Aiming at the problems of low efficiency and poor accuracy in conventional surface defect detection methods for aero-engine components, a surface defect detection model based on an improved YOLOv5 object detection algorithm is proposed in this paper. First, a k-means clustering algorithm was used to recalculate the parameters of the preset anchors to make them match the samples better. Then, an ECA-Net attention mechanism was added at the end of the backbone network to make the model pay more attention to feature extraction from defect areas. Finally, the PANet structure of the neck network was improved through its replacement with BiFPN modules to fully integrate the features of all scales. The results showed that the mAP of the YOLOv5s-KEB model was 98.3%, which was 1.0% higher than the original YOLOv5s model, and the average inference time for a single image was 2.6 ms, which was 10.3% lower than the original model. Moreover, compared with the Faster R-CNN, YOLOv3, YOLOv4 and YOLOv4-tiny object detection algorithms, the YOLOv5s-KEB model has the highest accuracy and the smallest size, which make it very efficient and convenient for practical applications.

Diffusion aluminum coating is crucial to protect aero-engine turbine blades from high-temperature oxidation. Slurry aluminizing, as a commonly-used coating preparation technology, has variations in the process parameters that directly affect the quality of the coating. Therefore, this paper investigates the effect of slurry thickness on coating quality. Different forms of aluminized coatings were obtained by coating nine DZ22B nickel-based superalloy plates of the same size with different slurry thicknesses while keeping other parameters constant. These aluminized coatings were characterized using a scanning electron microscope (SEM) with an energy dispersive spectrometer (EDS), an X-ray diffractometer (XRD), and a surface gauge. The results show that the AlNi phase dominates the matrix of the aluminized coating, and the outer layer of the coating has white dotted precipitates of Cr. As the slurry thickness increases, the coating thickness increases, and the proportion of the outer layer in the overall coating increases. In contrast, the thickness of the interdiffusion layer does not change significantly. The thicker the slurry, the higher the Al content of the coating surface. A medium-thickness slurry can form a smooth aluminizing coating with a roughness Ra < 4.5 μm surface. The combined results show that a medium-thick slurry can produce a high-quality coating.

Oscillatory pressure sintering is a novel crystal refinement technology. The doping of different concentrations of ZrB₂ under oscillatory sintering technology (9 Hz) is discussed here, focusing on its macroscopic mechanics and oxidation resistance. In particular, doping 2.5 wt% ZrB₂ can effectively increase the hardness of the alloy, slightly increase the fracture toughness of the alloy and have an outstanding effect on the oxidation resistance of the alloy at 1300 °C, achieving the effect of reducing mass loss by 80.3%.

Molybdenum silicon boron alloy is regarded as the next generation of superalloy that is expected to replace nickel-based superalloys. However, the high-temperature oxidation resistance of Mo-Si-B alloy has always been an issue worth studying. In this study, Mo-9Si-8B alloy was prepared via a plasma oscillatory pressure sintering process and pre-oxidized at 1300 °C while maintaining a certain balance of mechanical and oxidation properties. The influence of the oxide protective layer on its performance at high temperature of 1150 °C was explored, the micro-mechanism of its performance and its failure mode of the hinge-locking mechanism was illustrated, and finally, its oxidation kinetics was inferred. In conclusion, pre-oxidized Mo-9Si-8B (at.%) alloy did play a role in delaying the oxidation process during the initial period of cyclic oxidation. However, with the increase of cyclic oxidation time, the improvement of high-temperature oxidation resistance was limited.