the track must be divided up in homogeneous units.Information required for analysis includes:

1. The type of defect (Classification of failure);

2. Tonnage to failure;

3. Time to failure;

4. History of repairs and maintenance;

5. Infrastructure data. Position in track etc.

Lengths of rail in a unit may vary upon conditions. Ingeneral lengths from 5 km to 50 km may be used. Theconsiderations for lengths of rail to be identified, tested andanalysed will be discussed later.

The following example illustrates the typical use of theWeibull function.

Failure data for heavy haul-line 20 to 40 km:

Failure type : Kidney shaped crack

Line length (km) : 20

Max. defects per km : 5 (Has to be decided on as policy)

Table 5.1 shows data from a spreadsheet program used forthe calculation of the Weibull parameters.

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Table 5.1: Results from Weibull analysisTonnage

(mgt)Years Failures

per periodAve. Failures

per km% Failed

100 2 5 0.25 5

200 4 8 0.65 13300 6 4 0.85 17

400 8 8 1.25 25

500 10 4 1.45 29

600 12 6 1.75 35

700 14 5 2.00 40800 16 9 2.45 49

900 18 8 2.85 57

The columns in Table 5.2 are:

F(mgt) % of failures of the Kidney shaped crack type.Based on the max. defects allowable per km.

Tonnage (mgt) Actual gross load carried by rails.

)(

)(11

Tonnagenx

MGTFnnY

l

ll

=

-

=

Weibull parameter calculationLocation parameter, g :0

Table 5.2: Calculation of Weibull parametersF(mgt) Tonnage (mgt) Y X

5 100 -2.9702 4.6051

13 200 -1.9714 5.2983

17 300 -1.6802 5.703725 400 -1.2459 5.9914

29 500 -1.0715 6.214635 600 -0.8421 6.3969

40 700 -0.6717 6.5510

49 800 -0.3955 6.684657 900 -0.1696 6.8023

Regression Output: (Linear regression done on Y and Xcolumns)

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Constant -8.50235

Std Err of Y Est 0.088236

R 0.991049

No. of Observations 9

Degrees of Freedom 7

X Coefficient(s) 1.207463

Std Err of Coef. 0.043373

Shape parameter, b = X coefficient = 1.207463

hb nl = 8.502351 (Constant)

hnl = 7.041499

h = 1143.099From Table 5.2 the values of the Weibull parameters were

obtained:

h = 1143.1

b = 1.207

g = 0Using the Weibull parameters obtained above the

following typical calculations are now possible:

Reliability at certain life

%1414.0)0002(

1.143100002

)0002(

)(

207.1

==

-=

-=

-

-

R

eR

TeTR

b

hg

In terms of our model of five allowable kidney shapeddefects per km the rail will after carrying 2000 mgt have a 14%reliability; i.e., only 0.14 x 5 = 0.7 defects per km will beallowable or 4.3 defects per km will already exist.

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Failure rate at a certain life

( )

( )

kmperMGTperdefectsfailures

TT

/00111.0

1.114301500

1.1143207.1

)1500(

)(

1207.1

1

=

-=

-=

-

-

l

hg

hb

lb

When a certain defect level will be reached

Should it be decided to start ordering rails when defectshave reached a level of 4.5 defects per km:

207.1

1.114302280

1

1

%900.55.4

)(

--=

--=

==

-

-

e

Te

TF

b

hg

(By means of replacement of T in computer model).

= 0.90 = 90%

This means that the defect level of 4.5 defects/km will bereached by the time 2280 mgt has passed over the rail.

Further refinements to this model by for instance addingconfidence limits is possible.

5.2.6 Modes of Rail TestingAn effective rail test is one in which all defects which couldpresent a hazard to the safe passage of trains, at the time oftesting and projected forward to the time of the next test, arelocated and sized to an accuracy that permits a valid decision tobe made on its removal. A skilled test operator can perform areliable test at a spot location with hand probes within a fewminutes. The problem is in knowing where to look for thedefect. The solution is to use a machine to locate potentialdefects at speed.

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Thus, there are two distinct components to rail testing:

1. Location of defects by machine.

2. Description of defects by the operator.

The basic elements that are necessary to ensure that adefect is correctly located and identified are:

1. The equipment used for detection must represent thesize of the defect sufficiently accurately to produce arecognizable indication(s) on the operators displayunder all rail surface conditions that could beexpected.

2. The indication presented to the operator must beclearly identifiable as a rail defect.

3. The operator must have sufficient training, experience,and vigilance to respond to a defect indication withvery high reliability and to correctly perform handtesting to identify the defect.

