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Bearings are widely used in many equipments and its operating state directly concerns the performance of the whole machinery. In this paper, empirical mode decomposition method is firstly used to analyze the signals of different fault types of the bearing and extract the feature vectors. By comparing the performances of different BP networks using three different algorithms on the training data, then...
As an important component of the rotating machine, ball bearings are widely used in industrial production. Its operating state directly concerns the safety production and economic benefits. In this paper, wavelet analysis was used to deal with non-stationary characteristic signals of the bearing. Meanwhile, Hilbert envelope spectrum is quite suitable for feature extraction. A combined diagnosis method...
Knowledge-based diagnostic approaches are usually restricted to known systems because of the nature of knowledge representation in terms of empirical symptom-failure association. Model-based diagnosis methods to the expert systems offer substantial advantages in terms of flexibility and potentials of knowledge reuse. This paper describes a modeling method and diagnosis technique for the power system...
The increased amount of redundant units means improvement of task reliability, however, the additional units and corresponding vote devices request more logistics, which results in decline of basic reliability. In this paper, we design and make analysis and comparison of multiple redundant structures in two ways of task reliability and basic reliability. This paper provides theoretical reference for...
The maximum difference between the empirical distribution function and the theoretical distribution function is random in Kolmogorov-Smirnov(K-S) test. The distribution of this maximum difference, including mean and deviation, is studied based on bootstrap method in this paper. Firstly, the simulated samples are randomly re-sampled from the original finite observed samples. Then the maximum difference...
This paper presents a reliability analysis method based on Bayesian network in order to determine the weak parts of the system and enhance its reliability. The Bayesian network model is converted from its corresponding fault tree representing the system conditions and failures, which is used to calculate the occurrence probabilities of all nodes under different conditions. Four kinds of familiar faults...
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