Intelligent built-in test of wheel speed sensor in aircraft braking system based on FPGA acceleration

The built-in test (BIT) functionality of the aircraft braking system is directly related to flight safety. In the aircraft braking system, designing a reasonable and effective BIT fault diagnosis method is crucial for ensuring safe landing. The method proposed in this article addresses the issue of wheel speed sensor faults in aircraft braking systems. By leveraging the informational correlations between multi-sensor signals and flight parameters, the approach uses a small intelligent model and evidence fusion techniques to accurately identify true faults, normal conditions, or false alarms. While ensuring performance, the algorithm is deployed on FPGA, achieving faster diagnostic efficiency than software through hardware acceleration.

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Publication Details

Journal
IET conference proceedings.
Published
2025-01-01
DOI
https://doi.org/10.1049/icp.2024.3260
Primary Topic
Real-time simulation and control systems
Type
article
Field-Weighted Citation Impact
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article

Intelligent built-in test of wheel speed sensor in aircraft braking system based on FPGA acceleration

Shuangwen Sheng, Lingdong Geng, Lianmeng Wang, X. Yue et al.
IET conference proceedings.
Real-time simulation and control systems
article

Intelligent built-in test of wheel speed sensor in aircraft braking system based on FPGA acceleration

Shuangwen Sheng, Lingdong Geng, Lianmeng Wang, X. Yue, Zhan Liu, Jili Sun, Zhenguo Gao, Wenjian Sun
article en

Abstract

The built-in test (BIT) functionality of the aircraft braking system is directly related to flight safety. In the aircraft braking system, designing a reasonable and effective BIT fault diagnosis method is crucial for ensuring safe landing. The method proposed in this article addresses the issue of wheel speed sensor faults in aircraft braking systems. By leveraging the informational correlations between multi-sensor signals and flight parameters, the approach uses a small intelligent model and evidence fusion techniques to accurately identify true faults, normal conditions, or false alarms. While ensuring performance, the algorithm is deployed on FPGA, achieving faster diagnostic efficiency than software through hardware acceleration.

IET conference proceedings.Vol. 2024(13)
Aerospace Information Research Institute (CN)
Affordable and clean energy
Openalex Percentile: Top 99%
Real-time simulation and control systems
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