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多元数据融合在无人机结构-健康监测中的应用

何绪飞 艾剑良 宋智桃

何绪飞, 艾剑良, 宋智桃. 多元数据融合在无人机结构-健康监测中的应用[J]. 应用数学和力学, 2018, 39(4): 395-402. doi: 10.21656/1000-0887.380225
引用本文: 何绪飞, 艾剑良, 宋智桃. 多元数据融合在无人机结构-健康监测中的应用[J]. 应用数学和力学, 2018, 39(4): 395-402. doi: 10.21656/1000-0887.380225
HE Xufei, AI Jianliang, SONG Zhitao. Multi-Source Data Fusion for Health Monitoring of Unmanned Aerial Vehicle Structures[J]. Applied Mathematics and Mechanics, 2018, 39(4): 395-402. doi: 10.21656/1000-0887.380225
Citation: HE Xufei, AI Jianliang, SONG Zhitao. Multi-Source Data Fusion for Health Monitoring of Unmanned Aerial Vehicle Structures[J]. Applied Mathematics and Mechanics, 2018, 39(4): 395-402. doi: 10.21656/1000-0887.380225

多元数据融合在无人机结构-健康监测中的应用

doi: 10.21656/1000-0887.380225
基金项目: 工信部民机科研专项资助项目(G011605);中国博士后科学基金(2015M580956)
详细信息
    作者简介:

    何绪飞(1985—),男,博士生(通讯作者. Tel: 021-22321434; E-mail: hexufei1985@126.com);艾剑良(1965—),男,教授,博士,博士生导师(E-mail: aijl@fudan.edu.cn);宋智桃(1966—),男,研究员(E-mail: songzhitao_hd@caac.gov.cn).

  • 中图分类号: V24;O327

Multi-Source Data Fusion for Health Monitoring of Unmanned Aerial Vehicle Structures

Funds: China Postdoctoral Science Foundation(2015M580956)
  • 摘要: 结构健康监测是保证航空器持续安全运行的重要方式,正成为无人机平台研发和适航认证的一项关键技术.针对无人机结构动态监测中的多种不同传感器测量信息,实时提取结构加速度、应变响应信号和模态特征参数,构造归一化的小波包能量变化率指标、应变能变化率指标、模态频率变化率指标与混合损伤评价指标,用于指示结构健康状态.利用多层次数据融合技术进行数据级融合、特征融合以及基于Bayes概率神经网络的决策融合,建立结构损伤程度、位置信息与健康评价指标之间的对应关系,通过粗糙集约简显著降低了特征属性的空间维度,获得关于结构健康状况的一致性决策.通过某型号无人机的健康监测实例验证了上述数据融合技术在识别多种类型传感器输入、多位置损伤识别中的精度,表明多元数据融合在无人飞行器结构损伤识别中的有效性.
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出版历程
  • 收稿日期:  2017-08-08
  • 修回日期:  2017-09-14
  • 刊出日期:  2018-04-15

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