In-ﬁeld railhead crack detection using digital image correlation Knut Andreas Meyer,Daniel Gren,Johan Ahlström,Anders Ekberg DIC Highlights In-ﬁeld railhead crack detection using digital image correlation Knut Andreas Meyer,Daniel Gren,Johan Ahlström,Anders Ekberg •A novel application of DIC for railhead crack detection is proposed. •Field samples are studied under realistic loading conditions. •The intricate 3D crack network is characterized. In-ﬁeld railhead crackdetection usingdigital image correlation Knut Andreas Meyera,<, Daniel Grenb, Johan Ahlströmband Anders Ekbergc aDivision of Material and Computational Mechanics, Department of Industrial and Materials Science, Chalmers University of Technology, SE-41296, Gothenburg, Sweden bDivision of Engineering Materials, Department of Industrial and Materials Science, Chalmers University of Technology, SE-41296, Gothenburg, Sweden cDivision of Dynamics, Department of Mechanics and Maritime Sciences, Chalmers University of Technology, SE-41296, Gothenburg, Sweden ARTICLE INFO Keywords: Conditioning monitoring Digital image correlation Crack detection Railwaymaintenance SafetyAbstract A signiﬁcant challenge for railway infrastructure managers is to know when and how to maintain rails. Often, the critical missing information is the current health status, in particular information about rail cracks. Therefore, a new method for rail crack detection is proposed. By utilizing a train-mounted camera system, a single measurement train can monitor a large rail network. The system uses Digital ImageCorrelation(DIC)tomeasurethestrainﬁeldsduetorailbendingcausedbythemeasurement train. Promising results are obtained under laboratory conditions. The identiﬁed cracks are correlated totheactualcracknetwork,characterizedbyserial-sectioningmicroscopy. Furthermore,ﬁniteelement simulations show the method’s high sensitivity to crack depths. Knowing the crack depths enable infrastructure managerstooptimizethe railmaintenance. 1. Introduction In2012,theannualcostforrailwayinfrastructuremainte- nanceandrenewalacrossEuropewasestimatedtobebetween 15and25billionEuros[ 7]. Thecostofraildefectsalonein the 1990s was estimated at 2 billion Euros a year[ 3]. This ﬁgureequatestoabout6700 e,onaverage,perkilometerin Europe’s 300 000 km long railway network[ 13]. These costs do not includethe socio-economic costs associatedwith de- lays due to unscheduled repairs. Today, many infrastructure managers do not have suﬃciently accurate descriptions of the damage state in the rails. To mitigate this lack of infor- mation, they need eﬃcient and reliable condition monitoring systems. Manual visual inspection is still commonly used, but it requires highlytrained personnel andis labor intensive. Several methods for automated condition monitoring already exist,withthemostcommonNon-DestructiveTesting(NDT) methods beingultrasonic andeddy-current[22]. Ultrasonic testing can detect relatively large cracks at <Corresponding author knut.andreas.meyer@chalmers.se (K.A. Meyer); daniel.gren@chalmers.se (D. Gren); johan.ahlstrom@chalmers.se (J. Ahlström); anders.ekberg@chalmers.se (A. Ekberg) ORCID(s):0000-0001-7280-4436 (K.A. Meyer); 0000-0002-5128-8951 (D. Gren); 0000-0002-2672-4547 (J. Ahlström); 0000-0002-3219-1855 (A. Ekberg)high inspection speeds. Speeds up to 100 km_h have been reported[8], noting that the accuracy decreases as the operat- ingspeedincreases. Asforthedetectabledefectsize, Marais and Mistry[ 14] were able to ﬁnd cracks with a linear size downto 5 mm. Hence,ultrasonictestingismostlyapplicable toﬁnddeepcracks. However,thesemightbeconcealedby surfacecracks[3]. Eddy-currenttestingcomplementstheultrasonictesting asitcandetectsurfacedefects. Rajamäkietal.[ 20]founda penetrationdepthof 3 mmtobethepracticallimit. However, the resolution decays exponentially with depth. On the other hand, at ideal laboratory conditions, cracks located deeper have been identiﬁed, see e.g. Kishore et al.[ 10] who found cracks at a 5 mmdepth. Similar to ultrasonic testing, high inspection speeds (up to 70 km_h) have been reported in the literature[19]. Inadditiontothetwomostcommonmethodsdescribed above, several othershave been investigated in the literature. Amethodbasedonmagneticﬂuxleakagecouldidentifyartiﬁ- cialsurfacecracksbutwaslessaccuratefornaturalcracks[ 5]. The"alternatingcurrentﬁeld"methoddetectsdisturbances of induced current in a thin layer close to the surface, caused bysurfacedefects. Themethodislesssensitivetothesensor- Meyer et al.: Preprint Page 1of 16 In-ﬁeld railhead crack detection rail spacing compared to ultrasonic and eddy-current testing. Furthermore, quite accuratecracksizes andinclinationscan be measured[ 22]. However, the inspection speed is low (2- 3 km_h)[8]. Another approach is to use the thermoelastic eﬀect that causes a temperature change due to an applied load. Greene et al.