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15 November 2017 TWT transmitter fault prediction based on ANFIS
Mengyan Li, Junshan Li, Shuangshuang Li, Wenqing Wang, Fen Li
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Proceedings Volume 10605, LIDAR Imaging Detection and Target Recognition 2017; 1060547 (2017) https://doi.org/10.1117/12.2296313
Event: LIDAR Imaging Detection and Target Recognition 2017, 2017, Changchun, China
Abstract
Fault prediction is an important component of health management, and plays an important role in the reliability guarantee of complex electronic equipments. Transmitter is a unit with high failure rate. The cathode performance of TWT is a common fault of transmitter. In this dissertation, a model based on a set of key parameters of TWT is proposed. By choosing proper parameters and applying adaptive neural network training model, this method, combined with analytic hierarchy process (AHP), has a certain reference value for the overall health judgment of TWT transmitters.
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Mengyan Li, Junshan Li, Shuangshuang Li, Wenqing Wang, and Fen Li "TWT transmitter fault prediction based on ANFIS", Proc. SPIE 10605, LIDAR Imaging Detection and Target Recognition 2017, 1060547 (15 November 2017); https://doi.org/10.1117/12.2296313
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KEYWORDS
Transmitters
Neural networks
Radar
Fuzzy logic
Fuzzy systems
Systems modeling
Data modeling
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