<p>The aircraft braking system is critical to ensure the safe take-off and landing of the aircraft. However, the braking system is often exposed to high temperatures and strong vibration working environments, which makes the sensor prone to failure. Sensor failure has the potential to compromise aircraft safety. In order to improve the safety of the aircraft braking system, a fault detection and fault-tolerant control (FDFTC) strategy for the aircraft brake pressure sensor is designed. Firstly, a model based on a bidirectional long short-term memory (Bi-LSTM) network is constructed to estimate the brake pressure. Then, the residual sequence is obtained by comparing the measured pressure with the estimated pressure. On this basis, the improved sequential probability ratio test (SPRT) method based on mathematical statistics is applied to analyze the residual sequence to detect the fault. Finally, simulation and hardware-in-the-loop (HIL) testing results indicate that the proposed FDFTC strategy can detect sensor faults in time and efficiently complete braking when faults occur. Hence, the proposed FDFTC strategy can effectively deal with the faults of the aircraft brake pressure sensor, which is of great significance to improve the reliability and safety of the aircraft.</p>

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Fault Detection and Fault-Tolerant Control Based on Bi-LSTM Network and SPRT for Aircraft Braking System

  • Renjie Li,
  • Yaoxing Shang,
  • Jinglin Cai,
  • Xiaochao Liu,
  • Lingdong Geng,
  • Pengyuan Qi,
  • Zongxia Jiao

摘要

The aircraft braking system is critical to ensure the safe take-off and landing of the aircraft. However, the braking system is often exposed to high temperatures and strong vibration working environments, which makes the sensor prone to failure. Sensor failure has the potential to compromise aircraft safety. In order to improve the safety of the aircraft braking system, a fault detection and fault-tolerant control (FDFTC) strategy for the aircraft brake pressure sensor is designed. Firstly, a model based on a bidirectional long short-term memory (Bi-LSTM) network is constructed to estimate the brake pressure. Then, the residual sequence is obtained by comparing the measured pressure with the estimated pressure. On this basis, the improved sequential probability ratio test (SPRT) method based on mathematical statistics is applied to analyze the residual sequence to detect the fault. Finally, simulation and hardware-in-the-loop (HIL) testing results indicate that the proposed FDFTC strategy can detect sensor faults in time and efficiently complete braking when faults occur. Hence, the proposed FDFTC strategy can effectively deal with the faults of the aircraft brake pressure sensor, which is of great significance to improve the reliability and safety of the aircraft.