摘要
随着人工智能与武器装备的深度融合协作,雷达智能化运维是武器装备发展的必然趋势,对雷达转台的健康管理是雷达智能运维的关键环节。文中以雷达转台为研究对象,通过分析雷达转台故障特征,建立了多源数据融合的转台健康管理框架,并针对雷达转台设备多状态参数的特点,提出了数据采集项-测点二层状态评估方法,实现了雷达转台健康状态的综合评估。仿真验证结果表明,利用数据驱动的雷达转台健康状态评估模型与数据分析方法,通过对多源数据的实时监测,可实现对状态演化的持续感知分析,为雷达转台的预测性维护提供决策支持。
With the deep integration and collaboration between artificial intelligence and weaponry equipment,the intelligent operation and maintenance of radar systems have become an inevitable trend in the development of military equipment.The health management of radar turntables constitutes a critical part of radar intelligent maintenance.In this paper,taking radar turntables as the research object,a multi-source data fusion-based health management framework is established through comprehensive analysis of turntable fault characteristics.And addressing the multi-state parameter characteristics of radar turntable equipment,a two-layer state assessment methodology encompassing data acquisition items and measurement points is proposed and comprehensive assessment of radar turntable health status is achieved.The simulation verification result shows that the continuous perception and analysis of state evolution can be realized through real-time monitoring of multi-source data by the health assessment model and data analysis approach of the data-driven radar turntable,which provides decision support for predictive maintenance of radar turntables.
作者
张浩博
ZHANG Haobo(The 20th Research Institute of CETC,Xi’an 710068,China)
出处
《电子机械工程》
2025年第2期52-57,64,共7页
Electro-Mechanical Engineering
关键词
雷达转台
健康管理
状态评估
数据驱动
radar turntable
health management
state assessment
data driving
