Research and Development of a Network-Based Intelligent Maintenance Information System

A maintenance information system is an important part of equipmentmanagement. An intelligent maintenance information system (IMIS) is a synthesis of networktechnology, information technology and intelligent technology. The IMIS is used to finish flexiblemaintenance decision-making and fast maintenance planning, which helps enterprises to effectivelyreduce maintenance cost and increase working efficiency. Because the IMIS integrates advancedtechnologies, its performance is better than a traditional one. The difference between an IMIS and atraditional maintenance information system, and the functions, structure, important realizations,and application of an IMIS are discussed in this paper.

Research and design of an expert diagnosis system for rail vehicle driven by data mechanism models

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.

Research on Maintenance Information Management System for Distributed Manufacture System

An architecture and design of a maintenance information management system for distributed manufacture system is presented in this paper, and its related key technologies are studied and implemented also. A frame of the maintenance information management system oriented human-machine monitoring is designed, and using object-oriented method, a general maintenance information management system based on SQL server engineering database and adopted client/server/database three-layer mode can be established. Then, discussions on control technologies of maintenance information management system and remote distributed diagnostics and maintenance system are emphasized. The system is not only able to identify and diagnose faults of distributed manufacture system quickly, improve system stability, but also has intelligent maintenance functions.

Automation in road distress detection,diagnosis and treatment

Road transportation plays a crucial role in society and daily life,as the functioning and durability of roads can significantly impact a nation's economic development.In the whole life cycle of the road,the emergence of disease is unavoidable,so it is necessary to adopt relevant technical means to deal with the disease.This study comprehensively reviews the advancements in computer vision,artificial intelligence,and mobile robotics in the road domain and examines their progress and applications in road detection,diagnosis,and treatment,especially asphalt roads.Specifically,it analyzes the research progress in detecting and diagnosing surface and internal road distress and related techniques and algorithms are compared.In addition,also introduces various road gover-nance technologies,including automated repairs,intelligent construction,and path planning for crack sealing.Despite their proven effectiveness in detecting road distress,analyzing diagnoses,and planning maintenance,these technologies still confront challenges in data collection,parameter optimization,model portability,system accuracy,robustness,and real-time performance.Consequently,the integration of multidisciplinary technologies is imperative to enable the development of an integrated approach that includes road detection,diagnosis,and treatment.This paper addresses the challenges of precise defect detection,condition assessment,and unmanned construction.At the same time,the efficiency of labor liberation and road maintenance is achieved,and the automation level of the road engineering industry is improved.

Research on digital twin technology and its application in intelligent operation and maintenance of highspeed railway infrastructure

Purpose–This paper analyzes the application of digital twin technology in the field of intelligent operation and maintenance of high-speed railway infrastructure from the perspective of top-level design.Design/methodology/approach–This paper provides a comprehensive overview of the definition,connotations,characteristics and key technologies of digital twin technology.It also conducts a thorough analysis of the current state of digital twin applications,with a particular focus on the overall requirements for intelligent operation and maintenance of high-speed railway infrastructure.Using the Jinan Yellow River Bridge on the Beijing–Shanghai high-speed railway as a case study,the paper details the construction process of the twin system from the perspectives of system architecture,theoretical definition,model construction and platform design.Findings–Digital twin technology can play an important role in the whole life cycle management,fault prediction and condition monitoring in the field of high-speed rail operation and maintenance.Digital twin technology is of great significance to improve the intelligent level of high-speed railway operation and management.Originality/value–This paper systematically summarizes the main components of digital twin railway.The general framework of the digital twin bridge is given,and its application in the field of intelligent operation and maintenance is prospected.

基于BIM+技术的城市地下综合管廊智能运维管理研究

城市地下综合管廊是保障城市正常运转的“生命线”,关系着广大民众的日常生活和社会的稳定,如何使其平稳、高效运行已成为社会各界广为重视的问题。综合管廊运维管理涉及的主客体众多,以人工监管方式为主的传统运维方式效率低、准确率不足、安全性难以保障,因此,本文基于BIM+技术视角,为城市地下综合管廊的智能运维管理提供一种新思路,以期实现综合管廊管理的标准化、规范化,提高管理效率、降低管理成本。本文包括引言与结语共分为五个部分。首先,介绍本文的研究背景、意义,以及研究思路。其次,阐述综合管廊传统运维管理模式的现状及存在问题。然后,提出综合管廊运维管理的基本目标,并基于BIM+技术,尝试构建城市地下综合管廊的智能运维管理系统。最后,对文章进行总结并提出展望。

