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Issue DNV awards first class notation and AiP for Data Driven Verification o…

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작성자 최고관리자 댓글 0건 조회 1,603회 작성일 22-08-11 17:47

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DNV has awarded vessel owner, TechnipFMC, its first class notation for Data Driven Verification(DDV) of Dynamic Positioning(DP) systems. In addition, Kongsberg Maritime’s Dynamic Positioning Digital Survey(DPDS) has been awarded an Approval in Principle(AiP) under the DDV notation and was the software system used in the data driven verification process for the DP systems that have been tested onboard Deep Star.
Dynamic Positioning systems are used by offshore vessels for accurate maneuvering, for maintaining a fixed position or for track keeping(pipe/cable laying). These systems require classification which is normally performed via onboard inspections where the surveyor witnesses tests of the DP system and collects the relevant data for assessment by the classification society.
With the DDV class notation the testing of the DP system can now be performed on board more conveniently with the support of the crew and without the need for a surveyor to physically attend. The use of a digital system enables the crew to run test activities and automatically harvest secure and reliable data on the vessel’s behavior. This data can then be verified by the surveyor using a digital playback application.
The DDV class notation sets the requirements for the gathering, treatment, and delivery of collected data to ensure the quality of this data for use in a class assessment. This means that for the specified systems, the verified data can be used in the certification and classification of those systems in maritime and offshore vessels.
The notation enables secure and tamper-free data harvesting to be performed by the crew without surveyors being present onboard. Compared to traditional paper-based test reports, the body of evidence represents an accurate and detailed documentation of test activities, which can be revisited for as long as the data is stored. The notation covers several different verification methods, including self-verifying systems and digital twins.

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