Graph neural network approach for anomaly detection
L Xie, D Pi, X Zhang, J Chen, Y Luo, W Yu - Measurement, 2021 - Elsevier
To ensure the stable long-time operation of satellites, evaluate the satellite status, and
improve satellite maintenance efficiency, we propose an anomaly detection method based …
improve satellite maintenance efficiency, we propose an anomaly detection method based …
MAG: A novel approach for effective anomaly detection in spacecraft telemetry data
B Yu, Y Yu, J Xu, G Xiang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Anomaly detection is a crucial matter to ensure the spacecraft stability. During the spacecraft
operation, sensors and controllers generate a large volume of multidimensional time series …
operation, sensors and controllers generate a large volume of multidimensional time series …
Combining OC-SVMs with LSTM for detecting anomalies in telemetry data with irregular intervals
J Wu, L Yao, B Liu, Z Ding, L Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
To ensure the safety and stability of spacecrafts of which thousands of telemetry parameters
are monitored, fast and accurate response to anomalies or potential hazards is very …
are monitored, fast and accurate response to anomalies or potential hazards is very …
Satellite telemetry data anomaly detection using causal network and feature-attention-based LSTM
Z Zeng, G Jin, C Xu, S Chen, Z Zeng… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Most of the data-driven satellite telemetry data anomaly detection methods suffer from high
false positive rate (FPR) and poor interpretability. To solve the above problems, we propose …
false positive rate (FPR) and poor interpretability. To solve the above problems, we propose …
Improved deep learning based telemetry data anomaly detection to enhance spacecraft operation reliability
L Yang, Y Ma, F Zeng, X Peng, D Liu - Microelectronics Reliability, 2021 - Elsevier
Spacecraft is a complex system integrating a large number of electronic components and
payloads. During the in-orbit operation, abnormal events often occur due to the influences of …
payloads. During the in-orbit operation, abnormal events often occur due to the influences of …
Unsupervised anomaly detection using graph neural networks integrated with physical-statistical feature fusion and local-global learning
C Feng, C Liu, D Jiang - Renewable Energy, 2023 - Elsevier
Efficient and feasible anomaly detection scheme that could utilize data collected by
supervisory-control-and-data-acquisition (SCADA) system is essential for wind turbines …
supervisory-control-and-data-acquisition (SCADA) system is essential for wind turbines …
Imbalanced satellite telemetry data anomaly detection model based on Bayesian LSTM
J Chen, D Pi, Z Wu, X Zhao, Y Pan, Q Zhang - Acta Astronautica, 2021 - Elsevier
Anomaly detection of satellite telemetry data has always been a significant issue in the
development of aeronautics and astronautics. Timely and effective anomaly detection …
development of aeronautics and astronautics. Timely and effective anomaly detection …
Spacecraft anomaly detection with attention temporal convolution networks
L Liu, L Tian, Z Kang, T Wan - Neural Computing and Applications, 2023 - Springer
Spacecraft faces various situations when carrying out exploration missions in complex
space, thus monitoring the anomaly status of spacecraft is crucial to the development of the …
space, thus monitoring the anomaly status of spacecraft is crucial to the development of the …
Telemetry data-based spacecraft anomaly detection with spatial–temporal generative adversarial networks
The telemetry data obtained from an on-orbit spacecraft contain important information to
indicate anomaly of the spacecraft. However, the large number of monitoring variables and …
indicate anomaly of the spacecraft. However, the large number of monitoring variables and …
[HTML][HTML] A method for satellite time series anomaly detection based on fast-DTW and improved-KNN
CUI Langfu, Q Zhang, SHI Yan, Y Liman… - Chinese Journal of …, 2023 - Elsevier
In satellite anomaly detection, there are some problems such as unbalanced sample
distribution, fewer fault samples, and unobvious anomaly characteristics. These problems …
distribution, fewer fault samples, and unobvious anomaly characteristics. These problems …