In this paper, a model-based analytical redundancy method is used for sensor fault detection. The diagnosis system uses Kalman filters as state estimators, which can detect 6 kinds of typical sensor fault modes. Then Design a Multi-kernel SVM fault classification system, which makes use of PCA and WPEE method to extract fault characteristic. Compared to the traditional diagnostic and classification methods, Multi-kernel SVM is more effective.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Sensor Fault Diagnosis and Classification in Aero-engine


    Contributors:
    Zhu, Feixiang (author) / Li, Benwei (author) / Li, Zhao (author) / Zhang, Yun (author)


    Publication date :

    2014


    Size :

    15 Seiten





    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Data-Driven Equivalent Space Aero-Engine Sensor Robust Fault Diagnosis

    Song, Yixiao / Gou, Linfeng / Zhang, Meng et al. | IEEE | 2023


    Fault diagnosis for sensors and components of aero-engine

    Yebo, L. / Qiuhong, L. / Xianghua, H. et al. | British Library Online Contents | 2013


    METHOD FOR FAULT DIAGNOSIS OF AERO-ENGINE SENSOR AND ACTUATOR BASED ON LFT

    MA YANHUA / DU XIAN / WANG RUI et al. | European Patent Office | 2020

    Free access

    Method for fault diagnosis of aero-engine sensor and actuator based on LFT

    MA YANHUA / DU XIAN / WANG RUI et al. | European Patent Office | 2021

    Free access

    Fault fusion diagnosis of aero-engine based on deep learning

    Che, Changchang / Wang, Huawei / Ni, Xiaomei et al. | British Library Online Contents | 2018