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Sensor Fault Diagnosis and Reconstruction of Engine Control System Based on Autoassociative Neural Network

机译:基于自关联神经网络的发动机控制系统传感器故障诊断与重构

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摘要

The topology and property of Autoassociative Neural Networks(AANN) and the AANN's application to sensor fault diagnosis and reconstruction of engine control system are studied. The key feature of AANN is feature extract and noise filtering. Sensor fault detection is accomplished by integrating the optimal estimation and fault detection logic. Digital simulation shows that the scheme can detect hard and soft failures of sensors at the absence of models for engines which have performance deteriorate in the service life, and can provide good analytical redundancy.
机译:研究了自联想神经网络的拓扑结构和性质以及AANN在发动机控制系统传感器故障诊断和重构中的应用。 AANN的关键特征是特征提取和噪声过滤。传感器故障检测是通过集成最佳估计和故障检测逻辑来完成的。数字仿真表明,该方案可以在不存在使用寿命降低的发动机模型的情况下检测传感器的硬故障和软故障,并且可以提供良好的分析冗余。

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