An approach based on the singular spectrum decomposition (SSD)-singular value (SVD) and frequency weight energy operator (FWEO) was proposed for early fault diagnosis of rolling bearings. Since interference heavy noise in stage bearing fault, SSD could eliminate abundant noise, meanwhile adaptively decompose nonlinear, non-stationary signals into multiple mono-components which had distinct phys...

In order to achieve accurate fault diagnosis of rolling bearings, a hierarchical decision fusion method for bearings is proposed. The back propagation neural networks (BPNNs) architecture includes detection layer, isolation layer and degree identification which reduce the calculation cost enhance maintainability algorithm. By wavelet packet decomposition signal reconstruction raw vibration bear...

Reconstruction of one run of CLEO III raw data can take up to 9 days to complete using a single processor. This is an administrative nightmare, and even minor failures result in reprocessing the entire run, which wastes time, money and CPU power. We leveraged the ability of the CLEO III software infrastructure to read and write multiple file formats to perform reconstruction of a single run usi...

Aiming at the problem of early fault diagnosis rolling bearing, an detection method bearing based on a multiscale convolutional neural network and gated recurrent unit with attention mechanism (MCNN-AGRU) is proposed. This first inputs multiple time scales vibration signals into to train model through data processing then adds make predictive. Finally, reconstruction error between actual value ...