Browsing by Keyword "Fault diagnosis"
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Item Building and using an electrical network ontology for fault diagnosis(1998) Bernaras, A.; Laresgoiti, I.; Bartolomé, N.; Corera, J.; Tecnalia Research & Innovation; Centros PRE-FUSION TECNALIA - (FORMER)Nowadays reuse-based software development involves identifying both software and data components (objects, relations, etc.) reusable in different applications and/or domains. The KACTUS project set out to investigate the feasibility of knowledge reuse in complex technical systems and the role of ontologies to support it. This has been investigated by creating ontologies for particular domains and reusing them for different tasks or applications. One of the domains of interest in the project was the electrical network. In this paper we present our work on modelling a diagnosis application and on using the resulting ontology in the implementation of the system.Item Fault analysis with modular neural networks(1996-02) Rodríguez, C.; Rementería, S.; Martín, J. I.; Lafuente, A.; Muguerza, J.; Pérez, J.; SGAutomatic fault diagnosis in power systems presents real challenges to computing technologies. As an alternative approach to expert systems, several neural network solutions have been proposed recently. In this paper a modular, neural network-based solution to power systems alarm handling and fault diagnosis is described that overcomes the limitations of 'toy' alternatives constrained to small and fixed-topology electrical networks. In contrast to monolithical diagnosis systems, the neural network-based approach presented here fulfills the scalability and dynamic adaptability requirements of the application. Mapping the power grid onto a set of interconnected modules that model the functional behaviour of electrical equipment provides the flexibility and speed demanded by the problem. The way in which the neural system is conceived allows full scalability to real-size power systems.Item Intelligent maintenance for industrial processes, a case study on cold stamping(Springer Verlag, 2018) Boto, Fernando; Lizuain, Zigor; Cortadi, Alberto Jimenez; Perez Garcia, Hilde; Alfonso-Cendon, Javier; Sanchez Gonzalez, Lidia; Corchado, Emilio; Quintian, Hector; Tecnalia Research & Innovation; FACTORYThe correct diagnosis of tool breakage is fundamental to improve productivity, minimizing the number of unproductive hours and avoiding expensive repairs. The use of Data Mining techniques provides a significant added value in terms of improvements in the robustness, reliability and flexibility of the monitored systems. In this work, a general view of a diagnosis and prognosis of tool breakage in Industrial Processes is proposed. The important issues identified will be analyzed: filtering, process characterization and data based modeling. A case study has been implemented to carry out the prognosis of tool breakage in the cold stamping process. The results provided are qualitative trends and hypothesis to perform the prognosis. Although a validation in real operation is needed, these results are promising and demonstrate the goodness of using these type of techniques in real processes.Item A novel approach of multisensory fusion to collaborative fault diagnosis in maintenance(2021-10) Shao, Haidong; Lin, Jing; Zhang, Liangwei; Galar, Diego; Kumar, Uday; Tecnalia Research & InnovationCollaborative fault diagnosis can be facilitated by multisensory fusion technologies, as these can give more reliable results with a more complete data set. Although deep learning approaches have been developed to overcome the problem of relying on subjective experience in conventional fault diagnosis, there are two remaining obstacles to collaborative efficiency: integration of multisensory data and fusion of maintenance strategies. To overcome these obstacles, we propose a novel two-part approach: a stacked wavelet auto-encoder structure with a Morlet wavelet function for multisensory data fusion and a flexible weighted assignment of fusion strategies. Taking a planetary gearbox as an example, we use noisy vibration signals from multisensors to test the diagnosis performance of the proposed approach. The results demonstrate that it can provide more accurate and reliable fault diagnosis results than other approaches.Item Reliability evaluation of an HVAC ventilation system with FTA and RBD analysis(Institute of Electrical and Electronics Engineers Inc., 2020-10-12) Ciani, Lorenzo; Guidi, Giulia; Galar, Diego; Tecnalia Research & InnovationRail industry is rapidly developing, and rail becomes ever more viable in a wide range of regions. Therefore, the passenger experience and comfort has become a major concern for operators in the world. Heating, ventilation and air conditioning systems are used in railways to provide passengers thermal comfort and proper air motion. The ventilation system is one of the main elements of the system. Its components include both mechanical and electronic devices. All components are subjected to stress, and this tends to reduce their life cycle; the reliability of the ventilation system must be evaluated to plan and schedule appropriate maintenance activities. The paper evaluates reliability of the ventilation system using fault tree analysis and a reliability block diagram. Both techniques analyse data qualitatively; moreover, with specific algorithms they also provide quantitative results in term of reliability and probability of system failure. The paper compares the two reliability evaluation methods to verify their accuracy.Item Survey on fault operation on multilevel inverters(2010-07) Lezana, Pablo; Pou, Josep; Meynard, Thierry A.; Rodriguez, Jose; Ceballos, Salvador; Richardeau, Frédéric; POWER ELECTRONICS AND SYSTEM EQUIPMENTThis paper is related to faults that can appear in multilevel (ML) inverters, which have a high number of components. This is a subject of increasing importance in high-power inverters. First, methods to identify a fault are classified and briefly described for each topology. In addition, a number of strategies and hardware modifications that allow for operation in faulty conditions are also presented. As a result of the analyzed works, it can be concluded that ML inverters can significantly increase their availability and are able to operate even with some faulty components.