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It is always an important and challenging issue to achieve an effective fault diagnosis in rotating machinery in industries. In recent years, deep learning proved to be a high-accuracy and reliable method for data-based fault detection. However, the training of deep learning algorithms requires a large number of real data, which is generally expensive and time-consuming. To cope with this, we proposed a Resnet classifier with model-based data augmentation, which is applied for bearing fault detection. To this end, a dynamic model was first established to describe the bearing system by adjusting model parameters, such as speed, load, fault size, and the different fault types. Large amounts of data under various operation conditions can then be generated. The training dataset was constructed by the simulated data, which was then applied to train the Resnet classifier. In addition, in order to reduce the gap between the simulation data and the real data, the envelop signals were used instead of the original signals in the training process. Finally, the effectiveness of the proposed method was demonstrated by the real bearing experimental data. It is remarkable that the application of the proposed method can be further extended to other mechatronic systems with a deterministic dynamic model.

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In this study, we investigated the mediating effects of active procrastination and passive procrastination on the relationship between academic stress and academic performance. In addition, we proposed the moderating effect of academic self-efficacy on the relationship between academic stress and academic procrastination. According to the study, the influence of academic stress on academic performance is mediated by academic procrastination. When individuals perceive the academic stress, they will have better performance if they take active procrastinate while passive procrastination can produce poor performance. Moreover, when individuals have high self-efficacy, it will promote our active procrastination. That is to say, when the individual is aware of the academic stress, it is necessary to believe in their own ability and take active action, which will create good results.