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基于云-神经网络的液体火箭发动机故障检测方法 被引量:18
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作者 黄强 吴建军 《国防科技大学学报》 EI CAS CSCD 北大核心 2010年第1期11-15,共5页
根据故障检测原理,研究和实现了基于云-神经网络的液体火箭发动机故障检测方法。根据训练结果、测试结果和故障检测结果可以看出,云-神经网络用于液体火箭发动机的故障检测是可行的,经过历次试车数据验证,该方法没有误报警和漏报警。
关键词 模型 云-神经网络 液体火箭发动机 故障检测
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3D Ice Shape Description Method Based on BLSOM Neural Network
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作者 ZHU Bailiu ZUO Chenglin 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2024年第S01期70-80,共11页
When checking the ice shape calculation software,its accuracy is judged based on the proximity between the calculated ice shape and the typical test ice shape.Therefore,determining the typical test ice shape becomes t... When checking the ice shape calculation software,its accuracy is judged based on the proximity between the calculated ice shape and the typical test ice shape.Therefore,determining the typical test ice shape becomes the key task of the icing wind tunnel tests.In the icing wind tunnel test of the tail wing model of a large amphibious aircraft,in order to obtain accurate typical test ice shape,the Romer Absolute Scanner is used to obtain the 3D point cloud data of the ice shape on the tail wing model.Then,the batch-learning self-organizing map(BLSOM)neural network is used to obtain the 2D average ice shape along the model direction based on the 3D point cloud data of the ice shape,while its tolerance band is calculated using the probabilistic statistical method.The results show that the combination of 2D average ice shape and its tolerance band can represent the 3D characteristics of the test ice shape effectively,which can be used as the typical test ice shape for comparative analysis with the calculated ice shape. 展开更多
关键词 icing wind tunnel test ice shape batch-learning self-organizing map neural network 3D point cloud
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