故障检测与隔离
残余物
非线性系统
高斯分布
控制理论(社会学)
计算机科学
断层(地质)
自相关
算法
噪音(视频)
高斯噪声
高斯过程
人工智能
模式识别(心理学)
数学
统计
执行机构
控制(管理)
地震学
地质学
物理
量子力学
作者
H. Safaeipour,Mehdi Forouzanfar,Amin Ramezani
出处
期刊:Measurement
[Elsevier]
日期:2021-04-01
卷期号:174: 109008-109008
被引量:16
标识
DOI:10.1016/j.measurement.2021.109008
摘要
Incipient fault detection in real-time nonlinear closed-loop systems in the presence of unwanted stochastic terms remains a challenging issue, especially in mixed Gaussian and non-Gaussian environments. This paper is concerned with incipient-fault detection in such systems. To this goal, based on the autocorrelation of the windowed residual signal and the reasonable assumptions in the nonlinear system, an online incipient fault detection with acceptable computational efforts and an adaptive-robust residual scheme is provided. Also, a closed-loop form of the three-tank system (DTS200) has been devised and simulated to demonstrate the effectiveness of the proposed solution.
科研通智能强力驱动
Strongly Powered by AbleSci AI