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Identification of sensor faults on turbofan engines using pattern recognition techniques

机译:使用模式识别技术识别涡轮风扇发动机上的传感器故障

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摘要

The possibility to identify faults in the readings of the sensors used to monitor the performance of a high by-pass ratio turbofan engine is examined. A novel method is proposed, based on the following principle: if a measurement set is fed to an adaptive performance analysis algorithm, a set of component performance modification factors (fault parameters) is produced. Faults, which may be present in the measurement set, may be recognized from the patterns they produce on the modification factors. The constitution of a method of this type based on pattern recognition techniques is discussed here. Test cases corresponding to different sensor faults, simulating operation in real conditions are examined. Three kinds of pattern recognition techniques with increasing complexity are used, in order to correctly identify the examined sensor faults. It is demonstrated that by choosing an appropriate formulation it is possible to have a 100% success in the identification of the examined sensor faults.
机译:检查了在用于监控高旁通比涡轮风扇发动机性能的传感器读数中识别故障的可能性。提出了一种基于以下原理的新颖方法:如果将测量集输入到自适应性能分析算法,则会生成一组组件性能修改因子(故障参数)。可以根据测量因子在修正因子上产生的模式来识别测量集中可能存在的故障。本文讨论了基于模式识别技术的这种方法的构造。检查了与不同传感器故障相对应的测试用例,以模拟实际条件下的操作。为了正确地识别所检查的传感器故障,使用了三种具有增加的复杂度的模式识别技术。事实证明,通过选择合适的公式,有可能100%成功地识别出所检查的传感器故障。

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