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Large gear components widely exist in the transmission system of helicopters, ships, etc. Due to the small assembly clearance of large gear components, using an automatic docking system based on position control will lead to forced assembly. The purpose of this paper is to reduce the assembly stress of large gear components by an active compliant docking technology based on distributed force sensors.

Firstly, aiming at the noise interference in three-dimensional force sensor (TDFS), Kalman filter and Savitzky–Golay filter are used to process the sensor’s output signal. Secondly, the active compliant docking control model is constructed according to the principle of impedance control. Thirdly, the contact force is calculated based on the Euler equation, and the impedance control parameters are tuned by the particle swarm optimization algorithm. Finally, an active compliant docking system of a large gear structure based on distributed force sensor is built in the laboratory to verify the proposed method.

The experimental results show that the contact force and contact torque gradually decrease in all directions and are always in the safe range during the docking process. The feasibility of this method in practical application is preliminarily demonstrated.

The distributed TDFSs are used to replace the traditional six-dimensional force sensor in the active compliant docking system of gear components, which solves the problem of the small bearing capacity of the conventional active compliant docking system. This method can also be used for the docking of other large components.

The assembly of large component in out-field is an important part for the usage and maintenance of aircrafts, which is mostly manually accomplished at present, as the commonly used large-volume measurement systems are usually inapplicable. This paper aims to propose a novel coaxial alignment method for large aircraft component assembly using distributed monocular vision.

For each of the mating holes on the components, a monocular vision module is applied to measure the poses of holes, which together shape a distributed monocular vision system. A new unconstrained hole pose optimization model is developed considering the complicated wearing on hole edges, and it is solved by a iterative reweighted particle swarm optimization (IR-PSO) method. Based on the obtained poses of holes, a Plücker line coordinates-based method is proposed for the relative posture evaluation between the components, and the analytical solution of posture parameters is derived. The required movements for coaxial alignment are finally calculated using the kinematics model of parallel mechanism.

The IR-PSO method derived more accurate hole pose arguments than the state-of-the-art method under complicated wearing situation of holes, and is much more efficient due to the elimination of constraints. The accuracy of the Plücker line coordinates-based relative posture evaluation (PRPE) method is competitive with the singular value decomposition (SVD) method, but it does not rely on the corresponding of point set; thus, it is more appropriate for coaxial alignment.

An automatic coaxial alignment system (ACAS) has been developed for the assembly of a large pilotless aircraft, and a coaxial error of 0.04 mm is realized.

The IR-PSO method can be applied for pose optimization of other cylindrical object, and the analytical solution of Plücker line coordinates-based axes registration is derived for the first time.

The measurement of aircraft barycenter is a verification of theoretical barycenter and is an important step of aircraft development. In the traditional measurement method of aircraft barycenter, the posture of the aircraft needs to be adjusted manually and is measured by optical instruments. The efficiency of posture adjustment depends on the proficiency of workers, and the accuracy of measurement is not high. In view of these problems of the current barycenter measurement method, this paper aims to propose an aircraft barycenter measurement method based on multi-posture.

In this method, the numerical control locator is used as a supporting part to fix and adjust the aircraft, and the calculation model of aircraft barycenter is established according to the principle of rigid body rotation and the principle of moment balance. Then, the influence of the main error sources on the measurement accuracy of aircraft barycenter is analyzed by Monte Carlo simulation, and the measurement accuracy is compared with that of the barycenter measurement method based on horizontal posture. Finally, the experiment platform of barycenter measurement was built in the laboratory and the experiments were carried out.

The experimental results show that the barycenter measurement method proposed in this paper has obvious advantages in measurement accuracy and efficiency compared with the traditional method.

This method can be used to measure the barycenter of different types of aircraft quickly and automatically.

The purpose of this paper is to propose an assembly coordination modelling approach based on measured data for assembly quality control of multi-constrained objects in aircraft assembly. This approach aims to establish a high-precision digital mirror of physical assembly system in the virtual environment, with which the assembly process in the virtual environment can be performed synchronously with that in the physical world.

This paper presents a realistic geometrical representation model based on measured point cloud, as well as the multiple constraints modelling methods for local and global constraints with the proposed representation model. For the assembly target optimization, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, where the particle swarm optimization and simulated annealing algorithm are combined to calculate the optimal solutions.

As shown in the validation results, the minimum easiness value for easiness model in global optimization is 3.01, while the best value for weighting model by adjusting weights for more than 10 times is 1.94. The results verify that the proposed coordination modelling approach is effective to the assembly of multi-constrained objects, and the optimization model has an obvious advantage over the traditional weighting method.

This paper provides a new idea for the fine control of assembly quality of non-ideal components by introducing the measured data into the on-line assembly process. Besides, a novel optimization method based on the evaluation of multi-dimensional tolerance zone is proposed, which overcomes the problem of traditional weighting model wherein the weightings are difficult to determine.

