基于多信号流图模型的典型无人机测控系统测试性优化设计方法研究  

Optimization Method of Testability Design for Typical UAV TT&C Based on Multiple Signal Flow Graph Model

作　　者：贾占强 梁保卫[1] 王江辉 闫改[1] JIA Zhan-qiang;LIANG Bao-wei;WANG Jiang-hui;YAN Gai(CETC The 54th Research Institute,Shijiazhuang 050081,China)

机构地区：[1]中国电子科技集团公司第五十四研究所,河北石家庄050081

出　　处：《测控技术》2022年第6期26-32,共7页Measurement & Control Technology

摘　　要：针对无人机测控系统维修保障和故障诊断定位的实际需求,引入基于多信号流图模型,建立了无人机测控系统测试性优化设计方法。首先,介绍了多信号流图建模基本思路,给出了多信号流图的建模步骤;然后,结合典型无人机测控系统组成及工作原理,构建了无人机测控系统的多层次多信号流图模型,在此基础上开展了测试性预测和测试性优化设计,总结后给出了工程设计中的关键注意事项。研究结果表明:该方法可以有效提高无人机测控系统的故障检测率和故障隔离率,减小模糊组,优化后系统的测试性设计水平得到了提高,说明了该方法的有效性。According to the actual requirements of maintenance support and fault diagnosis and location of UAV tracking telemetry and command system(TT&C),an optimization method of testability design for UAV TT&C is established based on multiple signal flow graph model.The basic idea of multiple signal flow graph modeling is introduced, and the modeling steps of multiple signal flow graph are given.Combined with the composition and working principle of typical UAV TT&C,the multi-level and multiple signal flow graph model of UAV TT&C is constructed.On this basis, testability prediction and testability optimization design are carried out.The important design experience is summarized in fact.The results show that this method can effectively improve the fault detection rate and fault isolation rate of UAV TT&C,reduce the fuzzy group, and improve the testability design level of the TT&C,which shows the effectiveness of this method.

关 键 词：多信号流图 无人机测控系统 测试性 FMECA 优化设计 故障检测率 故障隔离率 模糊组 

分 类 号：V219[航空宇航科学与技术—航空宇航推进理论与工程]