A general Boolean semantic modelling approach for complex and intelligent industrial systems in the framework of DES

Discrete event system(DES)models promote system engineering,including system design,verification,and assessment.The advancement in manufacturing technology has endowed us to fabricate complex industrial systems.Consequently,the adoption of advanced modeling methodologies adept at handling complexity and scalability is imperative.Moreover,industrial systems are no longer quiescent,thus the intelligent operations of the systems should be dynamically specified in the model.In this paper,the composition of the subsystem behaviors is studied to generate the complexity and scalability of the global system model,and a Boolean semantic specifying algorithm is proposed for generating dynamic intelligent operations in the model.In traditional modeling approaches,the change or addition of specifications always necessitates the complete resubmission of the system model,a resource-consuming and error-prone process.Compared with traditional approaches,our approach has three remarkable advantages:(i)an established Boolean semantic can be fitful for all kinds of systems;(ii)there is no need to resubmit the system model whenever there is a change or addition of the operations;(iii)multiple specifying tasks can be easily achieved by continuously adding a new semantic.Thus,this general modeling approach has wide potential for future complex and intelligent industrial systems.

KZ1——A Prototype of Intelligent Operating System

This paper proposes an Intelligent Operating System (IOS) as the next generation operating system. IOS integrates operating system with artificial intelligence technology,and its key feature is an intelligent man-machine communication mechanism which makes the computer systems more friendly.The con- cepts,functions and architecture of IOS are introduced and an experimental IOS called KZ1 is des- cribed in detail.

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.

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.

Research progress on intelligent operation and maintenance of bridges

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.

Social Energy:Mining Energy From the Society

The inherent nature of energy,i.e.,physicality,sociality and informatization,implies the inevitable and intensive interaction between energy systems and social systems.From this perspective,we define "social energy" as a complex sociotechnical system of energy systems,social systems and the derived artificial virtual systems which characterize the intense intersystem and intra-system interactions.The recent advancement in intelligent technology,including artificial intelligence and machine learning technologies,sensing and communication in Internet of Things technologies,and massive high performance computing and extreme-scale data analytics technologies,enables the possibility of substantial advancement in socio-technical system optimization,scheduling,control and management.In this paper,we provide a discussion on the nature of energy,and then propose the concept and intention of social energy systems for electrical power.A general methodology of establishing and investigating social energy is proposed,which is based on the ACP approach,i.e., "artificial systems"(A), "computational experiments"(C) and "parallel execution"(P),and parallel system methodology.A case study on the University of Denver(DU) campus grid is provided and studied to demonstrate the social energy concept.In the concluding remarks,we discuss the technical pathway,in both social and nature sciences,to social energy,and our vision on its future.

Smart City: On Urban Operational Collaboration

This paper expounds the origin of urban operational coordination problem in historical setting, points out that operational coordination problem is essential to cities, induces the major challenges and opportunities for urban operating coordination at present, and takes IBM Intelligent Operation Center as example to illustrate the typical solutions with the detailed case study of the Intelligent Operation Center in Rio de Janerio.

Ontology-Based Semantic Multi-agent Framework for Micro-grids with Cyber Physical Concept

The distributed hierarchical control based on multi-agent system(MAS) is the main control method of micro-grids.By allowing more flexible interactions between computing components and their physical environments,cyber physical system(CPS) presents a new approach for the distributed hierarchical engineering system,with micro-grids included.The object of this paper is to integrate the CPS concept with MAS technology and propose a new control framework for micro-grids.With the analysis of the operating mode and control method of micro-grids,the cyber physical control concepts of ontologybased semantic agent are discussed.Then an MAS-based architecture of cyber physical micro-grid system and an intelligent electronic device(IED) function structure are proposed.Finally,in order to operate and test the cyber physical micro-grid concept,an integrated simulation model is presented.

Cooperative task assignment of multi-UAV system

With the rapid development of Unmanned Aerial Vehicle(UAV)technology,one of the emerging fields is to utilize multi-UAV as a team under autonomous control in a complex environment.Among the challenges in fully achieving autonomous control,Cooperative task assignment stands out as the key function.In this paper,we analyze the importance and difficulties of multiUAV cooperative task assignment in characterizing scenarios and obtaining high-quality solutions.Furthermore,we present three promising directions for future research:Cooperative task assignment in a dynamic complex environment,in an unmanned-manned aircraft system and in a UAV swarm.Our goal is to provide a brief review of multi-UAV cooperative task assignment for readers to further explore.

Reference direction based immune clone algorithm for many-objective optimization

In this paper, a new preference multi-objective optimization algorithm called immune clone algorithm based on reference direction method （RD-ICA） is proposed for solving many-objective optimization problems. First, an intelligent recombination operator, which performs well on the functions comprising many parameters, is introduced into an immune clone algorithm so as to explore the potentially excellent gene segments of all individuals in the antibody pop- ulation. Second, a reference direction method, a very strict ranking based on the desire of decision makers （DMs）, is used to guide selection and clone of the active population. Then a light beam search （LBS） is borrowed to pick out a small set of individuals filling the external population. The proposed method has been extensively compared with other recently proposed evolutionary multi-objective optimization （EMO） approaches over DTLZ problems with from 4 to 100 objectives. Experimental results indicate RD-ICA can achieve competitive results.

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.