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To improve the accuracy of fault diagnosis for multimodal process, an ensemble fault diagnosis approach based on IJITL-WEMD-RLSSVM (short words of, improved just-intime-learning (IJITL), empirical mode decomposition with window (WEMD), recursive least squares support vector machine (RLSSVM)) is presented. Firstly, the corresponding data are found in historical data through IJITL method and the small...
To improve the accuracy of fault diagnosis for motor bearing with non-stationary and nonlinear characteristic, an ensemble fault diagnosis approach based on EEMD (Ensemble Empirical Mode Decomposition), KPCA (Kernel Principal Component Analysis) and IGSABP(Improved Gravitational Search Algorithm for Back Propagation neural network) is proposed. Firstly, EEMD extracts the non-stationary vibration signal...
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