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- W2162417035 abstract "The electric power systems in US Navy ships supply energy to sophisticated systems for weapons, communications, navigation and operation. During battle, various weapons may attack a ship causing severe damage to the electrical system on the ship. This damage can lead to de-energisation of critical loads which can eventually decrease a ship's survivability. It is very important therefore to maintain the availability of power to the loads that keep the power system operational. There exists technology for ships that can detect incoming weapons. This knowledge can be used to determine reconfiguration actions which can be taken before the actual hit to reduce the damage to the electrical system when the weapon hits. Then reconfiguration for restoration can be performed after the hit to reconfigure loads de-energised by the damage from the hit. A new automated probabilistic predictive self-healing methodology to determine such reconfiguration control actions is presented. Implementation of these actions will lead to less damage caused by a weapon hit and can considerably improve a ship's chances of surviving an attack. This probabilistic approach entails three major functions: weapon damage assessment, pre-hit reconfiguration before a weapon hit for damage reduction and reconfiguration for restoration after a weapon hit to restore de-energised loads. A case study is presented to illustrate the new methodology." @default.
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- W2162417035 date "2007-01-01" @default.
- W2162417035 modified "2023-09-24" @default.
- W2162417035 title "Probability-based predictive self-healing reconfiguration for shipboard power systems" @default.
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- W2162417035 doi "https://doi.org/10.1049/iet-gtd:20060168" @default.
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