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1 – 5 of 5Zhihao Wang, Wenliang Chen, Min Wang, Qinghe Xu and Can Huang
The purpose of this study is to improve the position and posture accuracy of posture alignment mechanism. The automatic drilling and riveting machine is an important equipment for…
Abstract
Purpose
The purpose of this study is to improve the position and posture accuracy of posture alignment mechanism. The automatic drilling and riveting machine is an important equipment for aircraft assembly. The alignment accuracy of position and posture of the bracket type posture alignment mechanism has a great influence on the operation effect of the machine. Therefore, it is necessary to carry out the kinematic calibration.
Design/methodology/approach
Based on analysis of elastic deformation of the bracket and geometric errors of the posture alignment mechanism, an improved method of kinematic calibration was proposed. The position and posture errors of bracket caused by geometric errors were separated from those caused by gravity. The method of reduction of dimensions was applied to deal with the error coefficient matrix in error identification, and it did not change the coefficient of the error terms. The target position and its posture were corrected to improve the error compensation accuracy. Furthermore, numerical simulation and experimental verification were carried out.
Findings
The simulation and experimental results show that considering the influence of the elastic deformation of the bracket on the calibration effect, the error identification accuracy and compensation accuracy can be improved. The maximum value of position error is reduced from 5.33 mm to 1.60 × 10−1 mm and the maximum value of posture error is reduced from 1.07 × 10−3 rad to 6.02 × 10−4 rad, which is superior to the accuracy without considering the gravity factor.
Originality/value
This paper presents a calibration method considering the effects of geometric errors and gravity. By separating position and posture errors caused by different factors and correcting the target position and its posture, the results of the calibration method are greatly improved. The proposed method might be applied to any parallel mechanism based on the positioner.
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Ying Guo, Qinghe Han, Jinxin Wang and Xu Yu
Localization is one of the critical issues in Ocean Internet of Things (OITs). The existing research results of localization in OITs are very limited. It poses many challenges due…
Abstract
Purpose
Localization is one of the critical issues in Ocean Internet of Things (OITs). The existing research results of localization in OITs are very limited. It poses many challenges due to the difficulty of deploy beacon accurately, the difficulty of transmission distance estimation in harsh ocean environment and the underwater node mobility. This paper aims to provide a novel localization algorithm to solve these problems.
Design/methodology/approach
This paper takes the ship with accurate position as a beacon, analyzes the relationship between underwater energy attenuation and node distance and takes them into OITs localization algorithm design. Then, it studies the movement regulation of underwater nodes in the action of ocean current, and designs an Energy-aware Localization Algorithm (ELA) for OITs.
Findings
Proposing an ELA. ELA takes the ship with accurate position information as a beacon to solve the problem of beacon deployment. ELA does not need to calculate the information transmission distance which solves the problem of distance estimation. It takes underwater node movement regulation into computation to solve the problem of node mobility.
Originality value
This paper provides an ELA based on the relationship between propagation energy attenuation and node distance for OITs. It solves the problem of localization in dynamic underwater networks.
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Lei Wang, Chuang Xiong and Qinghe Shi
Considering that uncertain factors widely exist in engineering practice, an adaptive collocation method (ACM) is developed for the structural fuzzy uncertainty analysis.
Abstract
Purpose
Considering that uncertain factors widely exist in engineering practice, an adaptive collocation method (ACM) is developed for the structural fuzzy uncertainty analysis.
Design/methodology/approach
ACM arranges points in the axis of the membership adaptively. Through the adaptive collocation procedure, ACM can arrange more points in the axis of the membership where the membership function changes sharply and fewer points in the axis of the membership where the membership function changes slowly. At each point arranged in the axis of the membership, the level-cut strategy is used to obtain the cut-level interval of the uncertain variables; besides, the vertex method and the Chebyshev interval uncertainty analysis method are used to conduct the cut-level interval uncertainty analysis.
Findings
The proposed ACM has a high accuracy without too much additional computational efforts.
Originality/value
A novel ACM is developed for the structural fuzzy uncertainty analysis.
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Keywords
Weiwen Mu, Wenbai Chen, Huaidong Zhou, Naijun Liu, Haobin Shi and Jingchen Li
This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and…
Abstract
Purpose
This paper aim to solve the problem of low assembly success rate for 3c assembly lines designed based on classical control algorithms due to inevitable random disturbances and other factors,by incorporating intelligent algorithms into the assembly line, the assembly process can be extended to uncertain assembly scenarios.
Design/methodology/approach
This work proposes a reinforcement learning framework based on digital twins. First, the authors used Unity3D to build a simulation environment that matches the real scene and achieved data synchronization between the real environment and the simulation environment through the robot operating system. Then, the authors trained the reinforcement learning model in the simulation environment. Finally, by creating a digital twin environment, the authors transferred the skill learned from the simulation to the real environment and achieved stable algorithm deployment in real-world scenarios.
Findings
In this work, the authors have completed the transfer of skill-learning algorithms from virtual to real environments by establishing a digital twin environment. On the one hand, the experiment proves the progressiveness of the algorithm and the feasibility of the application of digital twins in reinforcement learning transfer. On the other hand, the experimental results also provide reference for the application of digital twins in 3C assembly scenarios.
Originality/value
In this work, the authors designed a new encoder structure in the simulation environment to encode image information, which improved the model’s perception of the environment. At the same time, the authors used the fixed strategy combined with the reinforcement learning strategy to learn skills, which improved the rate of convergence and stability of skills learning. Finally, the authors transferred the learned skills to the physical platform through digital twin technology and realized the safe operation of the flexible printed circuit assembly task.
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Qi Sun, Fang Sun, Cai Liang, Chao Yu and Yamin Zhang
Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail…
Abstract
Purpose
Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station.
Design/methodology/approach
This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train.
Findings
A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow.
Originality/value
This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.
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