Detecting Anomalies of Satellite Power Subsystem via Stage-Training Denoising Autoencoders
| Autor: | Weihua Jin, Shijie Zhang, Zhidong Li, Bo Sun, Zhonggui Chen |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer science
Noise reduction 02 engineering and technology lcsh:Chemical technology Biochemistry Article Analytical Chemistry 0202 electrical engineering electronic engineering information engineering lcsh:TP1-1185 Electrical and Electronic Engineering stage-training denoising autoencoder Instrumentation satellite power subsystem business.industry Anomaly (natural sciences) Training (meteorology) 020206 networking & telecommunications Pattern recognition Autoencoder anomaly detection Atomic and Molecular Physics and Optics Power (physics) 020201 artificial intelligence & image processing Anomaly detection Satellite Artificial intelligence Stage (hydrology) business |
| Zdroj: | Sensors, Vol 19, Iss 14, p 3216 (2019) Sensors Volume 19 Issue 14 Sensors (Basel, Switzerland) |
| ISSN: | 1424-8220 |
| Popis: | Satellite telemetry data contains satellite status information, and ground-monitoring personnel need to promptly detect satellite anomalies from these data. This paper takes the satellite power subsystem as an example and presents a reliable anomaly detection method. Due to the lack of abnormal data, the autoencoder is a powerful method for unsupervised anomaly detection. This study proposes a novel stage-training denoising autoencoder (ST-DAE) that trains the features, in stages. This novel method has better reconstruction capabilities in comparison to common autoencoders, sparse autoencoders, and denoising autoencoders. Meanwhile, a cluster-based anomaly threshold determination method is proposed. In this study, specific methods were designed to evaluate the autoencoder performance in three perspectives. Experiments were carried out on real satellite telemetry data, and the results showed that the proposed ST-DAE generally outperformed the autoencoders, in comparison. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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