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ARTIFICIAL INTELLIGENCE ENHANCED STRUCTURAL HEALTH MONITORING FOR EVALUATION OF TIME-DEPENDENT STRUCTURAL PERFORMANCE OF AGEING RAILWAY BRIDGES

CORDIS · observation · Publication date unknown

ARTIFICIAL INTELLIGENCE ENHANCED STRUCTURAL HEALTH MONITORING FOR EVALUATION OF TIME-DEPENDENT STRUCTURAL PERFORMANCE OF AGEING RAILWAY BRIDGES The aim of the present proposal is to develop an innovative Artificial Intelligence Enhanced Structural Health Monitoring (AIESHM) for evaluation of time-dependent structural performance of ageing railway bridges. This includes a sustainability and resilient-based asset management framework, which leads to significantly reducing the CO2 emission. The proposed AIESHM system, is used to identify the damages in order to prevent the failure or temporary closure, which could lead to loss of lives and additional costs namely construction of new bridge, slow down transportation rate and heavy traffic. This monitoring system will be (a) cost-effective, timely and accurate, (b) detectable for various types of damages, (c) reducing the CO2 emission (d) imp

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recordType

award

status

SIGNED

region

EU

value

276187.92

unit

EUR