Fault Management Research Articles

DC Voltage Control for Fault Management in HVDC System

This paper focuses on the transmission system options for connection of offshore wind farms and investigates the advantages and disadvantages of proposed concepts in order to draw a conclusion regarding their suitability for connection in the electricity system. Then, the most appropriate solution is implemented in Matlab/Simulink to show its benefits. For this purpose, 5 wind farms are connected to an offshore station and their power output is transferred onshore via a point – to – point DC link. Additionally a novel proposal of DC voltage control is included in the model to simulate the behaviour of the system when faults occur in the electricity grid.

Discrepant Perspectives on Conflict Situations Among Urban Parent-Adolescent Dyads.

Parents influence urban youths' violence-related behaviors. To provide effective guidance, parents should understand how youth perceive conflict, yet little empirical research has been conducted regarding parent and youth perceptions of conflict. The aims of this article are to (a) report on the nature of discrepancies in attribution of fault, (b) present qualitative data about the varying rationales for fault attribution, and (c) use quantitative data to identify correlates of discrepancy including report of attitudes toward violence, parental communication, and parents' messages about retaliatory violence. Interviews were conducted with 101 parent/adolescent dyads. The study population consisted of African American female caretakers (n = 92; that is, mothers, grandmothers, aunts) and fathers (n = 9) and their early adolescents (mean age = 13.6). A total of 53 dyads were discrepant in identifying instigators in one or both videos. When discrepancy was present, the parent was more likely to identify the actor who reacted to the situation as at fault. In the logistic regression models, parental attitudes about retaliatory violence were a significant correlate of discrepancy, such that as parent attitudes supporting retaliatory violence increased, the odds of discrepancy decreased. The results suggest that parents and adolescents do not always view conflict situations similarly, which may inhibit effective parent-child communication, parental advice, and discipline. Individuals developing and implementing family-based violence prevention interventions need to be cognizant of the complexity of fault attribution and design strategies to promote conversations around attribution of fault and effective conflict management.

Toward high assurance software systems with adaptive fault management

In this paper, we develop an adaptive approach to estimate the optimal preventive rejuvenation schedule, which maximizes the steady-state system availability. We formulate the upper and lower bounds of the predictive system availability using the one-look ahead predictive survival function from system failure time data and derive the pessimistic and optimistic rejuvenation policies. Then, we derive adaptive rejuvenation policies from the original data together with a right-censored observation. In the simulation experiments, we show the usefulness of the adaptive nonparametric predictive inference approach proposed in this paper.

Autonomous control strategy for fault management in distribution networks

In this paper, the application of autonomous control on automatic switches in electric power distribution networks is proposed. The key feature for the proposed control strategy is based on a decentralized control aiming to automatically isolate the faulty section while reducing the overall dependency on the number of fault indicators and communication hops involved in the fault management process. In order to evaluate the performance of the proposed control strategy, its behavior is compared with the centralized and distributed agent-based decentralized switching control methods. Different aspects are considered in the evaluation such as the number of activated communication hops and the corresponding communication latency. A practical network configuration is utilized in order to verify the proposed decentralized control strategy for the fault management. The results corroborate the efficacy of the proposed autonomous decentralized algorithm for fault management in distribution networks.

A cost-effective fault management system for distribution systems with distributed generators

Abstract Fault Management System (FMS) is one of the main functions in Distribution Automation System (DAS); however, the conventional FMS cannot be used in distribution systems with Distributed Generators (DGs) due to the lack of directional function. The directional fault detection device is expensive due to the expensive directional module used. In a wide-ranging distribution system, the investment cost will be very high if the fault detecting devices are expensive. Therefore, the design and implementation of a cost-effective FMS for distribution system with DGs is necessary. A Multi-Level Fault-Current Indicator (MLFCI) having a plurality of reed switches used to detect different current levels is proposed in this paper. The hardware prototype is designed and implemented. An algorithm used to locate fault based on the different fault current levels is derived. A MLFCI-based FMS for distribution systems with DGs is then realized. Experimental results demonstrate the feasibility of the proposed MLFCI. Simulation results are then used to demonstrate the validity of the proposed MLFCI-based FMS for distribution systems with DGs.

