Intelligent monitoring technology for aerospace environment based on time series neural network

Abstract:
With the continuous development of aerospace production and tasks, the actual demand for environmental monitoring in aerospace field, especially the monitoring and early warning of pollutants, is increasing. The traditional aerospace environment monitoring technology has certain shortcomings, such as not enough method, weak adaptability and difficulty in fully mining the potential value of aerospace data acquired. A data-driven intelligent monitoring technology for aerospace environment is designed based on the time series neural network LSTM with automatic feature extraction. The simulation results show that the intelligent monitoring technology for aerospace environment based on time series neural network could automatically extract the sequence features, and the prediction error is reduced by about 10% compared with the traditional monitoring technology, and has higher data utilization and adaptability.