The number of bridges in operation has increased. Along with the increase length time are service, structural safety also decreases. Bridge substructure is a key component bridges, but there few studies on management and identification water bridge damage. Deep learning focus research field target detection, this document lightens YOLO-v4 to achieve precise intelligent determination concrete cr...

Due to the location and environment of Taiwan, the frequency of nature disaster is high and the caused damages to the human life, properties and transportation facilities are serious. Considering the disaster prevention of bridge structures caused by earthquake, scour, debris flow, corrosion and senescence, literatures involving the developed bridge management information systems and the bridge...

In the research project “KBE4Infra”, knowledge-based engineering (KBE) techniques for capture, storage and reuse of engineering knowledge in bridge engineering are investigated. A rich data source of bridge engineering knowledge, are Bridge Management Systems (BMS). The work present addresses the question, whether it is possible to gain knowledge by the use of data in bridge management systems ...

This paper introduces the outline of a bridge management strategy based on the prediction of future bridge reliability using a semi-Markov deterioration model. This approach applies equally well to single bridges and to a whole network, and is expected to be implemented in the Bridge Management System (BMS) of the Autonomous Province of Trento (APT). More in detail, the model assumes the lifesp...