Abstract
Aiming at the problems of low intelligence and networking in predictive maintenance of military intelligent equipment, and difficulty in physical model modeling, the AI-based military intelligent equipment remote fault prediction and health management system (PHM) implementation framework, key technologies and guarantee decision-making methods are studied.The operating mode of the PHM system is explained in detail, and the software architecture and key technologies of the PHM system are analyzed on this basis. The outstanding features of AI-wide communication, pan-awareness, and self-learning are used to construct the health management of military intelligent equipment that integrates the PHM system architecture. The system realizes data-driven, intelligent and networked guarantee for the health management of military intelligent equipment. This paper provide reference and reference for military intelligent equipment support suitable for complex conditions, reduce operation and maintenance costs, and continuously improve the level of military intelligent equipment support.
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