基于MATLAB/Simulink库的复杂电网络的CAI

该文阐述在研究、探索、优化传统教学、实验教学、仿真教学、多媒体教学、网络教学、课程设计等多种教学形式的互补和完善教学设计的同时, 试图建立一种广泛适用于专业基础课程理论教学和实验教学的动态教学模式.课题组认为实验教学与仿真教学的有机结合对提高课程的教学质量、大学生的科研能力和创新意识将有很大的帮助.因此, 仿真的教学设计至关重要.本文皆在提出基于MATLAB/Simulink库的复杂电网的计算机辅助分析的方法.通过在教学过程和指导大学生科技竞赛活动中实践,起到明显的效果.

A method of searching fault propagation paths in mechatronic systems based on MPPS model

In view of the structure and action behavior of mechatronic systems,a method of searching fault propagation paths called maximum-probability path search(MPPS)is proposed,aiming to determine all possible failure propagation paths with their lengths if faults occur.First,the physical structure system,function behavior,and complex network theory are integrated to define a system structural-action network(SSAN).Second,based on the concept of SSAN,two properties of nodes and edges,i.e.,the topological property and reliability property,are combined to define the failure propagation property.Third,the proposed MPPS model provides all fault propagation paths and possible failure rates of nodes on these paths.Finally,numerical experiments have been implemented to show the accuracy and advancement compared with the methods of Function Space Iteration(FSI)and the algorithm of Ant Colony Optimization(ACO).

Optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing in cognitive radio network

In order to improve the throughput of cognitive radio(CR), optimization of sensing time and cooperative user allocation for OR-rule cooperative spectrum sensing was investigated in a CR network that includes multiple users and one fusion center. The frame structure of cooperative spectrum sensing was divided into multiple transmission time slots and one sensing time slot consisting of local energy detection and cooperative overhead. An optimization problem was formulated to maximize the throughput of CR network, subject to the constraints of both false alarm probability and detection probability. A joint optimization algorithm of sensing time and number of users was proposed to solve this optimization problem with low time complexity. An allocation algorithm of cooperative users was proposed to preferentially allocate the users to the channels with high utilization probability. The simulation results show that the significant improvement on the throughput can be achieved through the proposed joint optimization and allocation algorithms.

Dependency-based importance measures of components in mechatronic systems with complex network theory

To compensate for the limitations of previous studies,a complex network-based method is developed for determining importance measures,which combines the functional roles of the components of a mechatronic system and their topological positions.First,the dependencies among the components are well-represented and well-calculated.Second,a mechatronic system is modeled as a weighted and directional functional dependency network(FDN),in which the node weights are determined by the functional roles of components in the system and their topological positions in the complex network whereas the edge weights are represented by dependency strengths.Third,given that the PageRank algorithm cannot calculate the dependency strengths among components,an improved PageRank importance measure(IPIM)algorithm is proposed,which combines the node weights and edge weights of complex networks.IPIM also considers the importance of neighboring components.Finally,a case study is conducted to investigate the accuracy of the proposed method.Results show that the method can effectively determine the importance measures of components.

Discussion on the Application of Complex Power Network to Software Engineering

Along with the further development of science and technology, computer hardware and the Intemet are in a rapid development, and information technology has been widely used in all fields so that complex problems are simply solved. Because of the needs for the development, software starts to mutually integrate with complex power network, making the scale of software increase greatly. Such a growing trend of software promotes soft-ware development to go beyond a general understanding and control and thus a complex system is formed. It is necessary to strengthen the research of complex network theory, and this is a new way to help people study the complexity of software systems. In this paper, the development course of complex dynamic network is introduced simply and the use of complex power network in the software engineering is summarized. Hopefully, this paper can help the crossover study of complex power network and software engineering in the future.

Human Errors Monitoring in Electrical Transmission Networks

The electrical transmission networks are complex systems that are commonly run near their operational limits. Such systems can undergo major disturbances that have serious consequences. Individually, these disturbances can be attributed to specific causes, such as lightning strikes, ice storms, equipment failure, shorts resulting from untrimmed trees, excessive customer demand, or human errors. In the paper, the human errors from electrical transmission networks of Romanian Power Grid Company over period of 10 years are analyzed. It is hoped that obtained results will provide engineers a better understanding so they can cater to the needs of the human operators when to implement new interfaces for network monitoring tasks, not for the other technical objectives.

Complex network theory-based condition recognition of electromechanical system in process industry

In order to recognize the different operating conditions of a distributed and complex electromechanical system in the process industry,this work proposed a novel method of condition recognition by combining complex network theory with phase space reconstruction.First,a condition-space with complete information was reconstructed based on phase space reconstruction,and each condition in the space was transformed into a node of a complex network.Second,the limited penetrable visibility graph method was applied to establish an undirected and un-weighted complex network for the reconstructed condition-space.Finally,the statistical properties of this network were calculated to recognize the different operating conditions.A case study of a real chemical plant was conducted to illustrate the analysis and application processes of the proposed method.The results showed that the method could effectively recognize the different conditions of electromechanical systems.A complex electromechanical system can be studied from the systematic and cyber perspectives,and the relationship between the network structure property and the system condition can also be analyzed by utilizing the proposed method.

Preface

Complex networks are ubiquitous in our lives. Representative examples are the Internet, social networks, biological networks, E-commerce networks, electrical power grids, and larger-scale engineering systems. It is well known that the Internet has been a powerful engine for our societal evolution and technological innovation. Nowadays, network science and engineering faces fundamental challenges, such as understanding the complexity of various large-scale networks, developing new architectures and exploiting new substrates, and enabling new applications and new economics. To a better future, the complex networks in our lives will need to be better： more accessible, more reliable, more predictable, and more secure.