Chang Xiaodong, Huang Jinquan, Lu Feng
Jiangsu Province Key Laboratory of Aerospace Power System, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Sensors (Basel). 2017 Apr 11;17(4):835. doi: 10.3390/s17040835.
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.
对于飞机发动机的传感器故障诊断系统而言，健康性能退化是不可忽视的必然干扰。为解决这一问题，本文研究了一种基于滑模观测器（SMO）的商用飞机发动机集成在线传感器故障诊断方案。在该方法中，设计了一个滑模观测器用于发动机健康性能跟踪，另一个用于传感器故障重构。两个观测器均应用于飞行过程中。对前一个滑模观测器的结果进行分析，以便在飞行后更新后一个观测器的基线模型。这个想法是切实可行的，因为更新过程不需要对算法进行调整或重新设计，从而避免了地面干预，并且以经济高效的方式实现了更新过程。通过这种设置，所提方案对健康退化的鲁棒性大大增强，并且后一个滑模观测器能够在发动机寿命期间完成传感器故障重构。所提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，并在几种故障场景下评估了其有效性。
