RT-Notification: A Novel Real-Time Notification Protocol for Wireless Control in Fog Computing

Fog computing is an emerging paradigm that has broad applications including storage, measurement and control. In this paper, we propose a novel real-time notification protocol called RT-Notification for wireless control in fog computing. RT-Notification provides low-latency TDMA communication between an access point in Fog and a large number of portable monitoring devices equipped with sensor and actuator. RT-Notification differentiates two types of controls: urgent downlink actuator-oriented control and normal uplink access & scheduling control. Different from existing protocols, RT-Notification has two salient features:(i) support real-time notification of control frames, while not interrupting ongoing other transmissions, and(ii) support on-demand channel allocation for normal uplink access & scheduling control. RT-Notification can be implemented based on the commercial off-the-shelf 802.11 hardware. Our extensive simulations verify that RT-Notification is very effective in supporting the above two features.

A Study on FMS's Real-time Fault Diagnosis Expert System

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Imprecise Computation Based Real-time Fault Tolerant Implementation for Model Predictive Control

Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is proposed for MPC, according to the solving process of quadratic programming (QP) problem. In this algorithm, system stability is guaranteed even when computation resource is not enough to finish optimization completely. By this kind of graceful degradation, the behavior of real-time control systems is still predictable and determinate. The algorithm is demonstrated by experiments on servomotor, and the simulation results show its effectiveness.

A Novel Real-Time Fault Diagnostic System for Steam Turbine Generator Set by Using Strata Hierarchical Artificial Neural Network

The real-time fault diagnosis system is very great important for steam turbine generator set due to a serious fault results in a reduced amount of electricity supply in power plant. A novel real-time fault diagnosis system is proposed by using strata hierarchical fuzzy CMAC neural network. A framework of the fault diagnosis system is described. Hierarchical fault diagnostic structure is discussed in detail. The model of a novel fault diagnosis system by using fuzzy CMAC are built and analyzed. A case of the diagnosis is simulated. The results show that the real-time fault diagnostic system is of high accuracy, quick convergence, and high noise rejection. It is also found that this model is feasible in real-time fault diagnosis.

STUDY OF REAL-TIME EXPERT SYSTEM TOOL FOR INDUSTRIAL FAULT MONITORING AND DIAGNOSIS

From the requirements of industrial production,an integrated fault monitoring,diagnosis and repairing system is suggested in this paper. This new scheme of fault monitoring and diagnosis system is realized by a master-slave real-time expert system,and a real-time expert system tool for this system is also developed accordingly. As an example of application of this tool ,a realtime expert system for fault monitoring and diagnosis on DC mine hoist is developed. Experiments show that this tool possesses better supporting environment, strong knowledge acquisition ability, and convenience for use. The system developed by this tool not only meets the real-time requirement of DC hoist,but also can give correct diagnosis results.

Energy-Efficient Deterministic Fault-Tolerant Scheduling for Embedded Real-Time Systems

By combining fault-tolerance with power management, this paper developed a new method for aperiodic task set for the problem of task scheduling and voltage allocation in embedded real-time systems. The scbedulability of the system was analyzed through checkpointing and the energy saving was considered via dynamic voltage and frequency scaling. Simulation results showed that the proposed algorithm had better performance compared with the existing voltage allocation techniques. The proposed technique saves 51.5% energy over FT-Only and 19.9% over FT ＋ EC on average. Therefore, the proposed method was more appropriate for aperiodic tasks in embedded real-time systems.

Safety-assured,real-time neural active fault management for resilient microgrids integration

Federated-learning-based active fault management(AFM)is devised to achieve real-time safety assurance for microgrids and the main grid during faults.AFM was originally formulated as a distributed optimization problem.Here,federated learning is used to train each microgrid’s network with training data achieved from distributed optimization.The main contribution of this work is to replace the optimization-based AFM control algorithm with a learning-based AFM control algorithm.The replacement transfers computation from online to offline.With this replacement,the control algorithm can meet real-time requirements for a system with dozens of microgrids.By contrast,distributed-optimization-based fault management can output reference values fast enough for a system with several microgrids.More microgrids,however,lead to more computation time with optimization-based method.Distributed-optimization-based fault management would fail real-time requirements for a system with dozens of microgrids.Controller hardware-in-the-loop real-time simulations demonstrate that learning-based AFM can output reference values within 10 ms irrespective of the number of microgrids.

Design on Vibration Monitoring and Fault Diagnosis System of Large Water Pump Motor

Large water pump motor,whose operation decides the reliability of the whole production line,plays a very important role.Therefore,its online condition monitoring can help companies better know its operation,process fault analysis and protection.The essay mainly studies and designs large water pump motor′s real time vibration monitoring and fault diagnosis system.The essay completes the systems project design,the establishment of the system and performance test.Eddy-currentsensor,XM-120 vibration module,XM-320 axial translation module,XM-362 temperature module,XM-360 process amount module and XM-500 gateway module are used to measure the axial vibration and displacement of main motors.Laboratory tests prove that the system can meet the requirements of motor vibration monitoring.

Fault Tolerance in the Joint EDF-RMS Algorithm: A Comparative Simulation Study

Failure is a systemic error that affects overall system performance and may eventually crash across the entire configuration.In Real-Time Systems(RTS),deadline is the key to successful completion of the program.If tasks effectively meet the deadline,it means the system is working in pristine order.However,missing the deadline means a systemic fault due to which the system can crash(hard RTS)or degrade inclusive performance(soft RTS).To fine-tune the RTS,tolerance is the critical issue and must be handled with extreme care.This article explains the context of fault tolerance with improvised Joint EDF-RMS algorithm in RTS.The backup method has been derived to prevent the system from being recursively migrating the same task.If any task migrates three times,this migrated task will get shifted to the backup queue.This backup queue assigns the task to a backup processor and is destined for final execution.For performance evaluation purposes,a relative graph between fault and failure rates,failure and total processor utilization along with other averages have been evaluated.Furthermore,these archived results are compared with fault-tolerant Earliest Deadline First(EDF)and Rate Monotonic Scheduling(RMS)algorithms independently in relatively similar conditions.These comparisons show better performance against overloading conditions.

Development of Magnetic Field Sensor and Motor Fault Monitoring Application

For the purpose of motor fault real-time monitoring, this research developed a nano-silicon ni- tride film based magnetic field (MF) sensor, and applied this sensor in MF detection of two common faults. Through experiment, it turned out that arc discharge and slot discharge occur in motor fault produce MF with certain laws. This result proved the feasibility of the sensor and sensing method in MF analysis, and revealed possibility of a new method in fault detection.

Real-time condition monitoring and fault diagnosis in switched reluctance motors with Kohonen neural network

The faults in switched reluctance motors(SRMs) were detected and diagnosed in real time with the Kohonen neural network. When a fault happens, both financial losses and undesired situations may occur. For these reasons, it is important to detect the incipient faults of SRMs and to diagnose which faults have occurred. In this study, a test rig was realized to determine the healthy and faulty conditions of SRMs. A data set for the Kohonen neural network was created with implemented measurements. A graphical user interface(GUI) was created in Matlab to test the performance of the Kohonen artificial neural network in real time. The data of the SRM was transferred to this software with a data acquisition card. The condition of the motor was monitored by marking the data measured in real time on the weight position graph of the Kohonen neural network. This test rig is capable of real-time monitoring of the condition of SRMs, which are used with intermittent or continuous operation, and is capable of detecting and diagnosing the faults that may occur in the motor. The Kohonen neural network used for detection and diagnosis of faults of the SRM in real time with Matlab GUI was embedded in an STM32 processor. A prototype with the STM32 processor was developed to detect and diagnose the faults of SRMs independent of computers.

Primary Research on Real-Time Fault Diagnosis Platform for Fuel Tank System of an Aircraft

Sub-tanks in fuel tank systems of aircrafts transfer fuel to engines in certain order. These sub-tanks and attached tank-accessories affect each other, and make fault diagnosis in such systems rather difficult. Without real measured data, this paper analyzes fault modes and fault effects of the fuel tank system, including its tankaccessories, of a given aircraft. Fault model of the system is built theoretically, and fault diagnosis criteria are deduced. Such criteria are then quantified to train a back propagation neural network(BPNN) as fault diagnosis model. To realize fault diagnosis of the real fuel tank system, a real-time fault diagnosis platform based on Lab View and Vx Works to perform this diagnosis method is discussed. This platform is a technical groundwork for fault diagnosis in real fuel tank systems.

网格系统的故障检测与告警

及时发现网格系统的故障,是提高网格系统运行可靠性的关键.为此,在实现网格资源监控与网格任务监控的基础上,设计并实现了网格故障检测与告警系统.描述了故障检测与告警系统的整体框架架构及实现机制.本系统采用主动式故障检测,主动轮流咨询分布在网格节点上的代理Agent和分布在服务器上的任务监控代理Agent,基于自适应条件分别判断网格资源和网格任务是否运行正常,当出现故障或错误时及时发出告警,并显示告警信息.