The two aspects of detection, involving machine andoperator, explains why rail testing is carried out in a variety ofways:

Non-stop hand testing, where an operator pushedtrolley-mounted equipment along at a walking pace and carriesout a pedestrian sweep, stopping to explore and confirmindications. This offers the advantage that the information ispresented to the operator at a slow speed and he may performa simultaneous visual check of rail surface conditions. Themajor disadvantage is the high cost per test kilometre due toslow test speed and the need to test each rail separately.

While some railways still do out-of-face rail testing withultrasonic hand trolleys, their use is waning due to high laborcosts, the need for a chase vehicle anyway to regularly rechargewater supplies and safety considerations. Therefore, furthercomments will focus on flaw detection by vehicle.

Stop and confirm machine testing, where the testvehicle stops at each indication and the hand operator gets outto verify and mark the defect.

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Advantages are: Less sophisticated equipment means lower capital

cost.

Rail is marked for renewal at detection.

Detection can run in sync with rail repair.

Test vehicle may be hi-rail equipped, increasing itsflexibility to move between sites over roads and to seton and off track at road crossings.

Disadvantages are:

Slower operation than non-stop testing.

Test equipment may have to run under rules for trackequipment to permit backup moves.

Crew of hi-rail equipped ultrasonic cars must travel toother lodging.

Non-stop machine testing, where a multi-probe machinetravels the section at typically 35 40 km/h. Real timecomputing attempts to recognize signal indications, whichcould possibly be defects, and to paint the location for followup hand testing.

Advantages are:

Less interference with traffic.

Lower unit cost of testing.

Higher productivity.

In some territories, signal systems will not allow rail-bound equipment to back up, leaving a long walk ifimmediate verification is required.

Disadvantages are:

Higher capital cost of equipment.

Ultrasonic car may leave behind more defects than canbe fixed in a day, leading to slow orders.

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Longer time interval between detection andverification.

Rail surface fatigue can cause excessive indications.

Real time detection by computer must necessarily beconservative leading to a tendency to paint too muchrail.

Hand test results are not available to recognize forrecalibration..

Tandem machine testing is a variation on non-stoptesting. In this approach, a chase vehicle working in thesame track possession follows the principal testing vehicle.The led test car works non-stop as fast as the rail condition willallow, while the satellite car regulates its average speed, stopsincluded, to match the site advance. This method is capital-intensive, but addresses many of the disadvantages of non-stoptesting.

5.2.6.1 Rail Testing EquipmentVarious types of non-destructive methods have been employedfor testing rail in track, the main ones being:

Induction, where a low voltage eddy current is passedalong the rail between two moving probes, inducing astrong magnetic field around the rail. An internal raildefect causes distortions in the field around the rail,which are picked up by search coils (see 5.2.10).Induction methods can detect railhead defects andcertain web defects outside of the joint bar area.

Residual magnetic, where the rail is magnetized, andsearch coils generate a weak current at irregularities inthe rail.

Ultrasonic, where ultrasonic waves are beamed intothe rail and the echoes are studied for irregularities.

As ultrasound is the technology most frequently used byheavy haul railways, future comments will deal with ultrasonicrail flaw detection only.

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5.2.7 Ultrasonic PrinciplesWhile ultrasonic is a very specialized field usually left to theexperts, it is helpful for the railway user to have a grasp of theprinciples involved. The test tool is a beam of electro-acousticenergy with a frequency in the region beyond the hearingrange. The beam which can be linked to that of an electrictorch or flashlight is some 20 mm (1 in.) in diameter at itsorigin and diverges from cylindrical at 35 degrees. The beamis pulsed switched on then off at a set distance along therail, usually 2, 4, or 5 mm.

Ultrasonic transmitter crystals may be fitted in slidingshoes or in rotating wheels. The sliding shoes are in closercontact with the rail and afford a good angular stability, as themounting is flexible and adaptable. The wheel probes dealbetter with irregular rails and offer a broad base for scanningthe railhead. A combination of both systems exist on somemachines.

Like light, the transmitted ultrasonic energy is refractedupon changing from medium to medium, and reflected uponmeeting a suitable surface that is roughly perpendicular to itspropagation. In the flaw detection operation, two phenomenaare of interest. A beam hitting a discontinuity can reflect backand disclose an appearance that indicates a potential defect.And a beam masked from an expected end-echo cannot reflectback, and thus gives a disappearance that indicates apotential defect.

In practice, one is looking for various types of defects,each with its own characteristics. The major characteristicdistinguishing different defect types will be the defects planeof propagation. Thus, a transverse defect will be situated on aplane across the railhead and sloping at some 70 to 90 degreesto the vertical, while horizontal split heads and vertical splitheads describe themselves. In order to achieve reflection, thesearch beam must meet the defect plane at about right angles.From here, it becomes clear why rail-testing cars are fitted withseveral probes on each rail.

The beams are centered on the longitudinal axis of the railby mechanical means with reference to the gauge face. As the

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beams descend the web, and cannot radiate out from that path,there are zones in the rail foot hat are not tested by theultrasonic method.

