YAO Wen-rong1, XU Tian-zhen2, ZHANG Hai-bo2.Fault Diagnosis of Gas Path Sonsor for Turbofan Engine[J].航空发动机,2017,43(5):54-61 |
Fault Diagnosis of Gas Path Sonsor for Turbofan Engine |
DOI: |
Key Words:online sequential extreme learning turbofan engine sensor fault isolation fault diagnosis signal reconstruction |
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Abstract:In order to diagnose malfunctioning turbofan engines' sensor, a corresponding fault diagnosis system was designed with the
Online Sequential Extreme Learning (OS-ELM) algorithm. The core idea is that after finding some malfunction sensor, a predictive learning
mechanismis applied to construct fault detection and isolation for the sensor. The fault diagnosis for multiple-sensor failures can be effectively
solved by this mechanism. Meanwhile, the output layer weight vector of the algorithm net is updated selectively based on generalization
capability, the method could significantly improve the really-time of fault diagnosis system. Simulations on a turbofan engine show that the
diagnosis method of sensor faults could detect and isolate faults of single-sensor and double-sensor failures, which also prove the validity
and feasibility of the algorithm. |
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