In-the-Loop Simulation Experiment of Aero-Engine Fault-Tolerant Control Technology
Source abstract
Abstract
Aeroengines are prone to failure due to their large range of working envelopes and bad working environments. Fault diagnosis and a fault-tolerant control strategy for aeroengines and control systems are important means to improve the reliability of aeroengine. In this article, the turbofan engine is taken as the research object, and the fault diagnosis and fault-tolerant control of an aeroengine control system are studied. First, based on the principle of component-level modeling and the algorithm of the extended Kalman filter, an adaptive turbofan model is established, and the adaptive effect of the model in the range of the full envelopment is verified by digital simulation. Next, based on the analytical redundancy provided by the adaptive model, sensor fault diagnosis and fault-tolerant control are studied. The low-voltage speed closed-loop control and EPR closed-loop control are designed, and the sensor fault-tolerant control based on analytic redundancy and the switching control rate is studied. The simulation results show that the filter based on the adaptive model can accurately locate and diagnose the sensor faults, and the sensor fault-tolerance based on the analytic redundancy and switching control rate can be effective fault tolerance for the sensor faults. Finally, as a hardware platform, this article selects MC203 VxWorks as an embedded system, the adaptive model for a turbofan engine as the research object, and has carried on the fault diagnosis and fault-tolerant control in the loop simulation experiment research; the experimental results show that the adaptive model can provide accurate analytical redundancy, and the real-time and fault tolerance of sensor fault effect is better.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Fault Detection and Control Systems · Aerospace and Aviation Technology · Real-time simulation and control systems
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
References (39)
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