The passage of the ultrasonic energy is not as clean as onewould like. In particular, there is a disturbed zone of about 10mm at the interface between the probe and the rail. Thepassage from one medium to the other is assured by a film ofwater that acts as a couplant. Nevertheless, the first severalmillimetres of the entry into the rail cannot be exploited.Other parasite effects occur also. Thus the first stage in therecovery of the test information is to filter the returning energyto remove the misleading effects. The second stage is to setadjustable gates to select the areas in the rail that are ofinterest.

At this point, the energy reflected can be visualized on acathode ray oscilloscope, an illustration referred to a an A-scan.Defects will be recognizable from a set shape of theoscilloscope trace. They are said to have a signature.

In principle, this information suffices to locate potentialdefects. In practice, the traces are lively and require greatattention for interpretation, and there are simultaneouslyseveral channels of information for each rail. The problem isnow one of information technology to assure the recognitionof potential defects among the mass of tested data that willflow through the system. For example, some 10 informationpoints are generated every few millimetres along the rails, whiletravelling at 15 25 km/hr. Another visual aid may be apictogram. Known as a B-scan, this is a picture of a railsection, with diode lights or computer graphics given a "quickglance view of suspicious echoes. An audio tone signal cangive a supplementary indication.

All of the above indications are usually presented to theoperator in real time, but are usually stored on a multi-channelline recorder for later consultation in cases of controversialfindings.

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5.2.8 Inspection EffectivenessRail flaw detection reliability is a system in which totalreliability is the joint result of the performance of test probes,data processing clarity of information displays to the operator,the operator himself, and the management of rail testingintervals. Where there is a weak link in the system, it must becompensated by the other elements of the system.

For example, weak performance from the ultrasonicprobes can be compensated somewhat by more sophisticatedprocessing. Or overly complicated or confusing informationdisplays must be compensated by an experienced operator.Most importantly, poor overall performance from rail testingcan be compensated somewhat by very frequent testingintervals.

The following discusses some of the factors affecting rail-testing reliability.

5.2.8.1 Test ProbesTo locate an internal defect in rail, ultrasonic or inductionenergy must be transmitted along a pathway and at an energylevel sufficient to produce a clearly anomalous reflection fromthe fracture surface. This reflection must be distinguishablefrom the base of the rail itself and from railhead surfaces, andthe signal received from the fracture surface must besubstantially greater than the overall noise level introduced bythe grain structure of the rail or from the probe itself. And thesignal received must be sampled sufficiently frequently to havecaptured sufficient pulses or echoes to have seen thedefect.

Fortunately, the larger the defect, the greater the signalreflected. The difficulty arises in the detection of thresholddefect sizes. The pulse count from a small transverse defect,for example, can be very similar to the noise floor,particularly in older, less clean rail steels.

Furthermore, the full size, or length of the defect, is almostnever seen. This is because the full size of the defect is onlyseen if it happened to be oriented at exactly 90 degrees to oneof the search beams. As there are an infinite number of

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possible defect orientations and a finite number of probeorientations, this is rare. What is usually seen as the reflectingsurface is therefore the projection of the fracture surface ontothe plane of the probe.

True sizing of the defect only occurs when the defect islinear and oriented at 90 degrees to one of the search beams,As there are an infinite number of defect orientations and afinite number of probe orientations, this is rare. In theexample shown in Figure 5.6, a 32 mm (1-1/4 in.) curvilinearbolt hole crack emanating at 45 degrees from the bolt hole isseen as a 25 mm (1 in.) defect by the ultrasonic probearrangement. A particular problem is experience in those rarecircumstances where the crack emanates vertically from thebottom of the bolt hole. This type of crack is susceptible topull-apart, but is transparent to the 0 degree probe and under-represented by 43% by the 35 probe.

Figure 5.6: Length of a Bolt Hole Crack 32 mm Long andGrowing at 45 as seen by 35 and 0 Ultrasonic Probes

Another example of undersizing by ultrasonic occurs whendefects are located in the extreme corners of the railhead, theinitiation point for detail fractures from shell (Figure 5.7).7 8Here the problem is due to the diverging angles of theultrasonic beam. A centrally-located ultrasonic beam, 20 mmthick and diverging at 35 degrees, is unable to illuminate theparts of the crack surface near the gauge corner and in the

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head-web fillet area. Flaws larger than 65% of the head areaare therefore characteristically undersized. This can becounteracted to some degree by the addition of 70 degreeprobes on field and gauge side, but the lateral separation ofsuch probes is constrained by the possibility of taking airwhen encountering a severely worn rail gauge corner.

