InnoTamp

InnoTamp Currently, accurate geodetic information for track maintenance is only used for high speed lines to ensure optimal ride and safety; the former is not only passenger comfort but low dynamic forces on track and rolling stock, which also reduce their wear and tear. For non-high speed lines it is deemed too expensive and cumbersome (due to safety precautions) to geodetically survey and analyse tracks at regular intervals (monthly/bimonthly). Fugro, in collaboration with Network Rail, proposes InnoTamp: an innovative, cost-effective and safe survey methodology for maintaining positional track geometry (adjusting both rails to the required optimum alignment) even for non-high speed rail lines. Studies have shown that track maintenance cost savings of up to 30% are achievable when accurate geodetic data are regularly utilised. The use of InnoTamp will therefore lead to improved environmental sustainability and customer experience, optimised railway operations as well as optimised and cost-effective track maintenance for Network Rail and other track owners in future. InnoTamp extends the capabilities of Fugro's RILA technology, which has been used by Network Rail since 2013 to generate geodetic data for projects such as electrification and track renewals. This survey system neither requires personnel on track, not a dedicated measurement train. It makes use of regular timetabled revenue earning trains and has proven to be very cost effective. InnoTamp focuses on applying the collected geodetic track data such that track maintenance can be executed efficiently for all lines. It includes e.g. identifying where maintenance is required; for those areas, computing the best alignment and corresponding required track adjustments; checking and proving whether the computed adjustments are practically feasible; uploading the approved adjustments in the computers of on-track maintenance equipment; and finally checking and proving the track changes are implemented correctly. Fugro seeks funding to transition InnoTamp from an R&D concept through to prototype and proving in the areas of cloud computing, algorithm development, machine learning, process automation and application interfaces. In addition, the funding will be used to undertake pilots in (complex) mainline track layouts together with Network Rail, which would be the first in the world.