The model and method of SCADA diagnostics as an object with partially defined parameters

Modern SCADA are widely spread all over the world to control technological processes in different industries such as power engineering, military, transport, etc. These systems have strict requirements to ensure their fault tolerance and reliability. Therefore, a very important problem is to perform real time self-diagnostics for mission critical SCADA. We propose a diagnostic model based on expert system methodology to solve this issue

A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP

Mechanical and electrical products have complex structure and intelligent control system, their reliability plays an important role in the normal operation of security facilities. However, most manufacturers usually pay more attention to the product designing and manufacturing quality, with little interest in the intelligent fault diagnosis. The objective of this study is to develop the products quality intelligent analysis and management system based on Rough Set (RS) and Analytic Hierarchy Process (AHP). Firstly, this paper reviews the principle of hardware, software design, monitoring platform and quality analysis system to reduce the number of information transfer with computer technology. Secondly, the fault types and feature extractions of different faults of elevators are presented and simplified by using RS theory. Then, the objective weight of level index model can be obtained by AHP method, and the comprehensive analysis weight of each index is obtained by using the value of subjective and objective weight coefficients with the golden ratio. Finally, a comprehensive decision weight of the major index for quality control analysis system of many vertical elevators is presented. The results show that the data-driven condition monitoring and quality analysis system is a kind of important means to prevent a disaster of complex mechanical and electrical products

The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

Learning to automatically detect features for mobile robots using second-order Hidden Markov Models

In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features. Hidden Markov Models have been used for a long time in pattern recognition, especially in speech recognition. Their main advantages over other methods (such as neural networks) are their ability to model noisy temporal signals of variable length. We show in this paper that this approach is well suited for interpretation of temporal sequences of mobile-robot sensor data. We present two distinct experiments and results: the first one in an indoor environment where a mobile robot learns to detect features like open doors or T-intersections, the second one in an outdoor environment where a different mobile robot has to identify situations like climbing a hill or crossing a rock.Comment: 200

FAST : a fault detection and identification software tool

The aim of this work is to improve the reliability and safety of complex critical control systems by contributing to the systematic application of fault diagnosis. In order to ease the utilization of fault detection and isolation (FDI) tools in the industry, a systematic approach is required to allow the process engineers to analyze a system from this perspective. In this way, it should be possible to analyze this system to find if it provides the required fault diagnosis and redundancy according to the process criticality. In addition, it should be possible to evaluate what-if scenarios by slightly modifying the process (f.i. adding sensors or changing their placement) and evaluating the impact in terms of the fault diagnosis and redundancy possibilities. Hence, this work proposes an approach to analyze a process from the FDI perspective and for this purpose provides the tool FAST which covers from the analysis and design phase until the final FDI supervisor implementation in a real process. To synthesize the process information, a very simple format has been defined based on XML. This format provides the needed information to systematically perform the Structural Analysis of that process. Any process can be analyzed, the only restriction is that the models of the process components need to be available in the FAST tool. The processes are described in FAST in terms of process variables, components and relations and the tool performs the structural analysis of the process obtaining: (i) the structural matrix, (ii) the perfect matching, (iii) the analytical redundancy relations (if any) and (iv) the fault signature matrix. To aid in the analysis process, FAST can operate stand alone in simulation mode allowing the process engineer to evaluate the faults, its detectability and implement changes in the process components and topology to improve the diagnosis and redundancy capabilities. On the other hand, FAST can operate on-line connected to the process plant through an OPC interface. The OPC interface enables the possibility to connect to almost any process which features a SCADA system for supervisory control. When running in on-line mode, the process is monitored by a software agent known as the Supervisor Agent. FAST has also the capability of implementing distributed FDI using its multi-agent architecture. The tool is able to partition complex industrial processes into subsystems, identify which process variables need to be shared by each subsystem and instantiate a Supervision Agent for each of the partitioned subsystems. The Supervision Agents once instantiated will start diagnosing their local components and handle the requests to provide the variable values which FAST has identified as shared with other agents to support the distributed FDI process.Per tal de facilitar la utilització d'eines per la detecció i identificació de fallades (FDI) en la indústria, es requereix un enfocament sistemàtic per permetre als enginyers de processos analitzar un sistema des d'aquesta perspectiva. D'aquesta forma, hauria de ser possible analitzar aquest sistema per determinar si proporciona el diagnosi de fallades i la redundància d'acord amb la seva criticitat. A més, hauria de ser possible avaluar escenaris de casos modificant lleugerament el procés (per exemple afegint sensors o canviant la seva localització) i avaluant l'impacte en quant a les possibilitats de diagnosi de fallades i redundància. Per tant, aquest projecte proposa un enfocament per analitzar un procés des de la perspectiva FDI i per tal d'implementar-ho proporciona l'eina FAST la qual cobreix des de la fase d'anàlisi i disseny fins a la implementació final d'un supervisor FDI en un procés real. Per sintetitzar la informació del procés s'ha definit un format simple basat en XML. Aquest format proporciona la informació necessària per realitzar de forma sistemàtica l'Anàlisi Estructural del procés. Qualsevol procés pot ser analitzat, només hi ha la restricció de que els models dels components han d'estar disponibles en l'eina FAST. Els processos es descriuen en termes de variables de procés, components i relacions i l'eina realitza l'anàlisi estructural obtenint: (i) la matriu estructural, (ii) el Perfect Matching, (iii) les relacions de redundància analítica, si n'hi ha, i (iv) la matriu signatura de fallades. Per ajudar durant el procés d'anàlisi, FAST pot operar aïlladament en mode de simulació permetent a l'enginyer de procés avaluar fallades, la seva detectabilitat i implementar canvis en els components del procés i la topologia per tal de millorar les capacitats de diagnosi i redundància. Per altra banda, FAST pot operar en línia connectat al procés de la planta per mitjà d'una interfície OPC. La interfície OPC permet la possibilitat de connectar gairebé a qualsevol procés que inclogui un sistema SCADA per la seva supervisió. Quan funciona en mode en línia, el procés està monitoritzat per un agent software anomenat l'Agent Supervisor. Addicionalment, FAST té la capacitat d'implementar FDI de forma distribuïda utilitzant la seva arquitectura multi-agent. L'eina permet dividir sistemes industrials complexes en subsistemes, identificar quines variables de procés han de ser compartides per cada subsistema i generar una instància d'Agent Supervisor per cadascun dels subsistemes identificats. Els Agents Supervisor un cop activats, començaran diagnosticant els components locals i despatxant les peticions de valors per les variables que FAST ha identificat com compartides amb altres agents, per tal d'implementar el procés FDI de forma distribuïda.Postprint (published version