Figure 5.7: Illustration of Characteristic under Sizing of a LargeTransverse Defect by a Single 70 Ultrasonic Probe

5.2.8.2 Signal ProcessingThe electronic signals received by the test probes must beadjusted to discern a recognizable signal, while eliminatingspurious noise. Signal processing may affect overall testingreliability if filters are not adjusted to recognize returning signalthresholds that could constitute valid defects. For example,processing logic that does not lower the threshold level fordefects found deeper in the railhead whose reflected energywill be less than a shallow defect, would potentially misssmaller defects deeper in the rail.

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5.2.8.3 Displaying Indications to the OperatorMost testing systems use a gating logic whereby an ultrasonicecho is divided into reflections from head, web, base, andpossible defect. An indication of a potential defect ispresented to the operator only if sufficient signal pulses orechoes have been received within a time interval that wouldconstitute the defect zone. System test reliability dependsupon the successful definition of the time interval throughwhich echoes from the probes should be counted as anindication of both the presence and size of a defect.

Recent developments have also sought to assist theoperator by recognizing patterns typical of rail ends, bolt holes,bond pin drillings, etc. The objective is to present to theoperator only those patterns, which cannot be, explained bytypical track features. This prevents the operator from beingflooded with information that he must mentally process.

5.2.8.4 Operator VigilanceCurrent testing systems continue to be operator sensitive. Theideal operator can maintain mental vigilance over extendedperiods of time, using his training and experience to identifysuspicious pen indications or patterns, in spite of variousdistractions within the test car. Such operators exist, but thereare an equal number of excessively conservative operators whofrequently stop and hand test and may mark a rail forunnecessary removal where they do not recognize the patternof indications. On the other hand, some operators areproduction-oriented, or are perhaps too quick to attributeunusual indications to a rail surface condition. Operatorperformance should be reviewed regularly be selecting randomsamples of recorded signal indications, ideally in territorieswhere the number of detected defects has changed dramaticallybetween tests. These recordings should be reviewed with theoperator to locate areas where he may have missed a potentialrail defect.

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5.2.8.5 Estimates of Rail Testing ReliabilityThe effect of defect size on the probability of finding a defectis well illustrated in Figure 5.8.8 It was compiled by theTransportation Systems Center and the AAR, and is anassessment of typical testing capabilities of current contractorsequipment. The AAR model estimates that a defect covering60% of the railhead has a 90% chance of detection in a giventest. At the same time, a flaw covering 10% of the head islikely to have a probability of detection of only 45%.

Figure 5.8: Estimated reliability of conventionalrail test equipment

The American Railway Engineering Association is moredemanding in their recommended minimum performanceguidelines for rail testing. These guidelines, summarized asTable 5.3,9 define the minimum acceptable percentage ofdefects that must be detected by a single ultrasonic test. Thedetection rate recommended by the AREA as indicative of afair to good ultrasonic inspection varies with the type of defect,its size range and the class of track. For example, the AREArecommends that rail testing services be considering to beoperating below acceptable performance if more than 65% of

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transverse defects in the 5-10% range go undetected. On theother hand, 98% of transverse defects covering 60% of therailhead must be correctly identified and marked for removal.The specification also defines the minimum sizes of defectsthat are considered both worthy of reporting and within thesize range for reliable detection.

Such a specification invites questions to as how therequired testing performance can be verified. The best methodis to have a section of test track containing defects of knowsizes. This tests the capabilities of the test equipment, but isnot a realistic test of the vigilance of the operator in normalservice. Some railways run tandem tests where two test carswill alternate running in the trailing position.

Defects found by one test car and operator and not theother, after verification by breaking open or lab inspection,would be considered missed defects for the purpose ofverifying performance to the specification.

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Table 5.3: Minimum Performance for Rail Testing

Defect TypeSize

(Length or % of head Area)

Reliability Ratio (% of suchdefects properly indicated as

flaws in any single test)

Category I II

5-10% 65% 55%

11-20% 85% 75%

21-40% 90% 85%

41-80% 98% 95%

Transverse Defects in the RailHead eg. transverse fissurecompound fissure engineburn/welded burn fracture

81-100% 99% 99%

10-20% 65% 55%

21-40% 85% 75%

41-80% 95% 85%Detail Fracture from Shellingor Head Check

81-100% 98% 95%

3-5% 65% -6-10% 75% 65%11-20% 85% 75%

21-40% 90% 85%

41-80% 95% 95%

Defective welds Plant Welds (Head)

81-100% 99% 99%

12-25 mm 75% 65%

25-50 mm 95% 90%- Plant Welds (Web)

more than 50 mm 99% 95%

5-10% 75% 65%

11-20% 80% 70%

21-40% 85% 80%

41-80% 95% 90%- Field Welds (Head)

81-100% 99% 95%

12-25 mm 75% 65%

25-50 mm 90% 85%- Field Welds (Web)

more than 50 mm 99% 95%

50-100 mm long 80% 70%

100 mm - 1 m 95% 95%Longitudinal Defects in theRail Head eg. horizontal splithead vertical split head

more than 1 m 99% 99%

Web Defects * eg. head andweb separation split web

50-100 mm 95%90%

more than 100mm

99% 95%

Piped rail more than 200mm any

85% -

Any size with non vertical orientation,evidence of bulged web or progression into weld.

