No abstract

Compared with the traditional assembly simulation based on theoretical models, this paper proposes a new pre-assembly analysis method of aircraft components based on measured data. Specifically, before the actual assembly of the product, digital measurement methods are used to obtain the measured data of the target features of the manufactured parts. Subsequently, the measured data is processed and reconstructed to obtain the actual geometric shape of the part, based on which the product is pre-assembled and analyzed to evaluate the assembly quality in advance. Finally, according to the analysis results, the assembly process is adjusted in time to reduce assembly trial and error and improve assembly quality and efficiency. This article systematically introduces the implementation process of the method, which is illustrated through two cases study on aircraft wing box assembly process. Experimental results demonstrate the feasibility and effectiveness of this proposed method for assembly of large aircraft components.

Aerospace framework products typically have a thin-walled structure. To ensure the aerodynamic performance of the product, it is necessary to precisely control the shim clearance between the understructure and the skin. However, it is difficult to meet the requirements of product design by digital measurements and calculations of the shim clearance after installing parts on the final assembly or special test stand. To improve the efficiency and accuracy of the shimming process, a method to determine the shimming quantity by a flexible virtual assembly without a physical assembly process is proposed. The proposed method measures the initial shape of the assembly using digital technology that analyzes the assembled shape using a finite element model and calculates the shimming space using the assembled shape. First, the geometric information of the understructure, skin inner mold line (IML), and outer mold line (OML), or the actual pre-assembly shape, are obtained using a three-dimensional laser digitizer. The geometric features are reconstructed and the coordinate transformation matrix is then calculated. The coordinate system is unified based on the positioning features of each part, such as the positioning surface and positioning hole. Finally, the OML of the measured model and the theoretical OML are flexibly fitted to simulate the ideal state of the assembly. The shimming space between the IML and the understructure is calculated and the OML is precisely controlled by shimming. The physical verification results show that the deviation between the analysis results and the actual situation is within 0.1 mm. This method can predict the space of shimming when the OML reaches the ideal state without real assembly thereby reducing the time required for a repeated trial assembly of products and the cost of special measuring tools and conformal tools.

The automated measurement mode in the lidar measurement system (LMS) has advantages unmatched by other measurement equipment in measuring the surface of large components. Before starting the automatic measurement mode, it is necessary to plan the measurement guide points for the measurement area. The rationality of the measurement points planning will directly affect the quality of the measurement data and the measurement efficiency. This paper proposes a planning method for measurement points on the outer surface of components based on lidar automatic measurement technology. First, the geometric features to be measured are discretized into spatial point cloud data. Second, the edge points of the point clouds are extracted and indented to meet the measurement requirements, which improves the measurement accuracy of the edge areas. Finally, by planning the path of the measurement points, the laser beam of the lidar can traverse the points of the measurement features with the shortest paths. Through the analysis of two cases, the method proposed in this paper will provide a huge advantage for the LMS: (1) The edge points of all features can be identified and indented in a short time to ensure the measurement accuracy of the edge areas of each measurement feature. (2) Through the measurement path planning, the repetitive measurement path of the lidar can be significantly reduced, improving the measurement efficiency. The method proposed in this paper has important guiding significance for the subsequent measurement station planning and constructing large-scale spatial measurement fields of the LMS.

This paper investigates the influence of the workpiece pose errors on gear skiving accuracy. First, based on the theory of homogeneous coordinate transformation, the mapping relationship between the tooth flank of the workpiece and the skiving tool is established according to the principle of gear skiving. Second, the workpiece pose errors are defined, and the relationship between each workpiece pose error and cutting depth is analyzed. According to the kinematic chain of the machine tool, a method for measuring the workpiece pose errors based on actual inverse kinematics is proposed. Third, the tooth deviations from individual workpiece pose errors, and the coupling workpiece pose errors are studied. The sensitive errors are obtained from the tooth deviation by numerical simulation. Finally, the numerical analysis is verified by gear skiving experiments, and the proposed method can be used to identify the possible workpiece pose errors. Furthermore, the PSO algorithm is introduced to guide the workpiece setting pose errors in the gear skiving process.