| 基于光纤智能夹层和模糊RBF神经网络的飞行器载荷识别 |
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| 引用本文： | 胡兴柳,梁大开,陆观.基于光纤智能夹层和模糊RBF神经网络的飞行器载荷识别[J].南京航空航天大学学报,2009,41(4). |
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| 作者姓名： | 胡兴柳 梁大开 陆观 |
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| 作者单位： | 1. 南京航空航天大学智能材料与结构航空科技重点实验室,南京,210016;安徽工业大学电气信息学院,马鞍山,243002
2. 南京航空航天大学智能材料与结构航空科技重点实验室,南京,210016 |
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| 基金项目： | 江苏省自然科学基金，航空科学基金 |
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| 摘 要： | 为了更好地保障航空飞行器的安全,提高飞行器的可靠性,提出了一种通过性能参数稳定的光纤智能夹层采集数据,并且结合模糊RBF神经网络对机翼盒段载荷进行识别实验的方法.该方法融合了模糊理论和神经网络各自的优点,通过改进的模糊C均值聚类(FCM)聚类算法删除冗余的规则以进行规则的优化,能自适应地从学习样本数据中提取相应信息,实时地进行载荷辨识.从仿真结果可以看出:该网络模型具有学习时间较短、学习速率较快和精度较高等优点.
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| 关 键 词： | 模糊神经网络 智能夹层 初始聚类中心 模糊C均值聚类 |
Aircraft Load Identification Based on Smart Layer of Fiber and Fuzzy RBF Neural Network |
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| Hu Xingliu,Liang Dakai,Lu Guan.Aircraft Load Identification Based on Smart Layer of Fiber and Fuzzy RBF Neural Network[J].Journal of Nanjing University of Aeronautics & Astronautics,2009,41(4). |
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| Authors: | Hu Xingliu Liang Dakai Lu Guan |
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| Institution: | 1.The Aeronautical Science Key Lab for Smart Materials and Structures;Nanjing University of Aeronautics & Astronautics;Nanjing;210016;China;2.College of Information and Electric Engineering;Anhui University of Technology;Ma'anshan;243002;China |
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| Abstract: | In order to ensure the security of the aircraft and improve the reliability of the aircraft,a new method by combining fuzzy theories with neural network is used to identify the loads of the wing-box.Data are provided by the fiber smart layer with a stable performance.An improved fuzzy C-means(FCM) clustering algorithm is used to delete the redundant rule for the optimization.The fuzzy RBF neural network can obtain self-adaptive information from samples to be learned,thus the load can be real-time identified... |
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