85%75%

12-25 mm 75% 65%

25-50 mm 75% 65%

50-100 mm 90% 85%

Web Defects inJoint Area *eg. bolt hole crackhead and web separation more than 100

mm99% 99%

* defects must have progressed more than halfway through the web.

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5.2.9 Selecting Rail Testing IntervalsIt can be seen from the above that management of rail testingincorporates two abstract disciplines:

Risk management: an outlay of known preventioncosts to achieve a hypothetical reduction in theprobability of damage.

Statistical performance: the evaluation of detectionsuccess rates in relation to probability tolerances.

Furthermore, the subject matter is not definitive. Thegrowth rates of known types of defects are not narrowlypredictable. There are sources of rail breakage that are clearlynot predictable, such as defects in the rail foot, and there arerandom events such as infrequent but significant impacts fromwheel defects.

The well documented defect growth experience of theFAST Heavy Tonnage Loop presents a unique opportunity toexplore the theoretical relationship between rail testingfrequency and the possibility of a service break. For illustrativepurposes, assume that the 11 defects shown in Figure 5.5represents the full population of defects initiated and growingover a one year period in a 20 km line carrying 40 million grosston annually. Based upon practical experience, it can furtherbe assumed that a transverse defect left in track with a sizegreater than 60% could represent a significant risk of suddenfracture, and that it would be the objective of ultrasonic testingto prevent this eventuality.

It can be seen that in the absence of testing, from 13 ofthese defects could be expected to have covered more than60% of the railhead by 20 million gross ton of accumulatedtraffic; 24 more would reach this threshold by 30 milliongross ton. By the time 40 million gross ton had passed overthis rail, it could be speculated that two broken rails wouldhave been experienced, representing a 1 in 100 chance of abroken rail derailment using U.S. average statistics.

This case study can be used to illustrate the reduction inrisk that can be expected with rail testing. For example, iftesting at 9 million gross ton intervals (10 mgt), the rail flaw

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detector car would pass over the defect identified with theasterisk at the time when it would cover 23% of the railhead.According to AREA specs in Table 5.3, it would have a 90%chance of detecting and marking this defect for removal. If thedefect were missed and the flaw detector care were to againpass over the site at 13 million gross ton (15 mgt), the flawwould now cover 55% of the railhead and should be detectedwith 98% probability. The net probability of detecting thisparticular defect before it reaches the 60% size is thereforecalculated as 0.90 + 0.10 (.98) = 0.998. Of course, this makesthe perhaps gross assumption that there is no particularrecurring condition that is preventing detection.

Using this same methodology, one can calculate the neteffect of different test intervals on the probability that one ofthese defects will reach the 60% level before being detectedand marked for removal. Using the AREA MinimumPerformance Guideline as an assessment of the typicaldetection performance of the test car, the results shown inTable 5.4 are obtained for the year.

Table 5.4: Effect of Test Interval on Expected Number ofUndetected Defects in a Hypothetical 20 km Line with

Transverse Defect Growth Rates as Measured in the FASTHeavy Tonnage Loop

Test Interval Expected No. of Defects thatwill reach the 60% Level

Undetected

36 mgt (40 mgt) 11

18 mgt (20 mgt) 0.700

9 mgt (10 mgt) 0.234

4 mgt (5 mgt) 0.004

It can be seen that the probability of leaving a transversedefect undetected to a size representing a high risk of failure isvery dependent upon the testing frequency. Again, thisassumes that the probability of success is independent fromtest to test. On the surface it would appear that very frequentrail testing is economical, but there is a case of diminishingreturns.

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Assume for example that it costs $2,500 to replace a raildetected behind a rail flaw detector car costing $50 for the test.An emergency replacement, on the other hand would involvedelay of trains and could cost $10,000 per occurrence. Fortransverse defects, perhaps 1% of service failures may beexpected to lead to derailments costing an average of $400,000.Using these cost numbers, the value of the different testintervals can be calculated from the above probabilities for thehypothetical 20 km. The results are tabulated in Table 5.5.

This example would indicate an optimal testing interval of518 million gross ton, with 9 million gross ton as potentiallythe most economical.

To illustrate the value of reliable testing, assume that a railflaw detector vehicle is used that does not meet the AREAPerformance Guidelines, but instead performs as predicted byFigure 5.9. When testing for defects in this line at 9 milliongross ton (10 mgt) intervals such a car would be calculated toleave an expected 2.02 defects that would progress to the 60%level. A comparison of the economics of the two vehicles isincluded as Table 5.6.

