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随着机载航空电子设备的快速发展,使得传统地面系统承担的发动机诊断任务可以在线实现。实时数据的使用,可以在线监测发动机性能退化,减少故障检测和隔离的潜伏期,增加间歇性故障的检测率。为此,提出并设计了一种用于航空发动机气路故障检测和隔离、健康监测及参数估计的在线综合诊断结构。基于xPC Target原理搭建了硬件实时仿真平台,对该结构进行了仿真验证。仿真结果表明,该结构中的机载自适应模型对发动机健康参数、可测参数和不可测参数的估计误差在0.5%以内;气路故障诊断系统采用实时数据,可以更早地检测和隔离包含间歇性故障在内的各种气路故障。
With the rapid development of airborne avionics, the tasks of engine diagnostics undertaken by traditional terrestrial systems can be realized online. The use of real-time data enables on-line monitoring of engine performance degradation, reduced latency for fault detection and isolation, and increased detection of intermittent faults. To this end, a comprehensive on-line diagnosis structure for the detection and isolation of aero-engine gas path faults, health monitoring and parameter estimation is proposed and designed. Based on the principle of xPC Target, a hardware real-time simulation platform was built and the structure was simulated. The simulation results show that the estimated error of the airborne adaptive model in the structure for the engine health parameters, measurable parameters and unmeasurable parameters is within 0.5%. The gas path fault diagnosis system uses real-time data to detect and isolate the inclusion Intermittent failure, including a variety of gas failure.