تجزیه و تحلیل داده های پرواز با استفاده از شبکه های عصبی مصنوعی - پهپاد Nishant هند دانلود فایل

تعداد بازدید: ۳۰
توضیح مختصر
Flight Data Analyses of Fiber Optic Based Airworthy Structural Health Monitoring System for UAV using Artificial Neural Networks
توضیحات

 

taking advantage of the multiplexing capability of fiber optic sensors. Successful embedding technologies were also considered [5]. This work presents an advanced smart load monitoring airworthy system, for a UAV having composite tail booms. This is based on an array of FBG sensors, embedded in the tail booms during manufacturing. The system was tested on ground in order to verify its ability to track both static and dynamic boom loading. Structural characteristics like strain distribution kinder static loading, impact response, and normal modes were successfully traced by the system. Meaningful features (such as load) were extracted from the response of the structure during tests by implementing appropriate algorithms. In this study ANN is used as algorithm to estimate loads. The training data for these ANNs was provided by the tests conducted on the tail boom. As a final proof of concept, the system was integrated in the Nishant UAV (designed & developed by ADE, India: Figure 1 ) and was successfully flown. The application of this technology will help in the reduction of Direct Operating and Maintenance cost of the aircraft. 
 

 

تعداد کاراکتر باقیمانده: 500
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