Table 5.5: Economics of Test Frequency in a Hypothetical LineAnnual Cost of Defect

RepairsTest

IntervalCost ofTestingper year Detected Service

ExpectedAnnual

Broken RailDerail. Cost

Total Costper year

40 mgt $1000 $2500 $111,000 $44,000 $158,500

20 mgt $2000 $30750 $7000 $2800 $44,550

10 mgt $4000 $31915 $2340 $936 $39,191

5 mgt $8000 $32490 $40 $16 $40,546

Figure 5.9: Decision Matrix to Direct Risk Reduction

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Table 5.6: Economics of Rail Testing Performance in a HypotheticalLine at 9 mgt Testing IntervalAnnual Cost of Defect

RepairsSpecificationDefining CarPerformance

Cost ofTesting

peryear

Detected Service

ExpectedAnnual

Broken RailDerail. Cost

TotalCost per

year

AREMA $4000 $31915 $2340 $936 $39,191

TSC/AARModel

$4000 $27443 $20,228 $8092 $59,763

This example calculates that the less accurate test vehiclewould cost this heavy haul line an additional $20,000 each yearin this 20 km line segment, or $1000/km. There is clearlyvalue in maintaining good quality control on testing. In thisexample the difference is chiefly due to the differences in thetesting performance in the 30 60% size. As a generalstatement, if a rail flaw detection vehicle is to be cost effective,it must be very good at detecting defects such as transversedefects in the 30 80% size range, as this likely will representthat last time the defect is seen by the detector car before crackout unless test intervals are exceedingly tight.

5.2.9.1 Performance-Based Adjustment of TestIntervals

In light of the inexact nature of the science, most heavy haulrailways control risk by monitoring the occurrence of bothdetected and service defects.

In North America heavy haul railway practice, risk istypically judged to be sufficiently high to merit tightening testintervals when:

Service defect rates exceed 0.17 service failures/km(0.1 service failures/mi/yr).

Service plus detected rail defects exceed 0.04failures/km/million gross ton (0.06 failures/mi./mgt).

The ratio of service to detected defects exceeds 0.2.

In fact, risk can be the result of track condition that is notmatched to service demand, test intervals that are not matchedto the reliability of testing systems, or both. The appropriate

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course of action can be determined by comparing servicefailure statistics and the number of detected failures.

Figure 5.9 illustrates the decision matrix that could be usedto direct an effort to reduce risk. For example, if servicefailures are exceeding 0.04/km/million gross ton (0.06failures/mi./mgt), it is apparent that the railway property isliving with a significant risk of a broken rail derailment. Theobvious question is whether ultrasonic testing is reliable and isbeing performed frequently enough to find the defects. Shouldit also be the case that service failures represents more than20% of all rail defects recorded, it can be surmised that testingintervals must indeed be tightened as a first step to reducingrisk. On the other hand, if service failure rates are low, butdetected defects are high, it can be presumed that rail testing iseffectively compensating for a track that may have stressproblems or cumulative fatigue damage.

5.2.9.2 A Parametric ApproachIn 1991, Committee 4 of the American Railway EngineeringAssociation developed a quantitative guidance for specifyingrecommended ultrasonic testing intervals. The emphasis wasnot on specifying the intervals themselves, but on illustratinghow different railways have perceived the relative effects ofdifferent parameters on risk, and hence the resultant testinterval.

The results represent the experience of two major USrailroads that have developed inspection interval planningequations. The multipliers suggested to account for differentconditions are given in Table 5.7:

Table 5.7: Inspection Multipliers per ParameterSignificant Parameter Parameter Range Inspection

IntervalDecrease

Annual Tonnage Rate 10:1 ratio increase 70-80%

Track Class (as defined bymaximum allowable freight

speed)

U.S. FRA Class 1 to 6(16 km/h 133 km/h

60%

Existence of PassengerTrains

vs. exclusive freightline

50%

Rail section Size 68 kg/m vs. 45 kg/m 70%

Prior Rail Defect Rate 10:1 ratio increase 50-70%

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5.2.9.3 Cluster TestingWhen addressing the risk of a rail-caused derailment, it is wiseto look at the rail plant comprising a routing as a series ofshorter sections of track, with different defect-producingpotential. In older railway lines, lack of homogeneity is anatural result of the relaying of sections of track in differentyears, resulting in rails with different accumulated servicetonnage.

Curved track also generally produces more defects due tothe additional stresses imposed by lateral loading. This occurseven if the sections of track has rail with the same accumulatedservice tonnage with uniformly good track support conditions.

