期刊
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
卷 51, 期 7, 页码 4251-4261出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSMC.2019.2930805
关键词
Integrated design; Covariance matrices; Support vector machines; Fault detection; Discrete-time systems; Aerospace electronics; Probability distribution; False alarm rate (FAR); fault detection rate (FDR); linear discrete-time system; parity space vector machine (PSVM); robust fault detection
资金
- National Natural Science Foundation of China [61873149, 61733009]
- Research Fund for the Taishan Scholar Project of Shandong Province of China
The paper introduces a novel robust fault detection method called parity space vector machine (PSVM) for linear discrete-time systems. By constructing a PSVM model and formulating the fault detection problem as a distribution-free Bayes optimal classifier, the approach achieves a tradeoff between false alarm rate (FAR) and fault detection rate (FDR) effectively.
In this paper, a novel robust fault detection (FD) approach called parity space vector machine (PSVM) is proposed for linear discrete-time systems. Aiming to achieve a tradeoff between false alarm rate (FAR) and FD rate (FDR) simultaneously, we focus our study on an integrated design of parity space-based FD in the context of residual generation and residual evaluation. Without a prior knowledge of the distribution of the unknown inputs, we propose to construct a PSVM model and formulate the underlying FD problem as a distribution-free Bayes optimal classifier, where the FAR and FDR indicate the worst-case classification accuracies of future residuals for the fault free case and faulty case. Then a bank of parity space vectors and corresponding thresholds can be designed integratedly by applying the techniques of the minimum error minimax probability machine and, at the same time, an optimal tradeoff between FAR and FDR is achieved. Finally, the effectiveness of the proposed approach is demonstrated on a longitudinal control system of unmanned aerial vehicle and further comparison with a traditional parity space-based FD is also addressed.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据