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As a result of the diversity of the tower crane faults, after the faults occurred, it is difficulty to accurately discriminate the fault type immediately. In this paper, the “clustering” of the RBF neural network effected on the input samples can be used to automatically realize the classification of the failure modes. Accordingly, the faults are diagnosed, and the specific example of the tower crane...
We present a new analytical model for switched reluctance motors (SRMs). The model uses four coefficients, which are rotor position dependent and calculated from the flux-current-angle data using numerical curve fitting with least squares method. The four coefficients are further represented with sixth degree polynomials, which can be calculated effectively with Qin Jiushao's method. Simulated results...
Wavelet analysis has been a powerful tool for exploring and solving many complicated problems in natural science and engineering computation. In this paper, the notion of orthogonal vector-valued wavelet packets with 3-scale in higher dimensions is introduced. A procedure for constructing them is presented. Their orthogonality property is characterized by virtue of finite group theory, time-frequency...
Adaptive Resonance Theory (ART) and k-means have been widely used for clustering, but those two algorithms have their own limitations. In this paper a hybrid clustering algorithm is proposed which is based on ART2 and k-means. Firstly ATR2 is executed to find the initial cluster numbers and initial cluster centers, k-means uses these values to initialize its parameters and find new cluster centers,...
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