## 5 Conclusions  
To solve the problem that the existing crack detection methods have poor generalization ability and low accuracy for internal cracks, a detection scheme based on MSE-Faster R-CNN was proposed. Firstly, VGG-19 was employed as the baseline network to select crack candidate regions. Secondly, a novel design of MSE-Faster R-CNN detector was utilized to conduct feature fusion, classify the state of the candidate region and measure the crack position and length. The performance of the method was validated by different scales of numerical dataset. The following conclusions can be drawn:  
1. By comparing different state-of-art methods, experimental results showed that the internal crack detection by the proposed scheme had best performance at both large and small scale. The accuracy can reach 0.898 in location detection and 0.806 in crack  
Figure 7: Lifetime estimation and error rate of different porosity and legend in variation of crack length of using the information entropy model.  
detection. The proposed scheme can distinguish the differences between the small internal cracks and pores, but the detection error rate also increases.
2. Based on the localized diagnosis of cracks and the fusion lifetime estimation algorithm, the coating lifetime can be preliminarily evaluated by the crack detection results. The fusion lifetime estimation result with different crack lengths had acceptable RMSE (2.7) as well as time cost (1.63 s).
3. In future, further research should be promoted to detect other characteristics of internal cracks, such as density, morphology, crack orientation, etc. Current research mainly focuses on the diagnosis of a single crack. In reality, there may be multiple cracks at the same time. Due to the heat flow coupling effect between the cracks, this effect will have a complex impact on the temperature distribution. Current research regards the crack shape as an ellipse and regards crack orientation as almost straight, but in reality, there are other crack growth patterns and orientations. Such different growth patterns and orientations will have significant effects on the temperature distribution. In addition, the proposed scheme should be tested and improved using real data to validate the feasibility. Although transferring learning is used, which is helpful to the results, the existing datasets still need to be expanded at different scales.  
Conceptualization, Q.Z. and Y.W.; methodology, L.S.; software, L.S.; validation, L.S., Y.L. and X.C.; formal analysis, L.S., Y.L. and X.C.; investigation, L.S. and Y.L.; resources, L.S., Y.L. and X.C.; data curation, L.S. and Y.L; writing--original draft preparation, L.S.; writing--review and editing, L.S., Y.W. and Q.Z.; visualization, L.S.; supervision, L.S.; project administration, Y.W. and Q.Z.; funding acquisition, Y.W. All authors have read and agreed to the published version of the manuscript.  
This work was supported by National Science and Technology Major Project (2017-I-0007-0008).  
Not applicable.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
Not applicable.  
The authors declare no conflict of interest.