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:1001-2060(2006)05-0539-02,(,614000):;;,2003,:,,,4000km12,13,2.525MW,1Ó,:2.5;4;6;12;16MW;Ó215;4;6MW(-2500,-4000,-6000);Ó,4;6;10;12;16;25MW,360-40004MW,2000(),8PAO,:,50%,ElectronicSolarS.R.L20062-4000,Pratt&Whiney,,16MW,-90A2,-16,3000rPmin,,-1620062050,501956-62,2HS51959HS7(-82B)2090,CATIC,-30,18.7MW2003SAERI2,17.5MWAVIC-1SAERI,,2.525MW21520069JOURNALOFENGINEERINGFORTHERMALENERGYANDPOWERVol.21,No.5Sep.,2006,(-)1,-12500400060001200016000250002.546121625PMW2.554.136.1412.316.424.85P%22.125.027.234.136.039.0PGJh-1P%24.6P77.135.1P80.348.1P83.169.4P83.985.3P84.7113P85.6PGJh-1P%64.8P85.261.5P85.667.8P86.095P85.8115.9P86.4165.7P87.8PGJh-1P%223.9P93.9257.4P93.8276.6P93.7368.3P93.2445.3P93.3648.4P93.9:ISO,,,49984kJPkg,2.54:(1),,;(2)40008h;(3)(),;(4)NOxCO,,;(5)(4500h),()ASMEJournalofEngineeringforGasTurbinesandPower200510,,,,,R,,,,(=1.4)CO2(=1.29)(=1.67),,,()0452006Keywords:sludge,pyrolysis,mechanismfunction=AnIntelligentRemoteFault2diagnosisSystemforaTurbogeneratorSet[,]PHEQing,DUDong2mei,LIHong(EducationMinistryKeyLaboratoryonConditionMonitoringandControlofPowerPlantEquipmentAffiliatedtoEnergyandPowerEngineeringCollegeundertheNorthChinaElectricPowerUniver2sity,Beijing,China,PostCode:102206)PPJournalofEngineeringforThermalEnergy&Power.-2006,21(5).-532535Analyzedandstudiedarethetechniquesofintelligentfaultdiagnosisofvibrationforturbogeneratorsets.Bycombiningartificialneuralnetworktechnologywithobject2orientedone,afoursymptomneuralnetworkhasbeenestablished.Thefoursymptomsarevibrationfrequencyspectrum,axial2centertrajectory,speeding2up2and2downcharacteristicsandloadcharacteristics.Meanwhile,constructedwasanintelligentfault2diagnosisneuralnetworkforsensingvibrationsofsteamturbogeneratorsetswithincompletesymptominputs.Withthefrequencyspectrumsymptomsofturbogeneratorsetvibra2tionsservingasanexample,amethodfortheautomaticacquisitionoffrequencyspectrumsymptomswasstudiedandaspecificcasewasgivenofcomprehensivefaultdiagnosiswithanincompletesymptombasedonthefrequencyspectrumsymptom.Onthisbasis,byusingaBrowserPServermodeandJavatechnology,anintelligentremotefault2diagnosissys2temforturbogeneratorsetswasdevelopedalongwithadescriptionofthestructurecompositionofthesystem,functionalmodules,serversandclient2terminalprogramdesignandimplementationmethod.Keywords:turbogeneratorset,vibra2tion,neuralnetwork,intelligentfaultdiagnosis,remotediagnosis=StructureOptimizationFeaturesofQuasi2heatEnginesandTheirDemonstra2tionJustification[,]PZHANGXiao2hui(ThermalEnergyDepartmentoftheSoochowUniversity,Suzhou,China,PostCode:215006)PPJournalofEngineeringforThermalEnergy&Power.-2006,21(5).-536538Basedontheanalysisoftheconfigurationoptimizationcharacteristicsofanexistingheatengineandaquasi2heatenginedevice,themodelofaquasi2heatenginehasbeenextendedtoageneraltransmission2processmodel.Throughavariation2almethod,theconfigurationoptimizationcriterionforgeneraltransmissionprocesseswasderived,provingthatwithre2specttoalineartransmissionmodelandundertheconditionofafinite2dimensionconstraint,withtheentropyproductioninthetransmissionprocess(ordevice)beingatitsminimum,anequipartitionoftheconfigurationwillbeitsbasicchar2acteristics.Inthemeanwhile,alsodescribedistheapplicationoftheconfigurationoptimizationoftransmissionprocessesintheanalysisofquasi2heatenginesandinthestudyofgeneralizedthermodynamicsoptimizationtheory.Moreover,theconfigurationoptimizationfeatureunderdiscussionhasbeenpreliminarilyverifiedalongwithabriefexpositionofthede2velopmenttrendofitsapplications.Keywords:engineeringthermodynamics,quasi2heatengine,transmissionprocess,configurationoptimization=GasTurbineTechnologyofPermEngineManufacturingComplex[,]PALEXANDERYinojamchef,DANIYLSulimof(PermEngineManufacturingComplexStockCorp.ManagineCompany,Perm,Russia,PostCode:614000)PPJournalofEngineeringforThermalEnergy&Power.-2006,21(5).-539540Keywords:gasturbine;performance;powerplant0552006