Development of rail technology for high speed railway in China

Purpose–The purpose of this paper is to summarize the status and characteristics of rail technology of high-speed railway in China,and point out the development direction of rail technology of high-speed railway.Design/methodology/approach–This study reviews the evolution of high-speed rail standards in China,comparing their chemical composition,mechanical attributes and geometric specifications with EN standards.It delves into the status of rail production technology,shifts in key performance indicators and the quality characteristics of rails.The analysis further examines the interplay between wheels and rails,the implementation of grinding technology and the techniques for inspecting rail service conditions.It encapsulates the salient features of rail operation and maintenance within the high-speed railway ecosystem.The paper concludes with an insightful prognosis of high-speed railway technology development in China.Findings–The rail standards of high-speed railway in China are scientific and advanced,highly operational and in line with international standards.The quality and performance of rail in China have reached the world’s advanced level.The 60N profile guarantees the operation quality of wheel–rail interaction effectively.The rail grinding technology system scientifically guarantees the long-term good service performance of the rail.The rail service state detection technology is scientific and efficient.The rail technology will take“more intelligent”and“higher speed”as the development direction to meet the future needs of high-speed railway in China.Originality/value–The development direction of rail technology for high-speed railway in China is defined,which will promote the continuous innovation and breakthrough of rail technology.

Outlier Mining Based Abnormal Machine Detection in Intelligent Maintenance

Assessing machine's performance through comparing the same or similar machines is important to implement intelligent maintenance for swarm machine.In this paper,an outlier mining based abnormal machine detection algorithm is proposed for this purpose.Firstly,the outlier mining based on clustering is introduced and the definition of cluster-based global outlier factor(CBGOF) is presented.Then the modified swarm intelligence clustering(MSIC) algorithm is suggested and the outlier mining algorithm based on MSIC is proposed.The algorithm can not only cluster machines according to their performance but also detect possible abnormal machines.Finally,a comparison of mobile soccer robots' performance proves the algorithm is feasible and effective.

Multi-dimensional and Multi-threshold Airframe Damage Region Division Method Based on Correlation Optimization

In order to obtain the image of airframe damage region and provide the input data for aircraft intelligent maintenance,a multi-dimensional and multi-threshold airframe damage region division method based on correlation optimization is proposed.On the basis of airframe damage feature analysis,the multi-dimensional feature entropy is defined to realize the full fusion of multiple feature information of the image,and the division method is extended to multi-threshold to refine the damage division and reduce the impact of the damage adjacent region’s morphological changes on the division.Through the correlation parameter optimization algorithm,the problem of low efficiency of multi-dimensional multi-threshold division method is solved.Finally,the proposed method is compared and verified by instances of airframe damage image.The results show that compared with the traditional threshold division method,the damage region divided by the proposed method is complete and accurate,and the boundary is clear and coherent,which can effectively reduce the interference of many factors such as uneven luminance,chromaticity deviation,dirt attachment,image compression,and so on.The correlation optimization algorithm has high efficiency and stable convergence,and can meet the requirements of aircraft intelligent maintenance.

Visual Collaborative Maintenance Method for Urban Rail Vehicle Bogie Based on Operation State Prediction

The bogie is a crucial component of urban rail vehicles,and its performance plays a decisive role in the safe operation of vehicles.Aiming at the intelligent operation and maintenance requirements of rail transit equipment,in this paper,it takes several key parts of the urban rail vehicle bogie system as research objects,such as motor bearings,frames,fasteners,etc.,and proposes a three-dimensional(3D)visual collaborative maintenance method.Firstly,a multi-sensor urban rail vehicle bogie running simulation experiment analysis platform was constructed,thereby establishing a database of running state and performance characteristics of the bogie in the whole life cycle.Then,the health status of key components of bogie was predicted by the state interval prediction model.Finally,the three-dimensional visual collaborative maintenance model proposed in this paper was integrated to realize the early warning of the bogie operation faults,3D precise guidance of automatic location and maintenance operation information,and collaborative sharing of visual information among multiple users.

A review on artificial intelligence in high-speed rail

High-speed rail(HSR)has brought a number of social and economic benefits,such as shorter trip times for journeys of between one and five hours;safety,security,comfort and on-time commuting for passengers;energy saving and environmental protection;job creation;and encouraging sustainable use of renewable energy and land.The recent development in HSR has seen the pervasive applications of artificial intelligence(AI).This paper first briefly reviews the related disciplines in HSR where AI may play an important role,such as civil engineering,mechanical engineering,electrical engineering and signalling and control.Then,an overview of current AI techniques is presented in the context of smart planning,intelligent control and intelligent maintenance of HSR systems.Finally,a framework of future HSR systems where AI is expected to play a key role is provided.

Airframe Damage Region Division Method Based on Structure Tensor Dynamic Operator

In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region,the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper.The structure tensor feature space is established to represent the local features of damage images.It makes different damage images have the same feature distribution,and transform varied damage region division into consistent process of feature space division.On this basis,the structure tensor dynamic operator generation method is designed.It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules,in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division.And then the airframe damage region division is realized.The experimental results on different airframe structure damage images show that compared with traditional threshold division method,the proposed method can improve the division quality.The interference of damage adjacent region is eliminated.The information loss caused by over-segmentation is avoided.And it is efficient in operation,and consistent in process.It also has the applicability to different types of structural damage.