Purpose-The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approach-The expert diagnosis system utilizes statistical and deep ...Purpose-The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approach-The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle.Based on data mechanism models,it predicts the lifespan of key components,evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.Findings-The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system,which helps operators to monitor the operation of vehicle online,predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.Originality/value-This system improves the efficiency of rail vehicle operation,scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.展开更多
Safety is essential when building a strong transportation system.As a key development direction in the global railway system,the intelligent railway has safety at its core,making safety a top priority while pursuing t...Safety is essential when building a strong transportation system.As a key development direction in the global railway system,the intelligent railway has safety at its core,making safety a top priority while pursuing the goals of efficiency,convenience,economy,and environmental friendliness.This paper describes the state of the art and proposes a system architecture for intelligent railway systems.It also focuses on the development of railway safety technology at home and abroad,and proposes the active safety method and technology system based on advanced theoretical methods such as the in-depth integration of cyber–physical systems(CPS),data-driven models,and intelligent computing.Finally,several typical applications are demonstrated to verify the advancement and feasibility of active safety technology in intelligent railway systems.展开更多
In the context of the increasing scale of bridges and the increasing service life of bridges,it is very important to carry out efficient,accurate and intelligent bridge operation and maintenance.In recent years,advanc...In the context of the increasing scale of bridges and the increasing service life of bridges,it is very important to carry out efficient,accurate and intelligent bridge operation and maintenance.In recent years,advanced equipment,technology and intelligent algorithms have developed rapidly.It is necessary to apply advanced equipment and algorithms to bridge operation and maintenance business to facilitate the digitalization and intelligence of bridge operation and maintenance.To grasp the research progress on the bridge intelligent operation and maintenance,this paper summarizes the research progress in recent years from the aspects of intelligent detection equipment and technology,intelligent monitoring equipment and technology,intelligent data analysis,intelligent evaluation and early warning,and intelligent repair and maintenance.According to the review,more and more smart devices have been used to replace human beings to detect dangerous and hidden bridge components.At the same time,image processing,radar and other technologies have been used to analyze component damage more objectively and quantitatively.To solve the shortcomings of traditional sensors such as short life and low robustness,more non-contact measurement methods have been proposed.Scholars have proposed various intelligent algorithms to process the massive amount of bridge health monitoring data to improve the quality of the data.To achieve the rapid perception of bridge status and timely early warning of structural abnormalities,different from traditional theoretical calculations,scholars have tried to use data-driven methods to intelligently evaluate and early warning of bridge structural status.In terms of intelligent repair and maintenance,more intelligent algorithms have been used to optimize structural maintenance strategies and determine the best maintenance time by integrating multisource heterogeneous data.All these provide strong support for the automation,digitization and intelligence of bridge operation and maintenance.展开更多
本文针对烟草业务系统日常运维中,对生产异常,特别是物料损耗异常发现难、追溯排查难的问题,设计并实现了一种基于双向长短期记忆模型(bi-directional long short-term memory,Bi-LSTM)和自注意力机制的损耗异常分析模型。以烟丝损耗异...本文针对烟草业务系统日常运维中,对生产异常,特别是物料损耗异常发现难、追溯排查难的问题,设计并实现了一种基于双向长短期记忆模型(bi-directional long short-term memory,Bi-LSTM)和自注意力机制的损耗异常分析模型。以烟丝损耗异常检查为例介绍该模型,以卷包系统的时序剔除数据为输入,判断原材料损耗是否存在异常。该分析模型可用于烟草业务系统日常监控运维,自动识别各生产阶段物料损耗异常,并通过注意力权重从空间和时间维度解释分析结果,为人工排查提供先验,辅助生产管理,提升运维系统的智能化。展开更多
基金supported by Hunan Province Enterprise Technology Innovation and Entrepreneurship Team Support Program Project,Hunan Province Science and Technology Innovation Leading Talent Project[2023RC1088]Hunan Province Science and Technology Talent Support Project[2023TJ-Z10].
文摘Purpose-The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.Design/methodology/approach-The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle.Based on data mechanism models,it predicts the lifespan of key components,evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.Findings-The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system,which helps operators to monitor the operation of vehicle online,predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.Originality/value-This system improves the efficiency of rail vehicle operation,scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.
基金supported by the 2021 Chinese Academy of Engineering(CAE)International Top-level Forum on Engineering Science and Technology,“Safety and Governance of the High-Speed Railway”。
文摘Safety is essential when building a strong transportation system.As a key development direction in the global railway system,the intelligent railway has safety at its core,making safety a top priority while pursuing the goals of efficiency,convenience,economy,and environmental friendliness.This paper describes the state of the art and proposes a system architecture for intelligent railway systems.It also focuses on the development of railway safety technology at home and abroad,and proposes the active safety method and technology system based on advanced theoretical methods such as the in-depth integration of cyber–physical systems(CPS),data-driven models,and intelligent computing.Finally,several typical applications are demonstrated to verify the advancement and feasibility of active safety technology in intelligent railway systems.
基金funded by the National Key R&D Program of China(Grant No.:2021YFB1600300)National Natural Science Foundation of China(Grant No.:52008027,51878058)Fundamental Research Funds for the Central Universities,CHD(No.:300102213212).
文摘In the context of the increasing scale of bridges and the increasing service life of bridges,it is very important to carry out efficient,accurate and intelligent bridge operation and maintenance.In recent years,advanced equipment,technology and intelligent algorithms have developed rapidly.It is necessary to apply advanced equipment and algorithms to bridge operation and maintenance business to facilitate the digitalization and intelligence of bridge operation and maintenance.To grasp the research progress on the bridge intelligent operation and maintenance,this paper summarizes the research progress in recent years from the aspects of intelligent detection equipment and technology,intelligent monitoring equipment and technology,intelligent data analysis,intelligent evaluation and early warning,and intelligent repair and maintenance.According to the review,more and more smart devices have been used to replace human beings to detect dangerous and hidden bridge components.At the same time,image processing,radar and other technologies have been used to analyze component damage more objectively and quantitatively.To solve the shortcomings of traditional sensors such as short life and low robustness,more non-contact measurement methods have been proposed.Scholars have proposed various intelligent algorithms to process the massive amount of bridge health monitoring data to improve the quality of the data.To achieve the rapid perception of bridge status and timely early warning of structural abnormalities,different from traditional theoretical calculations,scholars have tried to use data-driven methods to intelligently evaluate and early warning of bridge structural status.In terms of intelligent repair and maintenance,more intelligent algorithms have been used to optimize structural maintenance strategies and determine the best maintenance time by integrating multisource heterogeneous data.All these provide strong support for the automation,digitization and intelligence of bridge operation and maintenance.
文摘本文针对烟草业务系统日常运维中,对生产异常,特别是物料损耗异常发现难、追溯排查难的问题,设计并实现了一种基于双向长短期记忆模型(bi-directional long short-term memory,Bi-LSTM)和自注意力机制的损耗异常分析模型。以烟丝损耗异常检查为例介绍该模型,以卷包系统的时序剔除数据为输入,判断原材料损耗是否存在异常。该分析模型可用于烟草业务系统日常监控运维,自动识别各生产阶段物料损耗异常,并通过注意力权重从空间和时间维度解释分析结果,为人工排查提供先验,辅助生产管理,提升运维系统的智能化。
