## 5 Conclusions and Future Works  
In this paper, an experimental platform for the detection of crack faults in asymmetric shaft systems is designed and built independently. The experimental vibration data are collected, and the end-to-end crack location detection model based on a convolutional neural network is proposed. The influencing factors and effects of fault detection accuracy are deeply studied. The main conclusions are as follows: By comparing the accuracy of the method, support vector machine, random forest, xgboost and naive Bayesian algorithm in crack location detection task, it can be found that when the signal-to-noise ratio is 0 dB, the average accuracy of the method proposed is 100%, while the maximum accuracy of other machine learning algorithms is no more than 63%; thus the accuracy of this model is the highest. By comparing the method in this paper and the other four machine learning  
Figure 14: Confusion matrix under different numbers of training samples: (**a**) training samples = 300; (**b**) training samples = 500.  
Figure 13: Influence of training set sample number on accuracy.  
algorithms under different signal-to-noise ratios, it can be found that the method in this paper has the highest accuracy and the strongest anti-noise ability under the signal-to-noise ratio of \(-6\) dB to \(10\) dB. By comparing the model in this paper with different training sample numbers, the number of training samples plays a decisive role in the accuracy and anti-noise ability of the fault detection network. The strategy of data enhancement by overlapping sampling is effective. In addition, by analyzing the confusion matrix under a different number of training samples, it can be found that the reduction of the number of training samples makes the cracks on the right side of the single disk rotor and the double disk rotor easy to be misclassified into other working conditions.  
This research has great applicability prospects for carrying out a fault detection method based on the combination of deep learning and experiment and migrating it to practical industrial applications. This paper only considers the study pd crack faults of asymmetric shafting. In the future, we will carry out more experimental research on rotor fault types, enrich the data set and further carry out the study on the transfer and application of this model to actual industrial data.  
Conceptualization, C.W. and Z.Z.; methodology, C.W. and Z.Z.; software, C.W.; validation, Z.Z. and D.G.; formal analysis, T.L.; investigation, C.W.; re-sources, Z.Z.; data curation, C.W. and Z.Z.; writing--original draft preparation, C.W.; writing--review and editing, D.G. and Z.Z.; visualization, T.L.; supervision, Y.X.; project administration, D.Z.; funding acquisition, D.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by [[PERSON], [PERSON]] grant number [111 project (B16038)].  
Not applicable.  
Data Availability Statement: Data is unavailable due to privacy.  
The authors gratefully acknowledge the financial support by the 111 Project P.R. China (Grant No. B16038).  
The authors declare no potential conflict of interest with respect to the research, authorship, and/or publication of this article.