Automated fibre placement (AFP) machine in-process layup inspection is essential for composite structure fabrication efficiency and quantity improvement. The laser profilometer scanning technique is one of the automated in-process inspection techniques. Laser profilometers can capture a large number of intensive high-resolution point clouds during the layup. To date, few studies have been published about processing point clouds at high speed for in-process layup defect detection and layup feature measurement. In this study, an algorithm called the cross-sectional line-processing algorithm was proposed, and a testbed was constructed to validate the algorithm. The algorithm processes each laser line captured by the laser profilometer and clusters the processed results together. Finally, the defect features and layup features can be segmented and recognized from the collected point cloud. Layup defect types can be recognized, and the dimensions of the layup features can be measured. The experimental results show that this approach can process at most 200 laser lines (about 160 000 points) per second, and the overall defect type recognition accuracy rate reaches about 78%, which meets basic AFP in-process inspection requirements.

Purpose: The purpose of this paper is to present an optimal posture evaluation model to control the assembly gaps in aircraft wing assembly. The gaps between two mating surfaces should be strictly controlled in precision manufacturing. Oversizing of gaps will decrease the dimensional accuracy and may reduce the fatigue life of a mechanical product. To reduce the gaps and keep them within tolerance, the relative posture (orientation and position) of two components should be optimized in the assembly process. Design/methodology/approach: Based on the step alignment strategy, i.e. preliminary alignment and refined alignment, the concept of a small posture transformation (SPT) is introduced. In the preliminary alignment, an initial posture is estimated by a set of auxiliary locating points, with which the components can be quickly aligned near each other. In the refined alignment, the assembly gaps are calculated and the formulation of the gaps with component posture is derived by the SPT. A comprehensive weighted minimization model with gap tolerance constraints is established for redistributing the gaps in multi-regions. Powell-Hestenes-Rockafellar optimization, Singular Value Decomposition and K-Dimensional tree searching are introduced for the solution of the optimal posture for localization. Findings: Using the SPT, the trigonometric posture transformation is linearized, which benefits the iterative solution process. Through the constrained model, overall gaps are minimized and excess gaps are controlled within tolerance. Practical implications: This method has been tested with simulated model data and real product data, the results of which have shown efficient coordination of mating components. Originality/value: This paper proposed an optimal posture evaluation method for minimizing the gaps between mating surfaces through component adjustments. This will promote the assembly automation and variation control in aircraft wing assembly.

Purpose: This paper aims to provide a shimming method based on scanned data and finite element analysis (FEA) for a wing box assembly involving non-uniform gaps. The effort of the present work is to deal with gap compensation problem using hybrid shims composed of solid and liquid forms. Design/methodology/approach: First, the assembly gaps of the mating components are calculated based on the scanned surfaces. The local gap region is extracted by the seed point and region growth algorithm from the scattered point cloud. Second, with the constraints of hole margin, gap space and shim specification, the optional shimming schemes are designed by the exhaustive searching method. Finally, the three-dimensional model of the real component is reconstructed based on the reverse engineering techniques, such as section lines and sweeping. Using FEA software ABAQUS, the stress distribution and damage status of the joints under tensile load are obtained for optimal scheme selection. Findings: With the scanned mating surfaces, the non-uniform gaps are digitally evaluated with accurate measurement and good visualization. By filling the hybrid shims in the assembly gaps, the joint structures possess similar load capacity but stronger initial stiffness compared to the custom-shimmed structures. Practical implications: This method has been tested with the interface data of a wing tip, and the results have shown good efficiency and automation of the shimming process. Originality/value: The proposed method can decrease the manufacturing cost of shims, shorten the shimming process cycle and improve the assembly efficiency.

Dimensional variation in aircraft panel assembly is one of the most critical issues that affect the aerodynamic performance of aircraft, due to elastic deformation of parts during the positioning and clamping process. This article proposes an assembly deformation prediction model and a variation propagation model to predict the assembly variation of aircraft panels, and it derives consecutive three-dimensional deformation expressions which explicitly describe the nonlinear behavior of physical interaction occurring in compliant components assembly. An assembly deformation prediction model is derived from equations of statics of elastic beam to calculate the elastic deformation of panel component resulted from positioning error and clamping force. A variation propagation model is used to describe the relationship between local variations and overall assembly variations. Assembly variations of aircraft panels due to positioning error are obtained by solving differential equations of statics and operating spatial transformations of the coordinate. The calculated results show a good prediction of variation in the experiment. The proposed method provides a better understanding of the panel assembly process and creates an analytical foundation for further work on variation control and tolerance optimization.