In this work, a new monitoring system is developed for bearing fault detection in high-speed trains. Firstly, data acquisition to collect vibration and other related signals wirelessly. Secondly, multiple correlation analysis (MCA) technique proposed detection. The MCA consists of the three processing steps: (1) collected signal decomposed by variational modal decomposition (VMD) formulate repr...

A novel method named residual-variational mode decomposition (RVMD) is proposed in this study to extract bearing fault features accurately. RVMD can determine the number of modes and balance parameter adaptively, it has two stages. In first stage, signal decomposed into a series until correlation coefficient between raw results reaches threshold. redefined kurtosis, which resist interferences f...

The operating state of bearing affects the performance rotating machinery; thus, how to accurately extract features from original vibration signals and recognise faulty parts as early possible is very critical. In this study, one-dimensional ternary model which has been proved be an effective statistical method in feature selection introduced shapelet transformation proposed calculate parameter...