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Several advantages of directed energy deposition-arc (DED-arc) have garnered considerable research attention including high deposition rates and low costs. However, defects such as discontinuity and pores may occur during the manufacturing process. Defect identification is the key to monitoring and quality assessments of the additive manufacturing process. This study proposes a novel acoustic signal-based defect identification method for DED-arc via wavelet time–frequency diagrams. With the continuous wavelet transform, one-dimensional (1D) acoustic signals acquired in situ during manufacturing are converted into two-dimensional (2D) time–frequency diagrams to train, validate, and test the convolutional neural network (CNN) models. In this study, several CNN models were examined and compared, including AlexNet, ResNet-18, VGG-16, and MobileNetV3. The accuracy of the models was 96.35%, 97.92%, 97.01%, and 98.31%, respectively. The findings demonstrate that the energy distribution of normal and abnormal acoustic signals has significant differences in both the time and frequency domains. The proposed method is verified to identify defects effectively in the manufacturing process and advance the identification time. [ABSTRACT FROM AUTHOR]

The aim of this paper is to address the surface reconstruction from point cloud in reverser engineering. The data was acquired through a 3D scan device and was processed as point cloud data. The points in cloud were connected to build 3D surface. The points cloud was processed in four steps to get 3D information surface. First, the subtraction scheme was used to get cover boxes ended with the set of convex was found under the convergence rule. Secondly, the points in the box were projected to the directions which were close to the normal direction method. Thirdly the overlap was avoided by using convergence rule and inner subdivision rule. Finally the information model was used to reconstruction. The method was used in landslide monitoring of Three Gorges area for 3D surface reconstruction and monitoring. The reconstruction method obtains high precision and low complexity. It is effective for large scale monitoring.

In this study, a direct synthesis approach is proposed to extract the coupling matrix of multi‐port filtering power divider (FPD) with arbitrary phase shift, power division as well as reference impedances, for the first time. This method provides an attractive technique to synthesise a multi‐functional device that combines the characteristics of bandpass filter, multi‐port power divider and ideal phase shifters as well as the impedance matching network, which can effectively diminish the overall size and improve the performance of the microwave front‐end network. A newly defined coupling matrix corresponding to arbitrary multi‐port topologies that introduces ideal phase shift by virtue of constant frequency‐independent reactance at the source and load is developed in FPD synthesis process. The coupling matrix is obtained directly by optimising the presented cost‐function in this paper, avoiding complex similar transformation process of coupling matrix. Finally, several numerical examples of multi‐port FPD with equal/unequal power division ratio, arbitrary phase shift and reference impedances are synthesised to well verify the proposed synthesis method, and a practical example is given to verify the validity of arbitrary phase shift and arbitrary reference impedance. [ABSTRACT FROM AUTHOR]