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To obtain spray resistance directly, a prismatic planing hull test was conducted in a towing tank in static water. The characteristic angles of the standing line and leading edge line of the spray zone were obtained through the fixed flight test of the whole prismatic planing hull. The prismatic planing hull was divided into front and rear parts along the standing line, and then the fixed flight state test of the split planing hull was carried out, and the spray resistance was directly measured by the front planing hull. The results show that the percentage of splash resistance in the total resistance is from 15.83 % to 30.10 % under the condition of high-speed planing; Split planing hull model test is an effective method for direct measurement of spray resistance.

Plane welds are a common type of weld in industrial sites. When the welding robot welds multiple types of plane welds at the same time, the traditional teaching and programming modes become relatively complicated. Therefore, in order to solve the problem of automatic robot welding of various types of plane welds, taking plane V-type butt, plane I-type butt, and plane lap welds as examples, this paper proposes a plane weld extraction method based on 3D vision. Firstly, in order to realize the line and plane segmentation of the workpiece point cloud, we establish the concept of plane point cloud density. Secondly, to segment workpiece edge lines, an iterative segmentation algorithm based on RANSAC is proposed. Then, based on the geometric features of the workpiece, a method for extracting weld feature points based on centroid positioning is proposed. Finally, the least squares method is used to fit the feature points of the welding seam to complete the welding trajectory planning. The experimental results show that the method can well solve the problem of automatic planning welding trajectory of plane V-type butt, plane I-type butt, and plane lap welds, to realize that the welding robot can simultaneously weld various plane welds without teaching and programming.

This study aims to identify the conveyor belt deviation. It presents a machine vision-based detection approach that uses the coordinates of the crossing point between the conveyor belt centerline and the laser line to determine whether the deviation fault occurs. In order to avoid the influence of the defects of the traditional Canny operator, an improved Canny edge detection algorithm combining hybrid filter and maximum inter-class variance method (OTSU) is used. Then the Hough transform is used to detect the straight line of the edge detected image and extract the laser centerline with the centerline extraction algorithm; finally, the Shi-Tomasi operator is used to detect the corners to get the intersection of the edge line and the laser line. The slope and center coordinates of the conveyor belt edges are calculated to determine whether the conveyor belt has run-off faults and calculate the offset amount. The results show that the proposed method can accurately determine the conveyor belt deviation and calculate the deviation amount.

Autonomous landing of aircraft during the approaching stage is a crucial part of the autonomous driving of aircraft. This paper mainly investigates the localization problem of aircraft during the end stage of the approaching process via a visual technique. To robustly identify the mark corners, a dedicated algorithm was proposed for a convex quadrilateral. The results proved its effectiveness, and the way for the marks′ edge line optimization was also presented. Moreover, different ways for updating runway parameters as well as selecting key points for pose estimation were also investigated in detail. It proved that continuously updating runway parameters related to mark corners distant from the camera with those close to the camera helps greatly improve the quality of runway parameter estimation. Besides, updating runway parameters forward favors the accuracy of runway parameters estimated, as runway parameters related to mark corners close to the camera hold better accuracy than those far from the camera. It also proved that taking mark corners as the key points is not a good way for pose estimation, as it involves errors at both the x and y coordinates. However, using the cross points between the side lines′ edges and the runway marks′ horizontal edge lines as the key points was much better, as it only involves an inaccuracy in the y coordinate. According to this investigation, cross points related to horizontal lines close to the camera are essential for ensuring pose estimation accuracy, while taking as many horizontal lines as possible for generating key points with side lines helps improve pose estimation accuracy.

To solve the problems of high repeatability and enormous time cost in the calculation process of the analytical prediction model of milling force, this paper establishes an efficient analytical prediction model based on the contact relationship between the tool and the workpiece. Transform this contact relationship into the relationship between the helical line in a two-dimensional plane and the milling area. The reasons for the change of milling force caused by tool geometric parameters ( helix angle, milling cutter radius, cutting edge number) and cutting parameters (depth of cut, width of cut) are analyzed. The expression of the two-dimensional cutting contact relationship is established, and the milling force prediction model without window function is constructed by combining the numerical simulation model, which simplifies the repetitive calculation steps in the calculation process and defines the boundary conditions of the milling area. The established two-dimensional equation of the micro-element cutting force function and the spatial cutting edge line in the milling region is used as the basis of the milling force prediction model, which not only ensures the accuracy of milling force prediction but also improves the calculation efficiency of the model. After the cutting experiments of multiple machining parameters and tool geometric parameters, the prediction results of the model are compared with the experiments, proving the model’s effectiveness. Compared with the existing milling force prediction model, the computational efficiency has been greatly improved.

