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Early detection of small faults in closed-loop systems is a challenging issue in the fault diagnosis literature. The effect of faults in closed-loop systems will be obscured by a robust feedback control, especially when the controller is coupled with nonlinear uncertainty. In this paper, an approach for rapid detection for small faults in a class of closed-loop uncertain systems is proposed based...
In this paper, an approach for rapid fault detection for a class of nonlinear sampled-data systems is proposed. Firstly, a learning estimator is constructed to capture the unknown system dynamics effects in sampled-data systems. The key issue in the learning process is that partial neural weights will converge into their optimal values based on the deterministic learning theory. Then a knowledge bank...
A novel hierarchical diagnosis network (HDN) is proposed by collecting deep belief networks (DBNs) by layer for the hierarchical identification of mechanical system. The deeper layer in HDN presents a more detailed classification of the result generated from the last layer to provide representative features for different tasks. A two-layer HDN is designed for a two-stage diagnosis with the wavelet...
In this paper, we propose an active fault diagnosis algorithm based on random walk approach under the Space Information Network (SIN) circumstance. Space information network is much more different with wireless sensor network for its long time delay and its inconstant topology. Therefore the existed fault diagnosis algorithm do not have a perfect performance as we want. The algorithm proposed in this...
Fault diagnosis is crucial for analog circuits. In this paper, a new fault diagnosis method based on genetic algorithm and support vector machine (GA-SVM) is proposed. We design fault mode and collect the fault datasets on the basis of a quad high pass filter circuit. Wavelet packet analysis is employed to extract fault samples information. Sampled data's dimension is further reduced by Principal...
This paper describes a fault diagnosis expert system for cement kiln developed in the way of integrating the new theories and methods of artificial intelligence and network technology with related production technology. The system can give online fault diagnosis and has features of simple network interface, excellent openness and easy expansibility. The design of the system layout, database, knowledge...
The diagnosis of faults is one of the important tasks in engineering systems. In this paper, based on the recent results on deterministic learning (DL) theory and rapid dynamical pattern recognition, a rapid fault diagnosis scheme is proposed for nonlinear oscillation systems. Firstly, a neural network bank for fault detection and isolation (FDI) is established through DL. Secondly, a mechanism for...
The diagnosis of faults is one of the important tasks in the operation of robotic manipulators. In this paper, a rapid fault diagnosis scheme is proposed for nonlinear robotic systems. Firstly, the system uncertainty and unknown fault dynamics are identified through deterministic learning. The knowledge on uncertainty and fault dynamics is stored in a bank of neural networks (NNs). Secondly, a mechanism...
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