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This paper focuses on Data-Driven Design FOR Model-Based fault diagnosis, called D34MB for short. When the objective model is static, LVD (Latent Variable Detection) methods can be realized based on the LVE (Latent Variable Extraction) and LVR (Latent Variable Regression) techniques. A unified weight-framework for D34MB are proposed in this paper, which(More)
Proposed in this paper is a diagnosis framework based on SLSE (Sliding Least Squares Estimate) and directional discrepancy. This framework can be used when linear dynamic equation and beforehand baseline data are not available. It is efficient, for SLSE works by recursive computation, removing the oldest datum while accepting the newest. Its computational(More)
The improvement of unanticipated fault detection and diagnosis (UFDD) capability is a difficult point, and is also a tendency for research and application. In this paper, a general process model (GPM) for unanticipated fault diagnosis is established. And combined with the characteristics of monitoring data, the corresponding diagnosis methods are(More)
A toolbox is developed in the MATLAB/GUI environment for FDI (Fault Detection and Isolation) which is an important field of automatic control theory and engineering. It provides an interactive interface for FDI. In this GUI (Graphical User Interface), a variety of methods are available for the FDI tasks, e.g., the traditional data-driven and model-based(More)
The star sensor has been widely used as an important and accurate attitude measurement sensor in classical satellite attitude determination systems. This paper analyses the influence of star sensor's sampling frequency on attitude determination accuracy within an Extended Kalman filter (EKF). Simulations are used to validate the theoretical analysis and(More)
The improvement of the detection and diagnosis capability for the unanticipated fault is a tendency in the research and application of fault diagnosis. In this paper, some notions and the basic principles for the unanticipated fault detection and diagnosis are given. A general process model applied to the diagnosis for the unanticipated fault is designed,(More)
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