Online Fault Diagnosis of the Water Circulation System of Altitude Simulation Test for LREs

Software and methodology are the two key aspects of fault diagnosis technology for detecting faults in the running water circulation system of altitude simulation tests on liquid rocket engines real-time. An online fault diagnosis software is developed in C# language, including communication module, data monitoring module, fault diagnosis module, anomaly detection module and anomaly event recording module. The fault diagnosis module is embedded with a back propagation neural network algorithm, and the core of the anomaly detection module is the threshold detection method. This software can monitor the data of different types of measurement and control systems in real time with the communication module, and perform anomaly detection and fault diagnosis based on real-time data. In testing, this online fault diagnosis software shows good stability and reliability. It has the ability to detect all abnormal events in which the data exceeds the limit and to correctly diagnose known faults with approximate 80% accuracy. These results can be applied to other types aerospace engine test system.

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Publication Details

Published
2024-08-20
DOI
https://doi.org/10.1109/ibcast61650.2024.10876995
Primary Topic
Advanced Sensor and Control Systems
Type
article
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article

Online Fault Diagnosis of the Water Circulation System of Altitude Simulation Test for LREs

Guozhu Liang, Yong Xu, Hongjie Guo
Advanced Sensor and Control Systems
article

Online Fault Diagnosis of the Water Circulation System of Altitude Simulation Test for LREs

Guozhu Liang, Yong Xu, Hongjie Guo
article en

Abstract

Software and methodology are the two key aspects of fault diagnosis technology for detecting faults in the running water circulation system of altitude simulation tests on liquid rocket engines real-time. An online fault diagnosis software is developed in C# language, including communication module, data monitoring module, fault diagnosis module, anomaly detection module and anomaly event recording module. The fault diagnosis module is embedded with a back propagation neural network algorithm, and the core of the anomaly detection module is the threshold detection method. This software can monitor the data of different types of measurement and control systems in real time with the communication module, and perform anomaly detection and fault diagnosis based on real-time data. In testing, this online fault diagnosis software shows good stability and reliability. It has the ability to detect all abnormal events in which the data exceeds the limit and to correctly diagnose known faults with approximate 80% accuracy. These results can be applied to other types aerospace engine test system.

Beihang University (CN)
Clean water and sanitation
Openalex Percentile: Top 66%
Advanced Sensor and Control Systems
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