Technology-Based Condition Assessment Framework for Railway Infrastructure

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The condition of railway infrastructure, such as rails, ballasts and sleepers, should always be monitored andanalyzed to ensure ride safety and ride quality for both passengers and freight. Railway infrastructure is hard toassess and monitor in terms of its condition due to various types of infrastructure components. The majority ofthe existing condition assessment models are limited to a specific component of railway infrastructure andparticular inspection technique / technology. Therefore, a comprehensive condition assessment tool should bedeveloped to cover the railway infrastructure components using different inspection techniques to ensure thesafety and quality of public service. This research aims at developing a technology-based condition assessmentframework for railway infrastructure considering structural and geometrical defects in different components.The defects of each component will be identified and studied through literature review and experts opinion inthe field. Two main inputs will be used to develop the model: (1) relative weights of importance ofcomponents, defects and their categories and (2) defects severities. To obtain the relative weights, the AnalyticNetwork Process (ANP) technique will be adopted, which considers the inter-dependencies among componentsand their defects. Fuzzy logic will be used to unify different defects / criteria and to translate the linguisticcondition assessment grading scale to a numerical score for severities. Furthermore, the weighted sum meanwill be used to integrate both the weights and severities to determine the condition and to evaluate the overallcondition of the railway infrastructure. The required data for the present research will be collected from ExpGlobal Inc., railway condition classification manuals, literature and questionnaires distributed to professionalsacross Canada. The fruit of this fusion will also be presented in a user-friendly automated tool using EXCEL.Several case studies from Exp Global Inc. will be selected to prove the concept of the proposed model/systemand validate its results. The proposed model helps asset managers in minimizing the inaccuracy of railwaycondition assessment and prioritizing maintenance, rehabilitation and budget allocation.