基于神经网络的双冗余预测器航空发动机传感器故障诊断研究

Yigang Sun, Daming Ren
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引用次数: 0

摘要

针对航空发动机控制系统中常见的传感器故障,提出了一种基于神经网络的双冗余预测器的控制方法。分别基于单传感器的时间序列冗余信息和多传感器的空间冗余信息建立了神经网络时间冗余预测器和空间冗余预测器。将阈值微分法应用于传感器故障的实时检测。隔离故障传感器并使用空间冗余预测器的输出来适应它。数字仿真结果表明了该方法的有效性和可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Aero-Engine Sensor Failure Diagnosis with Dual Redundant Predictors Based on Neutral Network
In consideration of the common sensor failures in aero-engine control system, a new approach is proposed using dual redundant predictors based on neutral network in this paper. The neutral network temporal redundant predictor and spatial redundant predictor are created over the time series redundant information of single sensor and the space redundant information of multi-sensor respectively. The threshold-value differentiate method is applied for real-time sensor failure detection. Isolate the fault sensor and use the outputs of spatial redundant predictor to accommodate it. Digital simulation results show that this method is effective and feasible.
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