分布式广播报警通知控制软件的设计与实现

首先介绍了公共报警通知系统的背景知识和重要意义。以发达国家和我国建设的一些公共报警通知系统为例,对公共报警通知系统的发展现状进行概述,并分析了现有技术方案的一些不足之处。在介绍了分址调频广播技术的基础上,对分布式广播报警通知控制软件的设计与实现进行了详细说明。该软件通过互斥量的方法解决了硬件资源和广播资源的访问冲突问题;通过超时重发指令的方式解决了网络通信中可能存在的指令数据包丢失问题;通过设置超时时间,自动识别发生网络故障或者设备故障的发射塔;在无需人工干预的情况下,自动重新控制恢复正常功能的发射塔。该软件实现了多个客户端对多个广播报警发射基站的高效、正确、和分布式控制,极大的发挥了基于分布式分址调频广播技术的公共报警通知系统的优点。该软件系统与配套的分布式分址调频广播硬件系统一起,形成了一种覆盖范围广、环境适应性强、分区报警控制灵活的公共报警通知系统,技术路线成熟,推广前景广阔。

网络侵权中权利人错误通知侵权责任的归责原则

《民法典》规定,权利人错误通知给网络用户或网络服务提供者造成损害的,由权利人承担责任。目前理论和实践针对该条款的适用存有争议,即认定权利人错误通知侵权责任时适用何种归责原则,是以无过错责任原则为准还是以过错推定原则为准,亦或采取过错责任原则。厘清上述主张的利弊,找出最佳适用方案极为必要。通过对适用过错责任原则的合理性、必要性以及可行性进行分析,该原则在平衡被害人权益保护和加害人行为自由二者利益上效用显著,有益于推动互联网的健康发展。适用过错责任原则,证明权利人主观过错的责任在网络用户一方,其可以采用主客观标准相结合的方式来证明权利人的主观过错,在减轻自身举证责任的同时也避免浪费司法资源。

中标通知书的法律性质分析——兼论中标通知书发出后的责任形态

中标通知书发出后,招标人改变中标结果或者中标人放弃中标项目,承担的是缔约过失责任还是违约责任,对于这一问题各界众说纷纭。通过运用文义解释及目的解释的法律解释方法分析,将中标通知书的法律性质理解为"能产生合同成立效力的承诺",将上述责任理解为"违约责任",更为符合《招标投标法》的立法初衷和立法精神。

基于SDN架构的网络故障检测与修复系统

在基于机器学习和基于贝叶斯网络的故障检测方法中,检测结果只是基于概率或者历史信息的推断,难以应用于网络故障检测与自动修复系统。针对该问题,提出基于产生式规则的故障检测方法,对已知故障自动下发安全策略进行阻断,对未知故障以告警形式通知网络管理员,同时设计一种自适应轮询算法,进一步减少系统开销并保证故障响应实时性。实验结果表明,该方法能够减少轮询开销,有效抑制报文异常。

《电子商务法》下“恶意错误通知”认定标准研究

为规制权利人异化“通知”规则功能,平衡权利人、电商平台及平台内经营者利益,《电子商务法》第42条第3款首创性引入“恶意错误通知”概念并对其发出者要求承担“加倍赔偿责任”,然上述规定对“恶意”与“错误通知”概念语焉不详。为避免该条款在司法实践下被误用,澄清其含义及法理实有必要。文章在对“恶意”与其他过错形式比较并结合司法实践考量后认为,第3款之“恶意”是对具惩罚性质“加倍赔偿责任”的主观考量,应采取“明知+不正当竞争动机”标准;而“错误通知”则是对事实的陈述,其构成不应包含主观要件。

基于副版本零调整策略的实时任务主副版本容错调度

为了降低硬实时周期性任务主副版本容错调度的副版本调整开销,提出了一种BEDFNENF容错调度算法.采用反向最早截止期优先(BEDF)策略为副版本预分配处理器时间,运行时则采用零调整最早通知时间优先(NENF)策略调度主版本.结果表明,BEDF-NENF算法能够按照最后机会策略调度副版本.当主版本错误概率不大于0.05时,BEDF-NENF算法的副版本调整平均比较次数和副版本调整时间比率均为0,与BEDF-RM算法、BEDF-EDF算法、BEDF-ENF算法的主版本完成率之差约为1%.BEDF-NENF算法不仅能够取得与同类调度算法接近的主版本完成率,而且能够通过省略副版本重新调整操作来降低调度的复杂性,节省调度时间.

Designing similarity measurement with distance measure and application on laterally directional mode flight test

Similarity measure construction has been proposed as fault detection of flight test method in order to obtain the primary control surface stuck and the combination stuck of primary control.Similarity measures were obtained through analyzing the certainty and uncertainty of fuzzy membership functions,which were designed based on well-known Hamming distance.It was applied to the fault detection of primary control surface stuck of uninhabited aerial vehicle(UAV).At post-failure control surface,if the UAV is controllable and trimmable using other control surfaces,the UAV is able to fly or return to the safety region through reconfiguration of flight control system.To detect the fault,similarity measure computations were carried out.This result could be applicable with the real-time parameter estimation method.By monitoring the value of coefficients due to the control surface deviation,it becomes aware that the control surface fault occurs or not.The control surface stuck position and value were separated by comparing the trim value with the reference value.This is the advantage of increasing in reliability without adding sensors or with additional low cost.