A Data Driven Approach to A Data Driven Approach to Railway Intervention PlanningRailway Intervention Planning

Derek BartramDerek Bartram

SupervisorsSupervisorsDr. M. BurrowDr. M. BurrowProf. X. YaoProf. X. Yao

ContentsContents

Current TechnologiesCurrent Technologies– StructureStructure– Problems / IssuesProblems / Issues

ProjectProject– AimsAims– Comparison To Current TechnologiesComparison To Current Technologies– System DesignSystem Design

Progress To DateProgress To Date Progress ProblemsProgress Problems

Typical Track DeteriorationTypical Track Deterioration

Angle 1 < Angle 2 < Angle 3Angle 1 < Angle 2 < Angle 3

Geometry MeasurementsGeometry Measurements

Geometry MeasurementsGeometry Measurements

Top heightTop height Web heightWeb height Web thicknessWeb thickness Ballast thicknessBallast thickness Ballast SD sizeBallast SD size Corrugation wavelengthCorrugation wavelength GaugeGauge TwistTwist CantCant

Existing Technologies : Existing Technologies : Decision Support SystemsDecision Support Systems

Expert System : Inference EngineExpert System : Inference Engine

If (ballast_type == granite) If (ballast_type == granite)

then minimum_thickness = 50mmthen minimum_thickness = 50mm If (ballast_type == sandstone)If (ballast_type == sandstone)

then minimum_thickness = 200mmthen minimum_thickness = 200mm

If (ballast_thickness < minimum_thickness)If (ballast_thickness < minimum_thickness)

then replace_ballastthen replace_ballast

Expert System : Inference EngineExpert System : Inference Engine

If (ballast_thickness < 50mm &&If (ballast_thickness < 50mm &&

ballast_type == granite)ballast_type == granite)

then replace_ballastthen replace_ballast

If (ballast_thickness < 200mm &&If (ballast_thickness < 200mm &&

ballast_type == sandstone)ballast_type == sandstone)

then replace_ballastthen replace_ballast

Decision Support Systems : Decision Support Systems : Problems / IssuesProblems / Issues

Expert system only as good as the rule baseExpert system only as good as the rule base

Simplified modelsSimplified models

Possible rule / intervention flawsPossible rule / intervention flaws

Large track segmentsLarge track segments

AimsAims

Improved deterioration modellingImproved deterioration modelling

Improved intervention planningImproved intervention planning

Improved localised fault detectionImproved localised fault detection Improved total life-cycle costingImproved total life-cycle costing

Static Vs Dynamic SolutionsStatic Vs Dynamic Solutions

Static solutionStatic solution Guaranteed good behaviour initiallyGuaranteed good behaviour initially Never improvesNever improves

Dynamic solutionDynamic solution Initial behaviour potentially badInitial behaviour potentially bad Requires high quality existing datasetRequires high quality existing dataset Improves with timeImproves with time

My Project : Assumptions (1)My Project : Assumptions (1)

The various possible faults for track are The various possible faults for track are identifiable by unique combinations of identifiable by unique combinations of

track component deteriorationtrack component deterioration

My Project : Assumptions (2)My Project : Assumptions (2)

For each type of failure, the solution to the For each type of failure, the solution to the problem is not related to other failure problem is not related to other failure

typestypes

My Project : Assumptions (3)My Project : Assumptions (3)

Once a track sections starts failing with a Once a track sections starts failing with a particular failure type, it will continue to particular failure type, it will continue to

fail with the same failure typefail with the same failure type

My Solution : TasksMy Solution : Tasks

Classify the various failure typesClassify the various failure types

Provide a mechanism for classifying unclassified Provide a mechanism for classifying unclassified track sectionstrack sections

Produce a deterioration model for each failure typeProduce a deterioration model for each failure type

Determine best intervention for each failure typeDetermine best intervention for each failure type

My Solution : Data ProcessingMy Solution : Data Processing

Handle missing dataHandle missing data

Segment dataSegment data

Build data runsBuild data runs

Make absolute values relativeMake absolute values relative

My Solution : Failure TypesMy Solution : Failure Types

Plot last data recording of each run in Plot last data recording of each run in

n-dimension spacen-dimension space

My Solution : ClassificationMy Solution : Classification

We know sets of individual data points and We know sets of individual data points and associated failure typesassociated failure types

Failure type does not change until Failure type does not change until interventionintervention

Decision treesDecision trees Evolutionary algorithmsEvolutionary algorithms

My Solution : ClassificationMy Solution : Classification

Decision treesDecision trees

My Solution : ClassificationMy Solution : Classification

Evolutionary AlgorithmEvolutionary Algorithm

My Solution : Work My Solution : Work DeterminationDetermination

For each run in failure type {For each run in failure type {Calculate fitness of subsequent interventionCalculate fitness of subsequent intervention

}}

Calculate average of fitness's for each Calculate average of fitness's for each intervention typeintervention type

Choose intervention with best average fitness Choose intervention with best average fitness

My Solution : Work My Solution : Work DeterminationDetermination

Fitness metricFitness metric

Length of time before next interventionLength of time before next intervention

Next failure typeNext failure type

My Solution : Deterioration ModellingMy Solution : Deterioration Modelling

Simple modelSimple model

Enhanced simple modelEnhanced simple model

Evolutionary model buildingEvolutionary model building

Progress To DateProgress To Date

Classify the various failure typesClassify the various failure types

Provide a mechanism for classifying unclassified Provide a mechanism for classifying unclassified track sectionstrack sections

Produce a deterioration model for each failure typeProduce a deterioration model for each failure type

Determine best intervention for each failure typeDetermine best intervention for each failure type

My Solution : ProblemsMy Solution : Problems

Large number of missing values in geometry Large number of missing values in geometry datadata

Inconsistent / missing? work history dataInconsistent / missing? work history data

Data anomaliesData anomalies

ConclusionsConclusions

Long term improvements over static solutionsLong term improvements over static solutions

Deterioration modelsDeterioration models Intervention planningIntervention planning

CostingCosting

Thank you for listeningThank you for listening

Questions?Questions?