全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
热力发电  2015 

改进型非线性状态估计的制粉系统故障诊断

, PP. 87-92

Keywords: 制粉系统,故障诊断,非线性,状态估计,马氏距离,过程记忆矩阵,冗余数据,诊断效率

Full-Text   Cite this paper   Add to My Lib

Abstract:

为能够快速、准确地对制粉系统故障进行诊断,根据制粉系统的运行特性和故障特征,对基于非线性状态估计的制粉系统故障诊断方法,提出了新的构造过程记忆矩阵的方法,依据马氏距离对故障数据样本进行预处理,并使用预处理后的数据构造过程记忆矩阵,从而有效地减少了冗余数据,提高了诊断效率和诊断的实用性和稳定性。

References

[1]  潘强,熊波.基于灵敏度预分类的bp神经网络故障诊断方法[j].测试技术学报,2014,28(4):305-310.panqiang,xiongbo.faultdiagonsismethodofbpneuralnetworksbasedonsensitivitypreclassifying[j].journaloftestandmeasurementtechnology,2014,28(4):305-310.
[2]  王松岭,刘锦廉,许小刚.基于小波包变换和奇异值分解的风机故障诊断研究[j].热力发电,2013,42(11):101-106.wangsongling,liujinlian,xuxiaogang.waveletpackettransformandsingularvaluedecompositionbasdefaultdiagnosisoffans[j].thermalpowergeneration,2013,42(11):101-106.
[3]  闫哲,王明春.基于核主元分析的凝汽器系统故障诊断[j].热力发电,2013,42(4):57-60.yanzhe,wangmingchun.kernelprincipalcomponentanalysisbasedfaultdiagonsisforcondensersystems[j].thermalpowergeneration,2013,42(4):57-60.
[4]  郭鹏,infielddavid,杨锡运.风电机组齿轮箱温度趋势状态监测及分析方法[j].中国电机工程学报,2011,31(32):129-136.guopeng,infielddavid,yangxiyun.windturbinegearboxconditionmonitoringusingtemperaturetrendanalysis[j].proceedingsofthecsee,2011,31(32):129-136.
[5]  李顺勇,宋云胜,赵兴旺.一种有效的面向高维数值型数据的聚类方法[j].山西大学学报(自然科学版),2014,37(2):206-209.lishunyong,songyunsheng,zhaoxingwang.aneffectiveclusteringapproachforhigh-dimensionalnumericdata[j].journalofshanxiuniversity(naturalscienceedition),2014,37(2):206-209.
[6]  grosskc,singerrm,wegerichsw,etal.applicationofamodel-basedfaultdetectionsystemtonuclearplantsignals[c]//proceedingsof9thinternationalconferenceonintelligentsystemsapplicationtopower-system.seoul,korea,1997.
[7]  bockhorstfk,grosskc,herzogjp,etal.msetmodelingofcrystalriver-3venturiflowmeters[c]//proceedingsofinternationalconferenceonnuclearengineering.sandiego,ca:1998:19-24.
[8]  chensf,pechtmg.multivariatestateestimationtechniqueforremainingusefullifepredictionofelectronicproducts[c]//proceedingsofaaaifallsymposiumartificialintelligentprognostics.arlington,va:2007:26-32.
[9]  cassidykj,grosskc,malekpoura.advancedpatternrecognitionfordetectionofcomplexsoftwareagingphenomenainonlinetransactionprocessingservers[c]//proceedingsofdependablesystemsandnetworks.washingtond.c.,usa:2002:35-40.[10]singerrm,grosskc,herzogjp,etal.model-basednuclearpowerplantmonitoringandfaultdetection:theoreticalfoundation[c]//proceedingsof9thinternationalconferenceonintelligentsystemsapplicationtopowersystem.seoul,korea:1997:61-68.[11]blackcl,uhrigre,hinesjw.systemmodelingandinstrumentcalibrationverificationwithanonlinearstateestimatetechnique[c]//proceedingsofmaintenanceandreliableconference.knoxville,tn:1998:52-57.[12]王岩,隋思.数理统计与matlab数据分析[m].2版.北京:清华大学出版社,2014:308-312.wangyan,suisi.mathematicalstatisticsanddataanalysiswithmatlab[m].2nded.beijing:tsinghuauniversitypress,2014:308-312.[13]董立羽,肖增弘.电厂锅炉制粉系统塞煤问题的对策分析[j].陕西电力,2008,36(2):24-27.dongliyu,xiaozenghong.analysisofcountermeasuresforresolvingproblemofcoalplugginginboilerpulverizingsystem[j].shaanxielectricpower,2008,36(2):24-27.[14]杨国旗,屈祥.电站锅炉效率的影响因素和提高途径[j].陕西电力,2009,37(4):24-27.yangguoqi,quxiang.influencefactorofboilerefficiency&itsimprovementmeasureinpowerplant[j].shaanxielectricpower,2009,37(4):24-27.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133