In this paper, a novel toolbox for bearing fault detection using the bearing vibration signals is proposed. Two baseline models are included: 1. Baseline for Feature Engineering Based Method, which consists of three steps: time-frequency feature extraction, Pearson Correlation Coefficient (PCC) reduction and classification. 2. Baseline for Deep Learning Based Methods: a powerful deep neural network model consists of Convolutional Blocks and Residual Blocks.