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时间:2020-05-14
《管道超声内检测自动壁厚转换算法.pdf》由会员上传分享,免费在线阅读,更多相关内容在行业资料-天天文库。
1、第65卷第11期化工学报、,01.65No.1l2014年011月CIESCJournalNovember2014一研一一究一一论一一R文&一管道超声内检测自动壁厚转换算法唐建,一,焦向东,戴波(北京化工大学机电工程学院,北京100029;北京石油化工学院,北京102617)摘要:管道超声内检测脉冲重复频率很高,产生的回波数据量很大,壁厚信息的自动获取是其核心问题。同时实际管道工况复杂,有用回波信号混杂多种噪声及不确定性干扰,这就要求自动壁厚转换算法有很强的适应性。但常用的二阶统计量方法用于自动壁厚转换时精度
2、较低,存在误判率与漏检率较高等情况。针对这一问题,提出采用高阶统计量中的1.5维谱处理回波信号,并根据壁厚频率范围和谱线的周期性特点,截取频谱数据做二次变换,得到改进的1.5维谱,获取壁厚的渡越时间,得出壁厚。实验结果表明该算法检测精度很高,大大优于二阶统计量方法,适用于长距离输油管道腐蚀内检测。关键词:管道;超声内检测:高阶统计量;1.5维谱;自动壁厚转换DOI:10.3969~.issn.0438-1157.2014.11.039中图分类号:TE973.6文献标志码:A文章编号:0438~1157(201
3、4)11—4490—07AutomaticwallthicknessconversionalgorithmofpipelineultrasonicinnerinspectionTANGJian'.,$lAOXiangdong2DAIBo,(SchoolofMechanicalandElectricalEngineering,Beo'ingUniversityofChemicalTechnology,BeUing100029,China2Beo'ingInstituteofPetrochemicalTechno
4、logy,Beijing102617,China)Abstract:Becausethepulserepetitionfrequencyofpipelineultrasonicinnerinspectionisveryhigh,theechodataamountgeneratedisverylarge.automaticacquisitionofwallthicknessinformationisthecoreproblem.Atthesametime,theworkingconditionoftheactu
5、alpipelineisverycomplex,theusefulechosignalismixedwithvariednoiseanduncertaindisturbance.whichrequirestheautomaticwal1tI1icknessconversionalgorithmwithastrongadaptability.Buttheaccuracyofsecond。orderstatistiesmethodcommonlyusedfortheautomaticwallthicknessco
6、nversionislower,themisdiagnosisrateandthemissrateishigher,andsoon.Aimingatthisproblem,theechosignalwasprocessedusing1.5一dimensionspectrumofhigher-orderstatistics.Andaccordingtothefrequencyrangeofwallthicknessandtheperiodiccharacteristicsofspectrallines,thes
7、pectrumdatawereinterceptedandtransformedagain.andtheimproved1.5-dimensionspectrumwasobtained.Thetransittimeofthewallthicknesswasacquired.andthenthewallthicknesswasobtained.Experimentalresultsshowthattheinspectionprecisionofthealgorithmisveryhighandmuchbette
8、rthanthesecond—orderstatisticsmethod,whichissuitableforthecorrosioninnerinspectiononlong—distanceoi1pipeline.Keywords:pipeline;ultrasonicinnerinspection;higher-orderstatistics;1.5一dimensionspectrum;aut
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