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In this paper, a data-driven method is proposed to detect and isolate the intermittent fault in gyroscopes. A mathematical description for the intermittent fault is first proposed in a probabilistic framework. Based on this probabilistic model, we present a random generation algorithm to emulate the occurrence of the intermittent fault. Considering the cross-correlation and autocorrelation between...
This paper proposes a new fault detection and isolation method for the spacecraft attitude sensors by integrating the dedicated observer scheme (DOS) and extended Kalman filter (EKF). In this paper, the attitude sensors are arranged into several groups and then a bank of EKFs are designed to estimate the attitude. Using the attitude estimates provided by the EKFs, a fault detection and isolation strategy...
This study deals with actuator fault estimation for discrete-time linear descriptor systems. The main contribution lies in the synthesis of a novel filter to estimate and isolate actuator faults for discrete linear descriptor systems. In this study, a restricted system equivalent (RSE) model is firstly obtained for the considered descriptor system, and then a fault estimation filter is designed based...
This paper presents a robust unknown input observer-based approach to deal with fault diagnosis for sampled-data control system with unknown input. Firstly a discrete-time model was considered to approximate its continuous-time dynamics. Secondly by considering the actuator or sensor fault as an auxiliary state vector, an augmented system is constructed. Thirdly we derive the structure of the proposed...
Most of faults in mono-propellant propulsion system for spacecraft often occur in thrusters' startup or shutdown process. How to design the fault diagnosis method to overcome the large overshoot interference by thruster startup/shutdown is still open. Since there are far from sufficient data for fault model prediction especially during the on-orbit flight, so we just chose pressure sensor and applied...
Decision tree support vector machine (DTSVM), which combines SVM and decision tree using the concept of dichotomy, is proposed to solve the multi-class fault diagnosis tasks. Since the classification performance of DTSVM is closely related to its structure, genetic algorithm is introduced into the formation of decision tree, to cluster the multi-classes with maximum distance between the clustering...
The detection of small current grounding fault line based on Wavelet transform technique and the neural network technique was presented. According of the distribution of energy of each line in the system of grounding, the extraction of feature vectors using wavelet multi-resolution analysis and the decision of fault line using neural networks are described. This strategy overcome the defects of conventional...
Fault diagnosis (FD) has recently received considerable attention in industry and academia. In order to make a more accurate and more complete estimation and decision for the problem, an approach that is capable of overcoming the disadvantage of single FD methodology, and eliminating the system uncertainty is presented. This paper takes Flat Wheel Detecting System as an example. First, the proposed...
Fault diagnosis (FD) has recently received considerable attention in industry and academia. In order to make a more accurate and more complete estimation and decision for the problem, an approach that is capable of overcoming the disadvantage of single FD methodology, and eliminating the system uncertainty is presented. This paper takes flat wheel detecting system as an example. First, the proposed...
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