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With the development of fault prognostics, remaining life prediction is becoming more and more important as a crucial technology of prognostics. In this paper, an improved Markov model is proposed for remaining life prediction. Fuzzy c-means (FCM) algorithm is employed to perform states division of Markov model in order to avoid the uncertainty of states division depending on personal experience....
The vibration signal of rotating machine is typical amplitude-modulated signal. In that case, the method of cyclostationary analysis is very effective for extracting and demodulating the modulating signal that usually contains some fault message. However, duo to a good many factors, such as the special construction, the amalgamation of multiple faults and the fluctuation of rotating speed etc., the...
In this paper, fault detection for networked control system with data packet dropout between sensor and controller is discussed. A fault observer structure is presented, in which the previous system output transmitted successfully is used for feedback of the observer when data packet dropout happens. Suppose continuous data packet dropout is finite, the dynamics of the observer error can be modeled...
Any traffic responsive system depends on its ability to sense traffic flow. In traffic engineering, detector data can not satisfy the demand of adaptive traffic signal control system because of its high cost, low coverage area, difficult to update and maintenance. Therefore, in order to obtain more detail of traffic condition information such as traffic volume, mean velocity, link travel time, occupancy,...
A novel classifier is proposed for fault diagnosis of rotor system, with independent component analysis (ICA) based feature extraction and multi-layer perceptron (MLP) based pattern classification. By the use of ICA, feature vectors are integratedly extracted from multi-channel vibration measurements collected under different operating patterns (in term of rotating speed and/or load). Thus, a robust...
A new particle filter based fault diagnosis method for nonlinear stochastic system with non-Gaussian noise and disturbances is proposed by combining particle filter algorithm and fault diagnosis theory. One of the appealing advantages of the new approach is that the complete probability distribution information of the state estimates from particle filter is utilized for fault detection, another is...
In order to realize comprehensive fault evaluation on faults occurred in maglev train, aim at the difficulty in establishing the evaluation weight matrix and subjection matrix parameter, faint comprehensive evaluation method based on ensemble learning algorithm is proposed. First, the structure of the suspension system of maglev train is analyzed and a fault diagnosis model is built. Then ensemble...
For estimating faults of the system with unknown nonlinear term, a novel fault diagnosis method based on nonlinear compensation term and proportional multiple-integral observer is proposed. In this method, the nonlinear compensation term is constructed by support vector machines (SVM), which can reduce the influence of unknown nonlinear part. Proportional multiple-integral observer based nonlinear...
A new method of roller bearings fault diagnosis based on least squares support vector machines (LS-SVM) was presented. Feature selection method based on simulated annealing (SA) algorithm was discussed in this paper. LS-SVM classifier was constructed for bearing faults. Compared with the Artificial Neural Network based method, the LS-SVM based method possessed desirable advantages. Experiment shows...
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