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											|  Wysłany: Nie 3:33, 08 Maj 2011    Temat postu: franklin and marshall sale Feature extraction base |  |  
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											| ,[link widoczny dla zalogowanych] Feature extraction based on independent component analysis of complex neural network fault diagnosis
 
 
 USA20LuisBAlmeida. ICAoflinearandnonlinearmixtureasedonmutualin {ormation. ISTandINESC a 1D,[link widoczny dla zalogowanych], Lis-bon,[link widoczny dla zalogowanych], PortugalMulti-NeuralNetworksforFaultsDiagnosisBasedonICAFeatureExtractionYangShixiJiaoWeidongWuZhaotong (DepartmentofMechanicalEngineering. ZhejiangUniversity, Hangzhou, 310027, China) Abstract: Artificialneuralnetwork (ANN). especiallytheself-organizingmap (SOM) basedonunsupervisedlearningisakindofexcellentmethodforpatternsclusteringandrecognition. Independentcomponentanslysis (ICA) isapowe, rfultoolforanalyzingnongaussiandata. InICA. theFASTICAbasedonfixed-pointiterationisakindofANNalgorithmwithhigheffi-ciency. whichisspeciallyappropriatetofeatureextractionofmultivariatedataatrealtime. Inthispaper, theFASTICAisfirstlyproposedforfeatureextractionofdifferentmechanicalpatterns (includingnormal,[link widoczny dla zalogowanych], gearfaultandloosefoundation) · followedbycertaintypicalANN (forexampleRBFNorSOM), whichimplementsthefinalclassification. BymeansofICAandthefurtherfeatureextractionstrategybasedonresidualmutualinformation (RMI), higherthansecondorderfeaturesembeddedinmulti-channelvibrationmeasurementscanbecapturedeffectively. Thus, mechanicalfaultpatternscanberecog-nizedcorrectly. TheresultsfromcontrastexperimentsshowedthatthecompoundICA-SOMclassifiercanbeconstructedinsimplerway, andclassifyvariousfaultpatternsatconsiderableaccuracy,[link widoczny dla zalogowanych], bothofwhichimplyitsgreatpotentialinhealthcon-ditionmonitoringofmachines. Keywords: faultdiagnosis; neuralnetwork; independentcomponentanalysis first author : Yang Shixi , male, associate professor , PhD . January 1968 students. Tel : (0571) 87951924; E-mail: yangsx @ zju. edu. cn
 
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