The surface quality of the workpiece has a great impact on the performance of the product. It has always been a key issue of the manufacturing discipline. The different wear levels of cutting tools determine the surface quality of the workpiece. Therefore, the work of this article is to establish a model for calculate the surface quality of the workpiece after milling. First, by defining the tool wear area S and the wear position angle ψ , the cutting edge line model of the tool is determined. Based on the tool motion trajectory and roughness calculation principle, a milling topography simulation roughness model considering tool wear is obtained. Secondly, the tool wear parameters were calibrated with the help of image detection methods, and the predicted values obtained by the model were compared with the experimental values. The law of the influence of the tool wear area S and the wear position angle ψ on the roughness parameters was obtained. Finally, the least squares support vector machine LS-SVM was used to verify the error of the roughness model of the milling topography simulation, and the result showed that the average error of the model was 8.68%.

Conical end milling cutter is used more and more widely in NC machining. The flute is an important feature of the milling cutter, which directly affects the cutting performance of the milling cutter. However, the conical flute belongs to a complex spatial helix surface. In the machining process, the relative motion of the wheel and milling cutter is complex. To solve this problem, this paper presents a trajectory calculation method for grinding the flute of conical milling cutters. Firstly, the conical cutting edge line is deduced, and the position of the wheel in the whole grinding process is calculated under the design requirements of the rake angle and the core radius. Secondly, a method for calculating the flute profile of complex flutes is given. Finally, the effectiveness of this method is verified by numerical simulation, and it can also be extended to more complex flute grinding in future research.

Graphene zigzag nanoribbons, initially in a topologically ordered state, undergo a topological phase transition into crossover phases distinguished by quasi-topological order. We computed mutual information for both the topologically ordered phase and its crossover phases, revealing the following results: (i) In the topologically ordered phase, A-chirality carbon lines strongly entangle with B-chirality carbon lines on the opposite side of the zigzag ribbon. This entanglement persists but weakens in crossover phases. (ii) The upper zigzag edge entangles with non-edge lines of different chirality on the opposite side of the ribbon. (iii) Entanglement increases as more carbon lines are grouped together, regardless of the lines’ chirality. No long-range entanglement was found in the symmetry-protected phase in the absence of disorder.

Talar fractures often require osteotomy during surgery to achieve reduction and screw fixation of the fractured fragments due to limited visualization and operating space of the talar articular surface. The objective of this study was to evaluate the horizontal approach to the medial malleolus facet by maximizing exposure through dorsiflexion and plantarflexion positions. In dorsiflexion, plantarflexion, and functional foot positions, we respectively obtained the anterior and posterior edge lines of the projection of the medial malleolus on the medial malleolar facet. The talar model from Mimics was imported into Geomagic software for image refinement. Then Solidworks software was used to segment the medial surface of the talus and extend the edge lines from the three positions to project them onto the \"semicircular\" base for 2D projection. The exposed area in different positions, the percentage of total area it represents, and the anatomic location of the insertion point at the groove between the anteroposternal protrusions of the medial malleolus were calculated. The mean total area of the \"semicircular\" region on the medial malleolus surface of the talus was 542.10 ± 80.05 mm2. In the functional position, the exposed mean area of the medial malleolar facet around the medial malleolus both anteriorly and posteriorly was 141.22 ± 24.34 mm2, 167.58 ± 22.36mm2, respectively. In dorsiflexion, the mean area of the posterior aspect of the medial malleolar facet was 366.28 ± 48.12 mm2. In plantarflexion, the mean of the anterior aspect of the medial malleolar facet was 222.70 ± 35.32 mm2. The mean overlap area of unexposed area in both dorsiflexion and plantarflexion was 23.32 ± 5.94 mm2. The mean percentage of the increased exposure area in dorsiflexion and plantarflexion were 36.71 ± 3.25% and 15.13 ± 2.83%. The mean distance from the insertion point to the top of the talar dome was 10.69 ± 1.24 mm, to the medial malleolus facet border of the talar trochlea was 5.61 ± 0.96 mm, and to the tuberosity of the posterior tibiotalar portion of the deltoid ligament complex was 4.53 ± 0.64 mm. Within the 3D model, we measured the exposed area of the medial malleolus facet in different positions and the anatomic location of the insertion point at the medial malleolus groove. When the foot is in plantarflexion or dorsiflexion, a sufficiently large area and operating space can be exposed during surgery. The data regarding the exposed visualization area and virtual screws need to be combined with clinical experience for safer reduction and fixation of fracture fragments. Further validation of its intraoperative feasibility will require additional clinical research.

Power system maintenance is an important guarantee for the stable operation of the power system. Power line autonomous inspection based on Unmanned Aerial Vehicles (UAVs) provides convenience for maintaining power systems. The Power Line Extraction (PLE) is one of the key issues that needs solved first for autonomous power line inspection. However, most of the existing PLE methods have the problem that small edge lines are extracted from scene images without power lines, and bringing about that PLE method cannot be well applied in practice. To solve this problem, a PLE method based on edge structure and scene constraints is proposed in this paper. The Power Line Scene Recognition (PLSR) is used as an auxiliary task for the PLE and scene constraints are set first. Based on the characteristics of power line images, the shallow feature map of the fourth layer of the encoding stage is transmitted to the middle three layers of the decoding stage, thus, structured detailed edge features are provided for upsampling. It is helpful to restore the power line edges more finely. Experimental results show that the proposed method has good performance, robustness, and generalization in multiple scenes with complex backgrounds.