High-precision and high-density three-dimensional point cloud models usually contain redundant data, which implies extra time and hardware costs in the subsequent data processing stage. To analyze and extract data more effectively, the point cloud must be simplified before data processing. Given that point cloud simplification must be sensitive to features to ensure that more valid information can be saved, in this paper, a new simplification algorithm for scattered point clouds with feature preservation, which can reduce the amount of data while retaining the features of data, is proposed. First, the Delaunay neighborhood of the point cloud is constructed, and then the edge points of the point cloud are extracted by the edge distribution characteristics of the point cloud. Second, the moving least-square method is used to obtain the normal vector of the point cloud and the valley ridge points of the model. Then, potential feature points are identified further and retained on the basis of the discrete gradient idea. Finally, non-feature points are extracted. Experimental results show that our method can be applied to models with different curvatures and effectively avoid the hole phenomenon in the simplification process. To further improve the robustness and anti-noise ability of the method, the neighborhood of the point cloud can be extended to multiple levels, and a balance between simplification speed and accuracy needs to be found.

Multisensor systems can overcome the limitation of measurement range of single-sensor systems, but often require complex calibration and data fusion. In this study, a three-dimensional (3D) measurement method of four-view stereo vision based on Gaussian process (GP) regression is proposed. Two sets of point cloud data of the measured object are obtained by gray-code phase-shifting technique. On the basis of the characteristics of the measured object, specific composite kernel functions are designed to obtain the initial GP model. In view of the difference of noise in each group of point cloud data, the weight idea is introduced to optimize the GP model, which is the data fusion based on Bayesian inference method for point cloud data. The proposed method does not require strict hardware constraints. Simulations for the curve and the high-order surface and experiments of complex 3D objects have been designed to compare the reconstructing accuracy of the proposed method and the traditional methods. The results show that the proposed method is superior to the traditional methods in measurement accuracy and reconstruction effect.

For the cooling method in surfacing repairing, most of the research focuses on the method based on the fixture structure. However, due to the low thermal conductivity and ultrathin alloy blade, the heat transfer speed from the molten pool to fixture is slow. When the heat is transferred to the fixture, most of the molten pool has solidified and absorbed or segregated out some impurities. Therefore, how to cool the welding area directly is more critical. For this reason, the thermal cycle characteristics of typical points of the blade and the heat transfer process of the key area of the fixture are analyzed, the original cooling time is calculated, and two innovative cooling methods based on lateral forced convection cooling and vertical jet impact forced convection cooling are proposed. For lateral forced cooling, with “AF-field” lateral convection cooling modeling, the cooling effects of characteristic points and sections under different flow velocities are calculated. For vertical jet impact cooling, the pressure, flow rate, and convective heat flux distribution on the wall under different impact heights and nozzle diameter are calculated. The influence of different inlet flow rates on cooling performance is influenced, based on the analysis results of impact modeling, the moving heat sink model is established, and the cooling effect under different heat sink-source distances is calculated. The heat transfer rules of two methods are analyzed in detail through modeling and simulations. The results show that both methods can improve the cooling effect and the vertical jet impact cooling method has an effect that is more obvious. When the nozzle radius is 2 mm, the impact height is 4d, the inlet flow velocity is 35 m/s, and the distance is 7 mm, and the cooling time under the vertical jet impact method is shortened by 12.5%, which can achieve better cooling effect. The experiment further validates the effectiveness of the modeling and simulations.

Currently, how to release the heat accumulated in the molten pool rapidly is the key factor in blade repair. We analyzed the problem of the current cooling method in blade additive manufacturing repair. Based on cooling effect, we proposed an advanced flexible multiflow path fixture cooling method for blade additive manufacturing repair. We created a coupled heat transfer model and deduced the heat transfer law for multiflow path conjugate flexible clamping. We obtained the optimal cooling scheme for flexible multiflow paths through numerical analysis. We built an experimental platform and tested the cooling effect of the fixture prototype by experiment. The results show that compared with the current cooling method, the new cooling method not only can lower the initial temperature of the fixture rapidly and realize the steady-state heat transfer between the fixture and the flow path quickly but can also significantly enhance the ability of fluid to participate in heat transfer in new flow paths, which significantly improves the cooling effect. The research results are of great significance for the improvement of aero blade additive manufacturing repair. INDEX TERMS Cooling method, blade repair, flexible fixture, numerical analysis, heat transfer.

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