Intelligent multimedia communication for enhanced medical e-collaboration in back pain treatment

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2004 SAGE PublicationsRemote, multimedia-based, collaboration in back pain treatment is an option which only recently has come to the attention of clinicians and IT providers. The take-up of such applications will inevitably depend on their ability to produce an acceptable level of service over congested and unreliable public networks. However, although the problem of multimedia application-level performance is closely linked to both the user perspective of the experience as well as to the service provided by the underlying network, it is rarely studied from an integrated viewpoint. To alleviate this problem, we propose an intelligent mechanism that integrates user-related requirements with the more technical characterization of quality of service, obtaining a priority order of low-level quality of service parameters, which would ensure that user-centred quality of perception is maintained at an optimum level. We show how our framework is capable of suggesting appropriately tailored transmission protocols, by incorporating user requirements in the remote delivery of e-health solutions

Considerations for a design and operations knowledge support system for Space Station Freedom

Engineering and operations of modern engineered systems depend critically upon detailed design and operations knowledge that is accurate and authoritative. A design and operations knowledge support system (DOKSS) is a modern computer-based information system providing knowledge about the creation, evolution, and growth of an engineered system. The purpose of a DOKSS is to provide convenient and effective access to this multifaceted information. The complexity of Space Station Freedom's (SSF's) systems, elements, interfaces, and organizations makes convenient access to design knowledge especially important, when compared to simpler systems. The life cycle length, being 30 or more years, adds a new dimension to space operations, maintenance, and evolution. Provided here is a review and discussion of design knowledge support systems to be delivered and operated as a critical part of the engineered system. A concept of a DOKSS for Space Station Freedom (SSF) is presented. This is followed by a detailed discussion of a DOKSS for the Lyndon B. Johnson Space Center and Work Package-2 portions of SSF

An integrated diagnostic architecture for autonomous robots

Abstract unavailable please refer to PD

Space applications of Automation, Robotics and Machine Intelligence Systems (ARAMIS). Volume 3: ARAMIS overview

An overview of automation, robotics, and machine intelligence systems (ARAMIS) is provided. Man machine interfaces, classification, and capabilities are considered

Fault Diagnosis for Substation with Redundant Protection Configuration Based on Time-Sequence Fuzzy Petri-Net

Due to timing inconsistency, dual protection configuration and uncertainty diagnosis result characteristics of 750kV substation, fault diagnosis method of substation with redundant protection configuration which based on time sequence fuzzy Petri nets is proposed. In this method, redundant knowledge about fault component is represented by using two sets of protected information. On that basis, component redundant diagnosis-model based on time sequence fuzzy Petri net is constructed, which can be decomposed into main and redundant subnet-model. In this model, initial-information credibility is determined using information-entropy, timing constraint is checked, and initial-information credibility is corrected using the relationship between acted protection and breaker. Compared with fuzzy Petri net diagnosis method take no account of timing constraint, this method can not only identify the malfunction information, but also obtain a certain result