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Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers

机译：基于滑模观测器的飞机发动机稳健的机上传感器故障诊断

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For a sensor fault diagnostic system of aircraft engines, the health performance degradation is an inevitable interference that cannot be neglected. To address this issue, this paper investigates an integrated on-line sensor fault diagnostic scheme for a commercial aircraft engine based on a sliding mode observer (SMO). In this approach, one sliding mode observer is designed for engine health performance tracking, and another for sensor fault reconstruction. Both observers are employed in in-flight applications. The results of the former SMO are analyzed for post-flight updating the baseline model of the latter. This idea is practical and feasible since the updating process does not require the algorithm to be regulated or redesigned, so that ground-based intervention is avoided, and the update process is implemented in an economical and efficient way. With this setup, the robustness of the proposed scheme to the health degradation is much enhanced and the latter SMO is able to fulfill sensor fault reconstruction over the course of the engine life. The proposed sensor fault diagnostic system is applied to a nonlinear simulation of a commercial aircraft engine, and its effectiveness is evaluated in several fault scenarios.
机译：对于飞机发动机的传感器故障诊断系统，健康性能下降是不可避免的干扰，不能忽略。为了解决这个问题，本文研究了基于滑模观察器（SMO）的商用飞机发动机集成在线传感器故障诊断方案。在这种方法中，一个滑模观察器被设计用于发动机健康性能跟踪，而另一个则用于传感器故障重建。两名观察员都在飞行中使用。分析前者SMO的结果，以便在飞行后更新后者的基线模型。由于更新过程不需要对算法进行调整或重新设计，因此该想法是切实可行的，从而避免了基于地面的干预，并且以经济有效的方式实现了更新过程。通过这种设置，所提出的方案对健康恶化的鲁棒性大大增强，并且后者的SMO能够在发动机使用寿命的过程中完成传感器故障的重建。提出的传感器故障诊断系统应用于商用飞机发动机的非线性仿真，并在几种故障情况下评估其有效性。

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