Static probabilistic worst case execution time estimation for architectures with faulty instruction caches

Semiconductor technology evolution suggests that permanent failure rates will increase dramatically with scaling, in particular for SRAM cells. While well known approaches such as error correcting codes exist to recover from failures and provide fault-free chips, they will not be affordable anymore in the future due to their growing cost. Consequently, other approaches like fine-grained disabling and reconfiguration of hardware elements (e.g. individual functional units or cache blocks) will become economically necessary. This fine-grained disabling will degrade performance compared to a fault-free execution. To the best of our knowledge, all static worst-case execution time (WCET) estimation methods assume fault-free processors. Their result is not safe anymore when fine-grained disabling of hardware components is used. In this paper we provide the first method that statically calculates a probabilistic WCET bound in the presence of permanent faults in instruction caches. The proposed method derives a probabilistic WCET bound for a program, cache configuration, and probability of cell failure. As our method relies on static analysis to bound the longest path, its probabilistic nature only stems from the probability that faults actually occur. Our method is computationally tractable because it does not require an exhaustive enumeration of all the possible combinations of faulty cache blocks. Experimental results show that it provides WCET estimates very close to, but never below, the method that derives probabilistic WCETs by enumerating all possible locations of faulty cache blocks. The proposed method not only allows to quantify the impact of permanent faults on WCET estimates, but, most importantly, can be used in architectural exploration frameworks to select the most appropriate fault management mechanisms and design parameters for current and future chip designs.

Association Analysis and Processing Strategy for Network Events Based on the Combination of RBR and CBR

In order to ensure the high performance, the high reliability, the high availability and the high service quality of network, fault management has become an urgent problem to be solved. The application of Rule-Based Reasoning (RBR) and Case-Based Reasoning (CBR) is recognized as an economically viable network fault process technology. To meet the demands of network fault management, this paper presents an association analysis and processing strategy for network events based on the combination of RBR and CBR. The network events are firstly passed through pretreatment module, the useful ones are saved for the following processing. Then, the first processing strategy which is more appropriate is select by RBR/CBR selector. Besides, a new CBR processing strategy is proposed by this paper. By the use of the algorithm based on the preliminary screening and the calculating of variance, the processing efficiency of CBR improved. At last, if the alarm event is not been solved, the system will alarm the related people and the solution can be used to rich the rule base and the case base. Based on these steps, experimental results are given to verify the proposed strategy.

Research on Mining and Classification of Public Opinion Mining Based on Semantic

In this paper, we used CSP algorithm as the core, constructed public opinion mining system including the mining module, the mining policy management module, the user management module, and the Fault Management module. The system's major job is finish public opinion mining, text classification, concept Clustering, the similarity analysis, automatic Digest, and optimize the result of the web system, mail system and other major media networks. After establish the theme, the system will optimizing the initial seed and get the resource, then get tabloid through text analysis technology, After that the documents will be classified to the concept of clustering, a concept of space and a neural network algorithms will be settled, so that it can provide users with the concept of space-based interface for the research and the circumstances surrounding the development process. The system provide the appropriate information platform for the departments to regulate public opinion timely and reasonable.

Special Issue on Three-Dimensional Structural Modeling

Three-dimensional (3D) structural models are generalizations of geological maps and cross-sections used by geologists for the last 200 years. They describe the geometry and layout of rock units in 3D space by honoring available observations, measurements and geological concepts. They are used on a daily basis in industry and academia to improve one’s understanding of an area, to quantify geological processes and to address natural resource management problems (oil and gas, mining, geothermal energy, ground water). This area of research raises interesting questions concerning the ways to build these models and to appropriately describe, analyze and reduce the associated uncertainty. For these ends, new conceptual models relating to geological processes and geometric parameters are needed. This issue gathers contributions regarding all of these aspects. In preparing this special issue, we have received a total of 25 paper proposals and 13 full papers, of which 5 are published in the present issue and 2 are still in revision. We would like to thank all the authors for their contributions and the reviewers for both their help and remarks, which have been essential to the editorial process. 3D structural modeling emerged in the 1970s by generating computerized depth maps with contouring techniques. These methods are very effective and are still in use today for the processing and analysis of topographic surfaces and depth maps. However, they raise problems when it comes to fault management, or when dealing with complex surfaces having several Z-values for the same geographic coordinate (e.g., recumbent folds, salt tops). This limitation motivated the development of techniques

Fault Manager of Diagnostic System in the Gasoline Engine ECU

A structure of fault manager is established. Under the premise of combining relevant standards, the five main modules of the fault manager effectively integrated and handled fault information. This fault manager is implemented in a home-ECU for its upcoming production.

