Manager of railway division of Roadscanners Oy
Multi-Source Railway Condition Data Analysis for Optimized Track Maintenance Decisions
Allocation of funding and planning of appropriate track maintenance actions are of vital importance to maintain track geometry at the necessary service level. Railway networks around the world are experiencing increased traffic, heavier axle loads, and seasonal related changes, along with diverse transport needs for freight and passenger trains. This is causing an immense burden on railway substructures. Simultaneously, budgets and track times for maintenance and rehabilitation work have been decreasing. Optimized track maintenance and rehabilitation decisions are a key to successful management of track condition and life-cycle costs.
This talk discusses experiences with an innovative method developed for effective track rehabilitation and maintenance planning. The method utilizes multi-source information including the track’s functional performance on the rail level, properties of the track environment, and structural conditions below the surface. Data analysis with combined multi-source information results in more accurate and detailed maintenance decisions. Track maintenance budgets can be allocated properly based on improved knowledge of necessary maintenance combined with the known condition of the railway network.
Would you like to read more? Read the full interview with Mika Silvast.
Mika Silvast is a manager of railway division of Roadscanners Oy in Finland. He holds a Master of Science in Geophysics specializing in non-destructive testing of construction materials and subgrade soils. Mr. Silvast has 20 years of international experience on infrastructure surveys and research utilizing ground penetrating radar (GPR) method. He has published several papers on use of GPR and other NDT methods in railway structural investigations. Mr. Silvast has had extensive cooperation with the Tampere University of Technology and Finnish Transport Agency in researching and developing GPR assisted technology in railway structural problem diagnosis and maintenance planning.