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Japan : Fujitsu Deep Learning Technology Successfully Estimates Degree of Internal Damage to Bridge Infrastructure.

Fujitsu Limited and Fujitsu Laboratories Ltd. today announced the development of sensor data analysis technology that can aggregate vibration data with sensors attached to the surface of a bridge, and then estimate the degree of the bridge's internal damage through the application of "FUJITSU Human Centric AI Zinrai technology," Fujitsu's approach to artificial intelligence. This technology was validated using data obtained from verification tests of fatigue degradation of bridges(1) carried out by the Research Association for Infrastructure Monitoring System (RAIMS)(2), a mutual aid organization that carries out joint research into technologies used in industrial activities. In this way the technology enables enhanced maintenance and management tasks, making it possible to remotely estimate the degree of internal damage to bridge infrastructure. Details of this technology will be announced at the Japan Society of Civil Engineers 2017 Annual Meeting, to be held at Kyushu University on September 11-13, 2017.

As many bridges built in Japan's period of high economic growth continue to deteriorate, the work required to maintain and manage this type of infrastructure has increased rapidly, accompanied by social problems including rising maintenance costs and a shortage of engineers. It is anticipated that these issues may now be resolved through the application of ICT to maintenance and management tasks for bridges and other social infrastructure.


Inspection tasks for bridges are usually performed visually to check the structure for damage. The issue with relying only on information gathered visually, however, is that inspectors can only identify abnormalities or anomalies appearing on the structure's surface, and are consequently unable to grasp information regarding the degree of internal damage. In recent years, in order to advance the use of ICT in these inspections, there have been many trials in which sensors were attached to the surface of the bridge deck(3), using vibration data to evaluate the level of damage. With the methods used until now, accurately understanding the degree of damage within the interior of the deck was an issue.

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Publication:Mena Report
Date:Sep 1, 2017
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