[ 6] showed that by using diﬀerential imag- ing, the surface defects becomevisible. As an alternativeto applying a mechanical load, other heating sources, such as eddy-current,have alsobeen used[1]. Whilethevariousautomatedapproachesdiscussedabove havemanyadvantages,visualinspectionbyexperiencedstaﬀ isstillacommonapproach. Inspiredbythis,researchershave investigated the use of surface image processing to detect surface raildefects [ 4,25,27,11]. However, thisapproach has signiﬁcant challenges in uncontrolled environments due to,e.g., contaminants onthe rail surface. Digital Image Correlation (DIC) is often employed in mechanical testing to calculate the strain ﬁelds. With this method,acrackisdetectedbythestrainconcentrationdueto itopeningandthusbeforeitcanbeobservedontheunloaded surface[9]. DICcanalsobeusedtoﬁndcracksinconcrete structures,seeMohanandPoobal[ 17]foranoverview. DIC usesdiﬀerencesbetweentwoimagestodetectcracks. Jessop et al.[9] used the diﬀerence between the undamaged and the damaged states. In this paper, however, we consider the diﬀerence between two images at diﬀerent load levels. A passingtrainsubjectstherailtoavaryingbendingmoment. The proposed system is mounted on the train and consists of camerasattwopositions. Hence,thesystemallowsautomatic crackcharacterizationalongarailwayline. Themethodisless sensitivetosurfacecontaminantsthandirectopticalmethods, asthedisplacementsareevaluatedasopposedtothestructure. In fact, surface contaminants may even improve the contrast and hencethe resolution.Thepurposeofthisstudyistoinvestigatethefeasibility ofthisnovelrailcrackdetectionmethod. First,themethodol- ogy for rail crack detection using DIC is described, followed by the analysis and experimental setup used to verify the methodology’sfeasibility. Section 4containstheresultsof thisveriﬁcationusingaﬁeldrailsample. Additionally,Sec- tion5includes ﬁnite element simulations that show how the surfacestrainsmeasuredwithDICareaﬀectedbydiﬀerent crack morphologies. Finally, Section 6discusses the present ﬁndings, theremainingchallenges,andpotentialfutureex- tensions ofthe proposedmethod. 2. Description of the proposed method Rails,sleepersandthegrounddeﬂectsasthetrainrolls over,asillustratedinFigure 1. Theseresultsarecalculated forafreighttrainwitha25-tonaxleloadusingthemethod- ology described later, see Section 5.1. The rail deﬂections give rise to bending moments in the rail. Figure 1shows that the bending moment in the middle of each wagon is ap- proximatelyzero. CameraAcanthentakeareferenceimage, showingtherailsurfacewithoutanappliedbendingmoment. WhenthetrainhasmovedsothatCameraBisinCameraA’s previousposition, Camera Bacquiresan imageof the same area as Camera A’s reference image. This new image shows the surface being aﬀected by tensile strains due to a positive railbendingmoment. Thesetensilestrainscausethecracksto open, see Figure 2. The crack opening cause a displacement jumpoverthecrackmouthleadingtoaninﬁnitestrain. How- ever,inDIC,thestrainiscalculatedbasedondisplacement between points with a ﬁnite spacing. Therefore, the strain illustrated in Figure 2is not a Dirac delta function. If the point spacing is small enough, a high strain concentration is detectedaroundthecrackmouth. Thisstrainconcentration is theproposed crackindicator. Meyer et al.: Preprint Page 2 of 16 In-ﬁeld railhead crack detection Camera B Camera A LwhLcLbLw a 0 2 4 6 8 10 12 14 16 18 20 22 24 26*1:5*1*0:50Deﬂection [mm] 0 2 4 6 8 10 12 14 16 18 20 22 24 26*20*10010 P osition [ m]Moment [kNm] Figure 1:Rail deﬂection and bending moment due to a train passage. Camera A measures the undeformed rail surface while Camera B measures the deformed surface. xuxxx Camera A Camera BM M Figure 2:Illustration of the measured strain around a crack mouth in a rail subjected to a positive bending moment 3. Experimental setup The initial evaluation of the crack detection method con- sistsoftwoexperimentalparts. First,arailsampleismounted inatestrig,subjectedtoabendingmoment,andanalyzedus- ingDIC.Second,thecracknetworksintheexaminedrailpart are characterized by serial sectioning. The investigated ﬁeldsamplewastakenfromtheSwedishmainline(Gothenburg- Stockholm) and has sustained 11 years of traﬃc, correspond- ingtoapproximately 165 MGT . Furtherdetails,includingits chemical composition,aregiven inMeyeretal. [16]. 3.1. Crack detectionusingDIC Tworailﬁeldsampleswereconnectedbythreadedrods, asshowninFigure 3. Twohydraulicallyconnectedcylinders load the samples in 4-point bending. This setupgives a con- stant bending moment in the part of the rail located between the cylinders. The hydraulic pressure was controlled by a manual pump and measured by an electronic pressure sensor. The commercial GOM system relies on a speckle pattern to create a 3-dimensional surface. We applied this pattern by ﬁrst paintingthe railhead black, followed by addinga white speckle. Theobjectivelenstailoredforthesmallestavailable Meyer et al.: Preprint Page 3 of 16 In-ﬁeld railhead crack detection (a) Picture of DIC experiment 720 mm 300 mm 210 mm (b) Schematic of bending ﬁxture Figure 3: DIC experimental setup with the yellow hydraulic cylinders exerting a 4-point bending in the rail samples. ﬁeldsofviewwaschosentoimprovetheresolution. Stitch- ing together eight diﬀerent camera positions (2x4) increased the covered portion of the rail. The strains were measured fortheunloaded