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In 2010, we proposed the improved unsupervised possibilistic clustering algorithm (IUPC) that can be run as an unsupervised clustering and overcome the weakness of the unsupervised possibilistic clustering algorithm (UPC) that it tends to generate coincident clusters. IUPC inherits the merits of UPC. In the meanwhile, IUPC solves the coincident clusters problem of UPC by limiting the feasible regions...
In this paper, An algorithm which uses an improved threshold algorithm in the de-noising of electricity signals and then extracted the fault feature by db10 wavelet, is proposed because of the features in the fault of high voltage electric power measurement system. Experiment results show that it is more efficient to de-noising by the improved threshold algorithm in wavelet analysis. The method in...
In consideration of the common sensor failures in aero-engine control system, a new approach is proposed using dual redundant predictors based on neutral network in this paper. The neutral network temporal redundant predictor and spatial redundant predictor are created over the time series redundant information of single sensor and the space redundant information of multi-sensor respectively. The...
Clustering has been used widely in pattern recognition, image processing, data mining and so on. Many clustering algorithms are sensitive to outlier faults in noisy environments. In this paper, we propose a new algorithm called sample weighted possibilistic fuzzy c-means clustering (SWPFCM). Based on combination sample weighting and a suitable for noise environment of initialization clustering center...
Based on the structure modal parameter identification method, the free vibration signal is first extracted using random decrement technique, and then the cross-correlations of different respond points obtained through NExT method are taken as the inputs of the modal time domain identification, and parameter identification is obtained by means of complex exponential method .. The local damage diagnosis...
The values of analog circuits' input and output signals and the component parameters are continuous, and meanwhile there are inevitable tolerance and non-linear components in analog circuits, therefore the presence of these factors increases complexity of the analog circuits fault diagnosis. RBF and BP neural network are two widely used feedforward neural networks, LabVIEW is a graphical programming...
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