论文标题
PCA方法和基于证据的滤波飞机传感器故障诊断
PCA Methods and Evidence Based Filtering for Robust Aircraft Sensor Fault Diagnosis
论文作者
论文摘要
在本文中，PCA和D-PCA技术用于数据驱动的诊断故障隔离（FI）和故障估计（FE）方案（FE）的设计，该方案的18个半自治飞机的主要传感器。具体而言，已经考虑了基于贡献和基于重建的贡献方法。为了提高FI绩效，已经提出了从循证决策理论中得出的推论机制。根据实验数据，为真实的空速传感器提供了一项详细的FI和FE研究。基于证据的过滤（EBF）显示出非常有效的，特别是在减少错误警报方面。
In this paper PCA and D-PCA techniques are applied for the design of a Data Driven diagnostic Fault Isolation (FI) and Fault Estimation (FE) scheme for 18 primary sensors of a semi-autonomous aircraft. Specifically, Contributions-based, and Reconstruction-based Contributions approaches have been considered. To improve FI performance an inference mechanism derived from evidence-based decision making theory has been proposed. A detailed FI and FE study is presented for the True Airspeed sensor based on experimental data. Evidence Based Filtering (EBF) showed to be very effective particularly in reducing false alarms.
