Abstract
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
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Zhu, F., Li, B., Li, Z., Zhang, Y. (2014). Sensor Fault Diagnosis and Classification in Aero-engine. In: Wang, J. (eds) Proceedings of the First Symposium on Aviation Maintenance and Management-Volume I. Lecture Notes in Electrical Engineering, vol 296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54236-7_45
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DOI: https://doi.org/10.1007/978-3-642-54236-7_45
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