The effects of automation-induced complacency on fault diagnosis and management performance in process control

Operators of automated systems can develop complacency, impairing their ability to respond in a timely and appropriate fashion when automation fails. This study sought to examine the impact of an instructional manipulation of attentiveness, in terms of engagement and accountability, on fault diagnosis and fault management. Participants trained on the operation of a simulated process control task, with instructions varied to induce higher or lower attentiveness to the task. After several routine faults within the system, a fault occurred along with a failure of a previously available diagnostic and management aid, and shortly after a second failure occurred. The first failure was associated with significant impairment of diagnosis and management, but comparatively few differences between attentiveness groups. Results are discussed in terms of their implications for a model of human-automation interaction.

Collective Learning in Multi-Agent Systems Based on Cultural Algorithms


 
 
 This paper aims to present a learning model for coordination schemes in Multi-Agent Systems (MAS) based on Cultural Algorithms (CA). In this model, the individuals (one of the CA components) are the different conversations that may occur in any multi-agent systems, and the coordination scheme learned is at the level of the way to perform the communication protocols into the conversation. A conversation can has sub-conversations, and the sub-conversations and/or conversations are identified with a particular type of conversation associated with a certain interaction patterns. The interaction patterns use the coordination mechanisms existing in the literature. In order to simulate the proposed learning model, we develop a computational tool called CLEMAS, which has been used to apply the model to a case of study in industrial automation, related to a Faults Management System based on Agents.
 
 

On Signaling-Free Failure Dependent Restoration in All-Optical Mesh Networks

Failure dependent protection (FDP) is known to achieve optimal capacity efficiency among all types of protection, at the expense of longer recovery time and more complicated signaling overhead. This particularly hinders the usage of FDP in all-optical mesh networks. As a remedy, this paper investigates a new restoration framework that enables all-optical fault management and device configuration via state-of-the-art failure localization techniques, such as the FDP restoration process. It can be implemented without relying on any control plane signaling. With the proposed restoration framework, a novel spare capacity allocation problem is defined and is further analyzed on circulant topologies for any single link failure, aiming to gain a solid understanding of the problem. By allowing reuse of monitoring resources for restoration capacity, we are particularly interested in the monitoring resource hidden property, where less or even no monitoring resources are consumed as more working traffic is in place. To deal with general topologies, we introduce a novel heuristic approach to the proposed spare capacity allocation problem, which comprises a generic FDP survivable routing scheme followed by a novel monitoring resource allocation method. Extensive simulation is conducted to examine the proposed scheme and verify the proposed restoration framework.

Evaluation and Analysis of Novel Mobile Agent Model in Network Fault Management

Network fault management aims at detecting and avoiding network problems, and thus at increasing a network's availability, keeping downtimes to a minimum, and improving network performance. It is a most important in network management and also in the research area of mobile agent technology. Models of mobile agent technology and the traditional SNMP (Simple Network Management Protocol) - Based C/S (Client/Server) are facing a lot of problems, such as availability, flexibility and scalability of network, traffic bottleneck, etc., with the increasing of network size, complexity and heterogeneity. The novel mobile agent model can improve these deficiencies and work better to achieve distributed network management. The network fault management save network bandwidth reduces latency, increase the reliability, and improve management efficiency. This paper provides the evaluates and analyses the performance of a network fault management in terms of average network traffic, cost spent the processing of nodes of the novel mobile agent model for unlimited nodes and also data access algorithms with the models of mobile agent technology with limited nodes and the traditional SNMP-Based client server system which is proved with the mathematical formulae and experimental results.

