Expert system to detect incipient fauts in rotating machines using fuzzy logic and virtual instrumentation

dc.contributorUniversidade Estadual Paulista (UNESP)
dc.creatorVanni, Renato
dc.creatorBotura Júnior, Galdenoro
dc.creatorLemos, Marilza Antunes de
dc.creatorMarques, Marcio Alexandre
dc.creatorRosa, Luiz Carlos
dc.date2016-03-02T12:59:43Z
dc.date2016-10-25T21:31:52Z
dc.date2016-03-02T12:59:43Z
dc.date2016-10-25T21:31:52Z
dc.date2012
dc.date.accessioned2017-04-06T10:01:18Z
dc.date.available2017-04-06T10:01:18Z
dc.identifierInternational Journal of Computer Theory and Engineering, v. 4, n. 6, p. 1011-1014, 2012.
dc.identifier1793-8201
dc.identifierhttp://hdl.handle.net/11449/135094
dc.identifierhttp://acervodigital.unesp.br/handle/11449/135094
dc.identifier0000-0003-4482-3300
dc.identifier2863978276801537
dc.identifier5612515856487911
dc.identifierhttp://www.ijcte.org/papers/628-S0074.pdf
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/945605
dc.descriptionThis paper refers to the design of an expert system that captures a waveform through the use of an accelerometer, processes the signal and converts it to the frequency domain using a Fast Fourier Transformer to then, using artificial intelligence techniques, specifically Fuzzy Reasoning, it determines if there is any failure present in the underlying mode of the equipment, such as imbalance, misalignment or bearing defects.
dc.languageeng
dc.relationInternational Journal of Computer Theory and Engineering
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectExpert systems
dc.subjectFault diagnosis
dc.subjectFuzzy logic
dc.subjectRotary machine
dc.subjectVirtual instrumentation
dc.titleExpert system to detect incipient fauts in rotating machines using fuzzy logic and virtual instrumentation
dc.typeOtro


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