In aircraft assembly, standard reference points with nominal coordinates are commonly applied for coordinate transformation between multiple measurement stations and the assembly coordinate system. For several reasons in practical application, these points often fail to envelop the key assembly space, which leads to large transformation uncertainty. This paper aims to analyze and further reduce the coordinate transformation uncertainty by introducing a new hybrid reference system (HRS).

Several temporary extension points without known coordinates are added to enhance the tightness between different stations, especially at the weakness area in the network, thus constituting an HRS together with the existing standard reference points. The coordinate transformation model of the HRS-based measurement network is established based on an extend Gauss–Markov model. By using the geometrical differential property and variance-covariance propagation law, the covariance matrixes in the transformation model are calculated, and the analytical solution of the uncertainties of transformation parameters are ultimately derived. The transformation uncertainty of each check points is presented by Helmert error expression.

The proposed analytical solution of transformation uncertainty is verified using the state-of-the-art Monte Carlo simulation method, but the solution process is simpler and the computation expenses are much less.

The HRS with three temporary extension points is practically applied to a tail boom in-site measurement for assembly. The average transformation uncertainty has been reduced by 26 per cent to less than 0.05 mm.

The hybrid coordinate transformation model is proposed for the first time. The HRS method for transformation uncertainty reduction is more economical and practical than increasing the number of standard reference points.

Posture adjustment plays an important role in spacecraft manufacturing. The traditional posture adjustment method, which has a large workload and is difficult to guarantee the quality of posture adjustment, cannot meet the requirements of modern spacecraft manufacturing. This paper aims to optimize the trajectory of posture adjustment, reduce the internal force of the posture adjustment mechanism and improve the accuracy of the system.

First, the measuring point is measured by a laser tracker and the position and posture of the cabin is solved. Then, Newton–Euler method is used to construct the dynamic model of the posture adjustment system (PAS) without internal force. Finally, the adjustment time is optimized based on Fibonacci search method and the trajectory of the cabin is fitted by the fifth order polynomial.

The simulation results show that, compared with the other trajectory planning methods, this method can effectively avoid the internal force of posture adjustment caused by redundant driving, and the trajectory of velocity and acceleration obtained are continuous, meeting the engineering constraints.

In this paper, a dynamic model of PAS without internal force is constructed. The trajectory planning of posture adjustment based on this model can improve the quality of cabin assembly.

This study aims to examine the demographic differences of Chinese nationals’ travel experience sharing through different offline and online platforms.

Cross-tabulation analysis was applied on a national sample of 6081 respondents in China.

The study found that Chinese women tend to share travel experience more often than Chinese men; old people in China tend to use the face-to-face approach more than online or social media to share their travel experience. About 66.5 per cent of the survey sample used WeChat Moments to share their travel experience, highlighting WeChat as the dominating social media platform in China for travel sharing. In general, people who share via online platforms (WeChat, Weibo, QQ Space) tend to be young, single or unmarried, well-educated and earning a high monthly income.

The study offers an in-depth understanding of travel experience sharing idiosyncrasies in China.

By using Technology Acceptance Model, the purpose of this study is to investigate how the perceived usefulness and ease-of-use of shopping mobile apps affects consumer’s flow experience, attitude, impulsive buying tendency (IBT) and urge to impulsive buying on halal fashion products.

A quantitative study was done on 357 Indonesian online shoppers to find out how perceived usefulness and ease of use of mobile shopping apps affect impulsive buying tendencies and urges on halal fashion products. Flow experience and attitude were used as mediating variables, and the research hypotheses were tested using Partial Least Square Structural Equation Modeling (PLS-SEM).

This study confirmed significant positive relationships between perceived usefulness and ease of use of mobile apps, flow experience, attitude, IBT and urge to impulsive buying. The results of this study show that perceived usefulness and ease of use influence flow experience. Ease of use also influences attitude, but perceived usefulness did not impact attitude. In addition, flow experience did not impact attitude. However, both flow experience and attitude influence IBT. Furthermore, IBT significantly mediated flow experience and attitude into urge to impulsive buying.

This study only captured consumers in one country, so its results cannot be generalized to other nations. Random sampling may limit result generalization. In this study, three mobile shopping applications were investigated and the results would have been different if more mobile shopping applications were investigated.

The study gives a better understanding of how the perceived usefulness and ease of use of mobile shopping apps affect a consumer's tendency and urge to impulsive buying on halal fashion products by using flow experience as mediating variable.

The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

Based on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by training the delicately designed neural network structure with bearing qualitative comparison data between different health statuses. The remaining useful life is then predicted using the bearing health evaluation model and the degradation tolerance threshold. To validate the feasibility, efficiency and superiority of the proposed method, comparison experiments are designed and carried out on a widely used bearing dataset.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.