Algorithm Based on Heuristic Strategy to Infer Lossy Links in Wireless Sensor Networks

With the maturing of the actual application of wireless sensor networks, network fault management is eagerly demanded. Severe link packet loss affects the performance of wireless sensor networks, so it must be found and repaired. Subject to the constraints on limited resources, lossy link is inferred using end to end measurement and network tomography. The algorithm based on heuristic strategy is proposed. This maps the problem of lossy links inferences to minimal set-cover problems. The performance of inference algorithms is evaluated by simulation, and the simulation results indicate feasibility and efficiency of the method.

Decentralized earth fault selectivity using transient front slopes for unearthed MV networks

In this paper, a transient-based selectivity function is introduced for identifying the faulty section due to earth faults. The proposed selectivity procedure enhances the earth fault management in unearthed/compensated MV networks using decentralized control. The faulty section is discriminated by evaluating relative polarities, at each section terminals of front slopes, created by the earth fault occurrence. The fault surge slopes are extracted by differentiating the residual current waveforms. A threshold value is evaluated to localize the polarity measuring. The outline of integrating the proposed selectivity function is discussed with the decentralized control.

An integrated environment monitoring system for underground coal mines--Wireless Sensor Network subsystem with multi-parameter monitoring.

Environment monitoring is important for the safety of underground coal mine production, and it is also an important application of Wireless Sensor Networks (WSNs). We put forward an integrated environment monitoring system for underground coal mine, which uses the existing Cable Monitoring System (CMS) as the main body and the WSN with multi-parameter monitoring as the supplementary technique. As CMS techniques are mature, this paper mainly focuses on the WSN and the interconnection between the WSN and the CMS. In order to implement the WSN for underground coal mines, two work modes are designed: periodic inspection and interrupt service; the relevant supporting technologies, such as routing mechanism, collision avoidance, data aggregation, interconnection with the CMS, etc., are proposed and analyzed. As WSN nodes are limited in energy supply, calculation and processing power, an integrated network management scheme is designed in four aspects, i.e., topology management, location management, energy management and fault management. Experiments were carried out both in a laboratory and in a real underground coal mine. The test results indicate that the proposed integrated environment monitoring system for underground coal mines is feasible and all designs performed well as expected.

Analysis of propagation dynamics in complex dynamical network based on disturbance propagation model

The paper regards the complex dynamical network (CDN) as a static network with temporal characteristics so as to consider its dynamic behavior. The influence factor and dynamics laws in CDN are explored by using the methods of simulation and statistical physics. It is found that both the dynamic behavior of the nodes and the number of initial disturbed nodes can accelerate the failure propagation and enlarge the influence scope. There is a phase transformation point of the repair ratio with the increase of repair time τ for the homogeneous network (the value of τ for all the nodes is the same). Beyond the threshold, the entire network will collapse; otherwise, the network can be back to normal after a period of time. There is an inflection point of the repair rate with the simulation step and the recovery rate in heterogeneous network is much slower than that in homogeneous network. The results can provide technical support for the fault management and network optimization in CDN which will promote the development of corresponding theory in CDN.

Automata for Web Services Fault Monitoring and Diagnosis

Like any software, web service fault management is also required to go through different phases of fault management lifecycle. Model based diagnosis has been a well established practice for its several positive aspects including cognitively being better understood by development and testing teams. Automata is a simple and formally well defined model being used for monitoring and diagnosis of system faults. For the reason, here we have reviewed works on automata for web service fault management and also propose a model of stochastic automata for the purpose.

Integrated design of fault localization and survivable mapping in IP over transparent WDM networks

Lightpaths play multiple critical roles in cross-layer fault management of IP over transparent optical networks. While the roles of lightpaths have been discussed specifically in fault localization as well as fault recovery phases, these existing works only take a sporadic, piecemeal view of these roles by studying each of them individually as a separate lightpath routing problem. In this paper, we instead take an integrated, systematic view by considering these multiple roles jointly as one single lightpath routing problem. In particular, we propose a new design model to fulfill the lightpath layout requirements in both identifying fiber link failures for fault localization and ensuring IP topology connectivity for fault recovery. With a much smaller formulation size, our new model significantly outperforms the existing counterpart in computational efficiency, scalability, and solution quality.