Research on Virtual Maintenance Training for Airborne Electronic Equipments

Author(s):  
Shuang Zhang ◽  
Minghua Chen ◽  
Guoyi Wen ◽  
Jing Wan
Keyword(s):  
Measurement ◽  
2021 ◽  
pp. 109344
Author(s):  
Ge Zhexue ◽  
Qi Zhuqi ◽  
Luo Xu ◽  
Yang Yongmin ◽  
Zhang Yi

Author(s):  
Josquin Foulliaron ◽  
Laurent Bouillaut ◽  
Patrice Aknin ◽  
Anne Barros

The maintenance optimization of complex systems is a key question. One important objective is to be able to anticipate future maintenance actions required to optimize the logistic and future investments. That is why, over the past few years, the predictive maintenance approaches have been an expanding area of research. They rely on the concept of prognosis. Many papers have shown how dynamic Bayesian networks can be relevant to represent multicomponent complex systems and carry out reliability studies. The diagnosis and maintenance group from French institute of science and technology for transport, development and networks (IFSTTAR) developed a model (VirMaLab: Virtual Maintenance Laboratory) based on dynamic Bayesian networks in order to model a multicomponent system with its degradation dynamic and its diagnosis and maintenance processes. Its main purpose is to model a maintenance policy to be able to optimize the maintenance parameters due to the use of dynamic Bayesian networks. A discrete state-space system is considered, periodically observable through a diagnosis process. Such systems are common in railway or road infrastructure fields. This article presents a prognosis algorithm whose purpose is to compute the remaining useful life of the system and update this estimation each time a new diagnosis is available. Then, a representation of this algorithm is given as a dynamic Bayesian network in order to be next integrated into the Virtual Maintenance Laboratory model to include the set of predictive maintenance policies. Inference computation questions on the considered dynamic Bayesian networks will be discussed. Finally, an application on simulated data will be presented.


2014 ◽  
Vol 49 (3/4) ◽  
pp. 332
Author(s):  
Gangfeng Deng ◽  
Xianxiang Huang ◽  
Qinhe Gao ◽  
Quanmin Zhu ◽  
Zhili Zhang ◽  
...  

2018 ◽  
Vol 38 (3) ◽  
pp. 291-302 ◽  
Author(s):  
Jie Geng ◽  
Xu Peng ◽  
Ying Li ◽  
Chuan Lv ◽  
Zili Wang ◽  
...  

Purpose Current virtual simulation platforms provide various tools to generate non-immersive simulation processes purposefully in different domains. The generated simulation processes are adopted for analysis, presentation, demonstration and verification. In the virtual maintenance domain, this intuitive and visual method has benefitted product maintainability design and improvement. Generating an ideal and reasonable non-immersive virtual maintenance simulation is always time-consuming because of the complicated human operations and logical relationships involved. This study aims to propose a semiautomatic approach to increase efficiency in non-immersive virtual maintenance simulation implementation. Design/methodology/approach The methodology analyzes the general catalogs of common maintenance tasks and explores the corresponding secondary development approaches of simulation tools that can achieve motion simulation in virtual environments, by focusing on the diversity, complexity and uncertainty in non-immersive virtual simulation process generation. Afterward, a single virtual human motion can be generated by controlling the parameters and indices of the simulation tools. Subsequently, all of the generated single motions are connected logically to simulate the entire maintenance process. Findings Instead of selecting various tools, such as that in a traditional method, the proposed methodology analyzes and integrates the necessary basic parameters considering the characteristics of virtual maintenance simulation for a target maintenance activity. Originality/value The user can control the predefined parameters to generate the simulation combining several other simple operations in virtual environments. Consequently, the methodology decreases simulation tool selection and logic consideration and increases efficiency to a certain extent in non-immersive virtual maintenance simulation generation.


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