Finally, variations in track and sub-grade supportconditions, rail metallurgical cleanliness and rail weld qualitycan have profound influences on defect occurrence rates. Asan example of the impact of metallurgical cleanliness in theperiod 1972 1980, Canadian Pacific Rail found that fully 38%of transverse defects had occurred in rails from the A or topposition of the ingot, which potentially has the greatest densityof non-metallic inclusions. A ingot rails would haveconstituted only 18% of the population of rails in track.8

It follows then, that the greatest risk reduction pay-offfrom rail testing will result from tests in those locations withhigher defect occurrence rates. The practice of schedulingadditional tests in high defect locations is called clustertesting. To reduce the additional cost of testing intervalsgoverned by high defect locations, rail-bound rail testing carsmay deadhead without testing over intervening track segmentswith acceptable defect occurrence rates.

Many railways schedule cluster testing on the basis ofsome known characteristic of track. For example, a highcurvature section of an otherwise tangent routing might receivean extra test, as could a length of older rail, or jointed railwithin a continuous welded rail routing. Other railwaysmonitor service and detected rail failures and schedule testingbased upon the limits of high defect rate locations.

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Hi-rail based cars are particularly adapted to cluster testing,where road access and frequent level crossing permit easyaccess to spot locations without tying up track in deadheading.

As there is a cost to deadheading between sites to becluster tested, for scheduling purposes, high defect locationsshould be 1020 km in length, with sufficient defectoccurrence rates, when averaged over this length, to trigger theselected threshold for an additional test.

Therefore, when selecting test intervals for a routing, theseshould be somewhat related to the potential for a servicefailure, in turn leading to a derailment. Test intervals shouldtarget specific longer track sections with significantly differentcharacteristics of rail age or quality, rail weight, jointed vs.welded rail, track support quality and curvature. When, aftertailoring testing intervals to these characteristics of track,defect occurrence rates in any homogeneous grouping of trackare still high, an additional test should be performed in theoffending location to control overall risk.

5.2.9.4 Special Care in Special Track WorkThe turnout area represents a particularly difficult area to testdue to change in the cross-section of the rails and castings.This means that the ultrasonic echo will return at a differenttime than expected or that some probes will contact therunning surface at unusual angles. As a further complication,castings have a considerably coarser grain structure than thesurrounding steel leading to different base echoes. As ageneral rule, only the standard rail cross-sections within theturnout area and railway diamonds are effectively tested withflaw detection vehicles.

In at grade crossings, the fouling of the rail surface byroad-borne materials, particularly salt, can obstruct a goodultrasonic indication. This can be overcome by sweeping outthe crossing in advance, slowing down the test and reversing ifan unusual indication is seen. Welds are another problem.Because of the change in grain structure and the fact thatfractures can propagate rapidly from very small cracks or stressraisers, welds are very difficult to test either with ultrasonic orinduction. One possibility is to have automated ultrasonic

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recognition of the weld upset, which could trigger a change inthe signal gain and the use of tighter inspection tolerances.

Most heavy haul railways ensure more careful testingthrough special track work. Some have retained a program ofhand testing, however hand testing typically uses the sameprobes that are used by rail flaw detector cars.

5.2.9.5 Rail Testing Intervals Canadian PacificApproach

Canadian Pacific Rail System uses a risk management approachwhereby rail-testing intervals are adjusted according todifferent categories of risk. The approach used is to firstsegment all tracks into homogenous sections with the sametonnage, weight of rail, type of traffic and rough levels of pastdefect occurrence rates. These segments must be at least 16km (10 miles) long to be practical for an additional test.

The approach is to first select a basic testing interval that isdependent upon tonnage, which is a proxy both for the rate ofaccumulation of fatigue in the rails and the probability that aservice failure will be encountered by a train. As Table 5.8shows, there are six basic testing intervals based upon the levelof tonnage.

The testing interval for each track segment may then beupgraded to the test frequency corresponding to the nexthighest risk class if there is an additional element of riskassociated with the track segment. The factors that will qualifyfor a more frequent risk are:

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Higher Risk Traffic: Line carries passenger trainsLine carries hazardous materials

Lower Standard Rail: Non control cooled rail is being used in alineCarrying more than 1 million gross tonper year 50 kg/m (100 lb/yd.) or lighterrail is being used in a line carrying morethan 2.7 million gross ton/year.50 kg/m (100 lb/yd.) or lighter rail isbeing used in a line where train speedsexceed 67 km/h (40 mph).

Evidence of Rail Fatigue:Detected rail defects exceed 0.7 defectsper km(1.2 defects/mi.) per test

Evidence of LowInspection Effectiveness:Service failures exceed 0.12 failures per

km(0.2 failures per mile) per year.

Table 5.8: CP Rail Testing Standards are Based Upon EightTesting Frequencies

Traffic Density +(mgt/yr.)

Traffic + Rail Type + Defects = Test Class

< 0.50.5 2.72.8 7.27.3 1314 27

> 27

HazardousMaterials

Passenger> 70 km/h

Non Cooled

< 50 kg/m

> 0.7/km/yr.Service/detected ratio > 0.2

5 yrs.3 yrs.2 yrs.annual2/yr.3/yr.4/yr.5/yr.

