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    黄金泉

    • 教授 博士生导师
    • 性别:男
    • 毕业院校:南京航空航天大学
    • 学历:博士研究生毕业
    • 学位:工学博士学位
    • 所在单位:能源与动力学院
    • 办公地点:明故宫校区10-508
    • 联系方式:13951796358 微信号:wxid_577glshhuj0q21(与手机绑定)
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    Robust In-Flight Sensor Fault Diagnostics for Aircraft Engine Based on Sliding Mode Observers

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    所属单位:能源与动力学院

    发表刊物:SENSORS

    关键字:commercial aircraft engine health degradation sensor fault diagnostics sliding mode observer

    摘要: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.

    ISSN号:1424-8220

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    发表时间:2017-04-01

    合写作者:Chang, Xiaodong,鲁峰

    通讯作者:黄金泉