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The modal analysis based on ANSYS for all the components of the train wheel-bearing of NJ(P)3226X1 had been carried out. The vibration of each component was excited by the hammer with an accelerometer. The respondent acoustic signals were acquired by the microphone and the natural frequencies were obtained. The comparison between the computation using ANSYS and the measurements had demonstrated the...
The interference from background noise makes it difficult to identify the incipient defect of a bearing via vibration analysis. By the aid of stochastic resonance (SR), the unavoidable noise can, however, be applied to enhance the system output. The classical SR phenomenon requires small parameters, which is not suited for bearing defect diagnosis since the defect-induced frequency of a bearing is...
In this paper, a new method based on wavelet analysis for feature extraction of gearbox vibration signals is explored. The similarity of the power spectrums between gearbox vibration signals and 1/f processes signals makes natural the use of wavelet-based fractal analysis for gearbox fault diagnosis. Then the principle of this method was discussed. To verify the feasibility and practicability of this...
In this paper, we attempted to classify the acceleration signals of different working states of bearings by using the wavelet-based fractal analysis. Considering the similarity of the power spectrums between bearing vibration signals and 1/f processes signals, the principles of wavelet-based fractal analysis for bearing fault diagnosis are explored. To verify the feasibility and practicability of...
The objective of this paper is to propose a new system for fault diagnosis of train bearings using PCA and ACO. On the base of the analysis of time and frequency domain statistical features extracted from the vibration signals collected from the bearings, twenty features which were the most sensitive to different working states were chosen as the object of follow-on process. After zero-average and...
The success of health monitoring and condition assessment for power transformer with vibration analysis lies on proper extraction of vibration features. The extraction of features in turn depends on appropriate signal processing methods. In this paper, a WPT and HHT based time-scale-frequency analysis is developed to extract the vibration features from power transformer tank. In this method, the WPT...
Blind source separation is a signal processing method based on independent component analysis, its aim is to separate the source signals from a set of observations by assuming the signals independently. This paper reviews the general concept of BSS, especially the theory for convolutive mixtures, the model of convolutive mixture and two deconvolution structures: recursive and direct structures, then...
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