A deep learning driven method for fault classification and degradation assessment in mechanical equipment.

•Deep learning method helps improve performance of degradation assessment.•Wavelet packet decomposition was leveraged to represent the features in both time and frequency domain.•Vibration-based condition monitoring techniques are discussed.•Comprehensive comparison was provided to validate the superiority of deep neural network in the experiment.•The superiority of deep learning in current industrial applications is interpreted.