@inproceedings{ddc5afb9eb6e4bc6a6b78f704a99bba7,
title = "Time Series Prediction Model of Spacecraft Health Management System Based on Wavenet Convolutional Neural Network",
abstract = "In this paper, we introduce the Time Series Prediction Model Based on Wavenet Convolutional Neural Network. This means can give early warning for the future working state and possible faults of spacecraft in advance. As the signal of spacecraft thermal control system belongs to one-dimensional time series, this topic proposes to use the time series model based on WaveNet convolution neural network to predict the time series signal of spacecraft thermal control system and interpret the prediction information.",
keywords = "CNN, Fault diagnosis, PHM, Time series prediction",
author = "Ping Zhang and Xinyu Xiang and Jieren Cao and Chunjian Zhu and Qiang Yuan and Renping Li and Lijing Wang and Ke Li",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 22nd International Conference on Man-Machine-Environment System Engineering, MMESE 2022 ; Conference date: 21-10-2022 Through 23-10-2022",
year = "2023",
doi = "10.1007/978-981-19-4786-5\_38",
language = "英语",
isbn = "9789811947858",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "272--278",
editor = "Shengzhao Long and Dhillon, \{Balbir S.\}",
booktitle = "Man-Machine-Environment System Engineering - Proceedings of the 22nd International Conference on MMESE",
address = "德国",
}