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Distributed neuro-fuzzy feature forecasting approach for condition monitoring
dc.contributor.author | Zurita Millán, Daniel |
dc.contributor.author | Cariño Corrales, Jesús Adolfo |
dc.contributor.author | Delgado Prieto, Miquel |
dc.contributor.author | Ortega Redondo, Juan Antonio |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica |
dc.date.accessioned | 2015-03-24T13:52:26Z |
dc.date.created | 2014 |
dc.date.issued | 2014 |
dc.identifier.citation | Zurita, D. [et al.]. Distributed neuro-fuzzy feature forecasting approach for condition monitoring. A: IEEE International Conference on Emerging Technologies and Factory Automation. "Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation". Barcelona: Institute of Electrical and Electronics Engineers (IEEE), 2014. |
dc.identifier.isbn | 978-1-4799-4846-8 |
dc.identifier.uri | http://hdl.handle.net/2117/26982 |
dc.description.abstract | The industrial machinery reliability represents a critical factor in order to assure the proper operation of the whole productive process. In regard with this, diagnosis schemes based on physical magnitudes acquisition, features calculation, features reduction and classification are being applied. However, in this paper, in order to enhance the condition monitoring capabilities, a forecasting approach is proposed, in which not only the current status of the system under monitoring in identified, diagnosis, but also the future condition is assessed, prognosis. The novelties of the proposed methodology are based on a distributed features forecasting approach by means of adaptive neuro-fuzzy inference system models. The proposed method is validated by means of an accelerated bearing degradation experimental platform. |
dc.language.iso | eng |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Robòtica |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
dc.subject.lcsh | Artificial intelligence |
dc.subject.other | {condition monitoring |
dc.subject.other | feature selection |
dc.subject.other | fuzzy neural nets |
dc.subject.other | fuzzy reasoning |
dc.subject.other | pattern classification |
dc.subject.other | reliability |
dc.subject.other | ANFIS |
dc.subject.other | adaptive neuro-fuzzy inference system models |
dc.subject.other | condition monitoring capabilities |
dc.subject.other | distributed neuro-fuzzy feature forecasting approach |
dc.subject.other | feature calculation |
dc.subject.other | feature classification |
dc.subject.other | feature reduction |
dc.subject.other | industrial machinery reliability |
dc.subject.other | Artificial neural networks |
dc.subject.other | Degradation |
dc.subject.other | Forecasting |
dc.subject.other | Predictive models |
dc.subject.other | Prognostics and health management |
dc.subject.other | Time-domain analysis |
dc.subject.other | Training |
dc.subject.other | Artificial intelligence |
dc.subject.other | Condition monitoring |
dc.subject.other | Feature extraction |
dc.subject.other | Fuzzy neural networks |
dc.subject.other | Machine learning |
dc.subject.other | Prognosis |
dc.subject.other | Remaining Useful Life |
dc.subject.other | Time domain analysis} |
dc.title | Distributed neuro-fuzzy feature forecasting approach for condition monitoring |
dc.type | Conference report |
dc.subject.lemac | Intel·ligència artificial |
dc.contributor.group | Universitat Politècnica de Catalunya. MCIA - Motion Control and Industrial Applications Research Group |
dc.identifier.doi | 10.1109/ETFA.2014.7005180 |
dc.relation.publisherversion | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7005180&isnumber=7005023 |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 15535896 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Zurita, D.; Cariño , J.A.; Delgado, M.; Ortega, J. |
local.citation.contributor | IEEE International Conference on Emerging Technologies and Factory Automation |
local.citation.pubplace | Barcelona |
local.citation.publicationName | Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation |