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Multi-agent systems (MAS) for software construction is an approach that has been applied to different and complex domains that require distributed and intelligent environments. A crucial concern related to MAS is how software agents based on the Belief-Desire-Intention (BDI) model should be tested. An agent is an autonomous and pro-active entity that can exchange information with other agents distributed...
In this paper, we describe a simulation based health monitoring system test-bed for an electrical power distribution system developed at the Integrated Vehicle Health Management Centre, Cranfield University. The purpose of the test-bed is to provide a technology neutral basis for implementing and evaluation diagnostic systems and software architecture in support the condition based maintenance process...
Rapid and accurate fault detection and diagnosis (FDD) is gaining importance for complex equipments because of the need to increase reliability and to decrease possible loss. In this paper, an intelligent fault diagnosis method is presented by using case-based reasoning (CBR) methodology to infer and classify various failures. Firstly, the case representation and the case base are established according...
Power transformer is one of the key important and most expensive equipments in electrical power system. Building systems to monitor their real time behaviours and diagnose their faults autonomously with comprehensive knowledge-base are the key issue. This paper provides a new framework for power transformer monitoring and fault diagnosis based on ontology reasoner. The Gaia methodology is applied...
Self-diagnosis is a fundamental capability of self-adaptive systems. In order to recover from faults, systems need to know which part is responsible for the incorrect behavior. In previous work we showed how to apply a design-time diagnosis technique at run time to identify faults at the architectural level of a system. Our contributions address three major shortcomings of our previous work: 1) we...
The performance and reliability of overlay services rely on the underlying overlay network's ability to effectively diagnose and recover from faults such as link failures and overlay node outages. However, overlay networks bring to fault diagnosis new challenges such as large-scale deployment, inaccessible underlay network information, dynamic symptom-fault causality relationship, and multi-layer...
The remote performance monitoring system used in modern agricultural machinery was proposed based on internet for the features of modern agricultural machinery such as complex, widely distributed, Poor working conditions, on-site performance monitoring being difficult and so on. The overall system structure and working principle was introduced emphasizing on the remote monitoring service center structure,...
In petrochemical process, the kernel task of avoiding abnormal situation is fault diagnosis of the process. As signed directed graph (SDG) can reflect the path of fault propagation clearly, it is a hot spot in fault diagnosis of petrochemical process currently. However, basic SDG is poor in resolution and insensitive to early fault, so it is needed to introduce other algorithms to solve the shortcomings...
Research in the area of Autonomic Networks is on the rise. Autonomicity - realized through control loops, is an enabler for advanced self-manageability of network nodes and devices. Therefore, the specification and design of autonomic behaviors is required for each of the management functions defined by the well established FCAPS network management framework (Fault-, Configuration-, Accounting-, Performance-...
Timed failure propagation graph (TFPG) is a directed graph model that represents temporal progression of failure effects in physical systems. In this paper, a distributed diagnosis approach for complex systems is introduced based on the TFPG model settings. In this approach, the system is partitioned into a set of local subsystems each represented by a subgraph of the global system TFPG model. Information...
Service-Oriented Computing reveals features which are not commonly found in conventional computing paradigms; loose coupling, dynamism, blackbox, evolvability, and heterogeneity. These features make diagnosing and healing faults found in deployed services and service-related elements more challenging than managing conventional systems. Hence, service-oriented systems management often results in problems...
With the study and analysis on intelligent fault diagnosis for inverting circuit, an improved diagnosis method combined BP neuron network and D-S evidence theory was proposed. Each measuring point was extracted by BP neural network to obtain the local diagnosis, which is adopted to design the belief function of D-S evidence theory. Multiple monitoring points' information is fused to receive the comprehensive...
As the health status of aeroplane structural components has direct influence on the flight safety, it is important to monitor the health status of structural components timely. In this paper, acoustic emission technology is used to monitor the health status of the aeroplane structural component. The acoustic emission health information from the aeroplane structural component is analyzed and disposed...
This paper introduces a new method to design expert system reasoning with CPLD for fault diagnosis. Firstly, the reasoning process of normal expert system is analyzed; Secondly, the knowledge and experiences of experts are transformed to binary or multi-valued reasoning using fault tree, and the processes are realized with simple gate circuits; lastly, the new scheme is used in fault diagnosis for...
Information integration is a key for further growth of efficiency in management decisions for the railway domain. In the context of the EU project InteGRail (funded in the 6th Framework Programme) an integration approach leveraged by ontologies known from the semantic Web and logic-based reasoning mechanisms has been successfully demonstrated. To this effect existing heterogeneous monitoring data...
Service-oriented architecture (SOA) is a cost effective approach to building enterprise applications. SOA reveals non-conventional characteristics of heterogeneity, grid-like distribution, evolvability, and limited visibility. Hence, services management presents non-conventional challenges. Especially, fault diagnosis at runtime is challenging due to the SOA features. Model-based reasoning (MBR) is...
Overlay networks have emerged as a powerful and flexible platform for developing new disruptive network applications. The attractive characteristics of overlay networks such as planetary-scale distributions, user-level flexibility (e.g., overlay routing) and manageability bring to overlay fault diagnosis new challenges, which include inaccessible underlying network information, incomplete and inaccurate...
The dependability of overlay services rely on the overlay network's capabilities to effectively diagnose and recover faults (e.g., link failures, overlay node outages). However, overlay applications bring to overlay fault diagnosis new challenges, which include large-scale deployment, inaccessible underlying network information, dynamic symptom-fault causality relationship, and multi-layer complexity...
Network fault diagnosis is an important aspect of network management. Often, a single component failure will result in a cascade of secondary faults that overwhelm simple reasoning approaches. If the network monitoring information is being transmitted through the network to the network management system (NMS), then fault diagnosis is complicated by the fact that the transmission of relevant monitoring...
Causality diagram theory is a kind of uncertainty reasoning theory based on the belief network. It expresses the knowledge and causality relationship by diagrammatic form and direct causality intensity. Furthermore, it resolves the shortages of the belief network, and realizes a hybrid model which can process discrete and continuous variations. The theory of causality diagram model and the steps of...
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