A graph embedded in graph framework with dual-sequence input for efficient anomaly detection of complex equipment under insufficient samples

Haodong Yan, Fudong Li, Jinglong Chen, Zijun Liu, Jun Wang, Yong Feng and Xinwei Zhang

Reliability Engineering and System Safety, 2023, vol. 238, issue C

Abstract: Real-time anomaly detection is essential for the safe launch of some sophisticated equipment, such as liquid rocket engines (LRE), in order to head off disasters. However, the Industrial Internet of Things (IIoT) edge's real-time requirements cannot be addressed by the present methodologies, and the outcome is poor when dealing with a lack of training samples on the device side. We provide a solution for device-side real-time anomaly detection using the architecture known as Graph Embedded in Graph Networks to address these issues (GG-Nets). To fully extract features under insufficient training data, in our method, we learn the temporal relationship of timestamps in the multivariate signal through a time-series graph attention network (T-GAT) and extract features, and use the extracted features to replace the original signal as the information of the sensor attention network (S-GAT) nodes. For efficiency, the signals in the original sample are divided into odd and even sequences, which greatly reduces the number of nodes in the T-GAT. Experiments reveal that the proposed method outperforms other state-of-the-art models on the LRE ignition dataset. Furthermore, the ablation experiment proves that each module of the model improves the effect and extensive discussions explore interpretability. Our code can be found on: https://github.com/yhd-ai/GG-Nets.

Keywords: Anomaly detection; Graph attention network (GAT); Liquid rocket engine (LRE); Multivariate time series; Industrial Internet of Things (IIoT) (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832023003320
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:238:y:2023:i:c:s0951832023003320

DOI: 10.1016/j.ress.2023.109418

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().