research-article

Anomaly Detection of Aerospace Facilities Using Ganomaly

Authors:

Tianyuan ChenAuthors Info & Claims

ICMSSP '20: Proceedings of the 2020 5th International Conference on Multimedia Systems and Signal Processing

Pages 40 - 44

https://doi.org/10.1145/3404716.3404730

Published: 08 July 2020 Publication History

Abstract

In the field of aerospace, the abnormal detection of data is of great significance. The rapid and effective detection of abnormal parameters is key to find potential failures of spacecraft. Traditional methods of anomaly detection need much manual labour and material resources but cannot satisfy the requirements of real-time accuracy. At the same time, there are far more normal samples than abnormal samples, and the original classification methods cannot be applied. In this paper, we propose a GANomaly-based framework for anomaly detection of aerospace data. GANomaly is a framework that analyzes the underlying relationships of data using potential space, which is more in line with the characteristics of the payload data and the actual scenarios for anomaly detection. This article compares GANomaly with other anomaly detection methods on the public aerospace dataset and payload dataset respectively. The results show that the GANomaly-based anomaly detection framework has good capabilities for detecting abnormality of aerospace datasets.

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Cited By

Ain QAftab Ahmed Jilani AAzhar Butt NUr Rehman SAbdulrahman Alhulayyil H(2024)Anomaly Detection for Aviation Cyber-Physical System: Opportunities and ChallengesIEEE Access10.1109/ACCESS.2024.349551912(175905-175925)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3495519
Yang ZZhang WCui WGao LChen YWei QLiu L(2022)Abnormal Detection for Running State of Linear Motor Feeding System Based on Deep Neural NetworksEnergies10.3390/en1515567115:15(5671)Online publication date: 4-Aug-2022
https://doi.org/10.3390/en15155671
Li QLuo ZZheng J(2022)A New Deep Anomaly Detection-Based Method for User Authentication Using Multichannel Surface EMG Signals of Hand GesturesIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2022.316416271(1-11)Online publication date: 2022
https://doi.org/10.1109/TIM.2022.3164162
Show More Cited By

Index Terms

Anomaly Detection of Aerospace Facilities Using Ganomaly
1. Information systems
  1. Information systems applications
    1. Data mining
      1. Data stream mining

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ICMSSP '20: Proceedings of the 2020 5th International Conference on Multimedia Systems and Signal Processing

May 2020

112 pages

ISBN:9781450377485

DOI:10.1145/3404716

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Shenzhen University: Shenzhen University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 July 2020

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ICMSSP 2020

ICMSSP 2020: 2020 5th International Conference on Multimedia Systems and Signal Processing

May 28 - 30, 2020

Chengdu, China

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Cited By

Ain QAftab Ahmed Jilani AAzhar Butt NUr Rehman SAbdulrahman Alhulayyil H(2024)Anomaly Detection for Aviation Cyber-Physical System: Opportunities and ChallengesIEEE Access10.1109/ACCESS.2024.349551912(175905-175925)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3495519
Yang ZZhang WCui WGao LChen YWei QLiu L(2022)Abnormal Detection for Running State of Linear Motor Feeding System Based on Deep Neural NetworksEnergies10.3390/en1515567115:15(5671)Online publication date: 4-Aug-2022
https://doi.org/10.3390/en15155671
Li QLuo ZZheng J(2022)A New Deep Anomaly Detection-Based Method for User Authentication Using Multichannel Surface EMG Signals of Hand GesturesIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2022.316416271(1-11)Online publication date: 2022
https://doi.org/10.1109/TIM.2022.3164162
Li HLi Y(2022)Anomaly detection methods based on GAN: a surveyApplied Intelligence10.1007/s10489-022-03905-653:7(8209-8231)Online publication date: 28-Jul-2022
https://dl.acm.org/doi/10.1007/s10489-022-03905-6

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