Radar Equipment Battlefield Damage Assessment And Restoration Expert System Research

Battlefield Damage Assessment and Repair(BDAR) guarantees the weapon system in a high readiness, high attendance rate and the army in continual battling. Especially, in modern battles, the rate of hi-tech weapon's being total destroyed is decreased while that of being partly damaged is increased. Therefore, BDAR becomes more important, and it is necessary to study and analyze its theories, approaches and techniques systematically.After discussing of the current BDAR, the chosen radar's Damage Mode and Effects is analyzed in the paper according to its function structure and fighting mission. And then, an Expert System is presented to assess effectively and intelligently based upon the Bayesian networks.In detail, three knowledge representations, i.e. production rule, frame and Bayesian networks are adopted to express different kinds of knowledge in the Expert System, and forward deduction and Bayesian networks'uncertain reason are combined to accomplish the Expert System inference process. Meanwhile, the radar's threat mechanisms and Damage Mode are analyzed, and a common electrocircuit model is proposed to simplify the network while modeling the Bayesian network. At last, to implement the system, the forward deduction is completed by CLIPS, and SMILE is employed in the modeling and inference process of Bayesian networks, while the above two methods are integrated in whole system by using ActiveX component.