If any three of the above factors are in evidence in the linesegment, the testing interval is tightened by two classes.Therefore, in the example of Table 5.9, a line carrying 10million gross ton per year would be tested once per year. Butif it carried hazardous goods a well, it would be tested twiceper year. If in addition to this the line was laid with lighterthan 50 kg/m (100 lb/yd) rail and had a service to detecteddefect ratio of 0.25, it would be tested three times per year, orafter every 3 million gross ton of traffic.

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Table 5.9: Test Interval Class is Tightened BasedUpon Risk Factors

Traffic Density +mgt/yr.

Traffic + Rail Type + Defects = TestClass

7.3 13 annual

7.3 13HazardousMaterials

2/yr.

7.3 13HazardousMaterials

< 50 kg/mService/detected

ratio > 0.23/yr.

5.2.10 Induction Measuring PrinciplesThe induction testing technique requires the injection of adirect current into the rail. The current is generally around3600A. The injection takes place through the application oftwo sets of brushes that are placed on the railhead. The spacingbetween the brush sets is of the order 120cm (4ft). The currentflows into the rail through the leading brush set and outthrough the trailing brush set. The rail thus becomes part of anelectrical circuit.

Once motion is introduced, a magnetic field associatedwith the current flow in the rail is induced. The magnetic fieldis the means by which information about the condition of therail is coupled to the sensor unit. The sensor unit is locatedbetween the two sets of brushes. The sensor unit is set up tomaintain a constant lift-off between the underside of the unitand the surface of the railhead. If this is not done, the datarecorded will be noisy and thus very difficult to interpret.

The mechanism by which rail condition is inferred startswith the current. In general for modern rail weights, only thehead and the top part of the web is filled with current. In thepast with smaller rail sections, the whole rail section has beenfilled with current. As the current flows through the rail, if anyfeatures such as a defect block the current path, the currentwill take the shortest possible route to get around theobstruction. This distortion of the current flow will also lead toa distortion of the associated magnetic field. It is this distortionof the magnetic field that is detected by the sensor unit (seeFigure 5.10).

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Figure 5.10: Distortion of Induced Magnetic Field aroundTwo Types of Flaws

The sensor unit itself houses multiple coils or Hall Effectdevices. Often the arrangement is differential in nature to helpkeep the number of false indications down. By differential it ismeant that two identical sensors located next to each otheracross the railhead will be wired together. Thus it is only whenone sensor sees a disturbance and the other doesnt that asignal will be sent to the test system. For example, a rail end isessentially a gross transverse defect, both sensors will see therail end so no signal will be sent to the test system. Atransverse defect will generally only be seen by one sensor, sothe asymmetrical disturbance will send a signal to the testsystem. Multiple sensors are used to allow the detection of allof the components of the field disturbances.

Considering the current flow through the rail, as it islongitudinal, current distortion will not occur as a result oflongitudinal features in the rail. The features that will producethe most current disturbance are those that are transverse inthe railhead. Unlike the ultrasonic technique, the inductiontechnique does not have trouble with inspecting right to thetop surface of the railhead. The nature of the current flow is

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such that it is the very center of the railhead that is likely to bemissed if the system is unable to fill the railhead with energy.

The signals sent to the system are generally observed todetermine if they exceed a set threshold. If they do, a count isstarted. The number of threshold exceedances then determineswhether the data is presented to the inspecting operator as apotential defect or not. With increasing computer power newanalysis algorithms, some combining information fromdifferent channels (both induction and ultrasonic), arebecoming more common.

The data can be presented in many different formats. Mostoften it is a combination of processed (counted) data and rawanalog data side-by-side. The processed data is often themechanism that highlights the problem area and then thesubtle features of the indication can be extracted from theanalog waveform.

5.2.11 ConclusionWhile recent research has provided some clues to assessingrisk, it is not yet possible to develop a solid mechanisticrelationship between the risk of derailment and the frequencyof tests. To control the likelihood of service failures, rail caneither be tested very frequently with lower accuracy equipment,as it will be likely that the rail is scanned while the defect islarger and more easily detectable. Alternatively, a moreaccurate test system can be employed on a longer cycle, as it islikely that even if the test happened to coincide with the earlyappearance of the defect it will still be detected. In fact, heavyhaul operators have found that the costs of poor servicereliability are such that it is profitable to both use very effectivetesting systems, with particular emphasis on high reliability indetection of larger defects, while also maintaining frequenttesting.

5.3 Rail Wear Measurements5.3.1 Rail Wear Measurement Techniques

It is true in the rail industry as in any other that What GetsMeasured Gets Managed. A regular program of rail crosssectional/wear measurements is critical to the ability to

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