No abstract

Purpose The size of the aircraft tooling structure is huge, and the ambient temperature is difficult to maintain a constant state. Aiming at the influence of current temperature, this paper aims to propose a compensation method for registration error of large-scale measurement fields based on multi-temperature sensors. Design/methodology/approach In this method, an enhanced reference points (ERS)–temperature regression model is constructed from ERS and temperature data. The ERS offsets compensation model is established by solving the offset through the regression model, and the ERS offset compensation analysis is carried out. Findings The experimental results show that the proposed registration error compensation algorithm has obvious advantages over traditional methods in reducing the influence of ambient temperature and improving the measurement accuracy by reducing the registration error. Originality/value This method reduces registration error caused by the influence of ambient temperature and is used for aircraft measurements in different temperature environments.

The combination of large tooling size, environmental vibration, and equipment errors at the aircraft assembly site leads to errors in the enhanced reference system (ERS) point measurement information. ERS point errors directly reduce the accuracy of the assembly measurement field. This paper proposes ERS point error prediction and registration compensation based on the neural network to address this problem. First, the effects of equipment measurement errors and environmental vibration factors on the measurement field are studied. The ERS point error prediction model based on the neural network is established. On this basis, model evaluation is used to assess the prediction model of this paper. Then, a measurement field registration compensation model is constructed based on the neural network error results for ERS point compensation analysis. Finally, an experimental validation platform was built to predict the ERS point errors and compensate for the constructed measurement fields using the method in this paper. The experimental results show that, compared with the conventional method, the maximum registration errors in the X, Y, and Z directions are reduced from 0.0812, −0.0565, and −0.2810 to −0.0184, −0.0010, and 0.0022 mm, respectively, after compensation in this paper. The method proposed in this paper can not only predict the ERS point error state and provide a reference for designers but also guide the selection of appropriate ERS points when constructing the measurement field. The compensation method in this paper effectively reduces the measurement field registration error.

Purpose In the digital assembly system of large aircraft components (LAC), the docking trajectory of LAC is an important factor affecting the docking accuracy and stability of the LAC. The main content of docking trajectory planning is how to move the LAC from the initial posture and position to the target posture and position (TPP). This paper aims to propose a trajectory planning method of LAC based on measured data. Design/methodology/approach First, the posture and position error model of the wing is constructed according to the measured data of the measurement points (MPs) and the fork lug joints. Second, the particle swarm optimization algorithm based on the dynamic inertia factor is used to optimize the TPP of the wing. Third, to ensure the efficiency and stability of posture adjustment, the S-shaped curve is used as the motion trajectory of LAC, and the parameters of the trajectory are solved by the generalized multiplier method. Finally, a series of docking experiments are carried out. Findings During the process of posture adjustment, the motion of the numerical control locator (NCL) is stable, and the interaction force between the NCLs is always within a reasonable range. After the docking, the MPs are all within the tolerance range, and the coaxiality error of the fork lug hole is less than 0.2 mm. Originality/value In this paper, the measured data rather than the theoretical design model is used to solve the TPP, which improves the docking accuracy of LAC. Experiment results show that the proposed trajectory method can complete the LAC docking effectively and improve the docking accuracy.