Q235钢均匀腐蚀声发射监测实验研究
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摘要
在石油工业生产过程中，工业设备的安全问题始终处于重要地位，而金属材料的腐蚀现象是生产设备安全的最大隐患。金属设备所接触的复杂环境加速了腐蚀现象的发生，进而增加了生产事故的发生机率。一旦在生产过程中发生事故，必然会给国家的财产造成损失，对社会造成恶劣的影响。因而世界各国每年都会在腐蚀防护与监测上投入大量的人力与物力。
金属储罐底板的腐蚀现象包括点蚀和均匀腐蚀两部分。两种腐蚀现象都能对金属储罐底板造成严重的破坏，引发裂纹产生、腐蚀穿孔，进而导致介质泄漏，引起严重的事故。均匀腐蚀的发展速度虽然缓慢，但腐蚀面积大，并且均匀腐蚀过程中的气泡产生过程和金属溶解过程所产生的声发射信号具有代表性。Q235钢为金属储罐常用底板材料，对其均匀腐蚀过程中产生的声发射信号进行研究，探讨腐蚀声源的产生机制，有利于进行腐蚀防护与监测。
本文经在查阅大量国内外腐蚀声发射研究文献后，建立了一套提取均匀腐蚀声发射信号的实验系统。分别对均匀腐蚀过程中气泡产生、破裂过程和金属溶解、生成物剥落过程进行声发射信监测。利用声发射参数分析法，分析了Q235均匀腐蚀气泡产生过程和金属溶解过程的声发射特征。运用小波分析在信号去噪和特征提取中的相关理论知识，结合实际声发射信号的特点采用阈值去噪方法剔出了噪声信号的干扰，并对降噪处理后的信号进行四层小波包分解，提取分解后各节点能量作为神经网络的输入。在结构上选取“紧致型”的小波神经网络，以Morlet小波函数作为隐含层激励函数，网络学习训练过程基于误差的逆向传播，按照梯度下降方向调整网络参数，同时避免了网络陷入局部最优解中,达到了对均匀腐蚀过程中金属溶解与气泡破裂过程的模式识别。
In the production process of the oil industry, the security of industrial equipment hasalways been an important position. And for the safety of production equipment, the corrosionof metal materials is the biggest hidden trouble. the complex environment that metalequipment contact with accelerated corrosion phenomena, and the accidents in productionincreases. The occurring of an accident in the production process is bound to cause lossing theproperty of the state as well as the adverse impact to the society. And a lot of manpower andresources were put into the corrosion protection and monitoring every year in the wholeworld.
In general, the corrosion of the metal tank bottom includes two parts, the pitting and theuniform corrosion. Both of the two corrosions can cause serious damage to the metal tankbottom. For example causing cracks and corrosion perforation, which can led to a media leakand causing a serious accident. Although the rate of the development of uniform corrosion isrelatively slow, the corrosion area is relatively large. And AE signals Collected from theprocess of bubble formation process and the metal dissolution process is representative in theuniform corrosion. The studying of acoustic emission signals generated in the process ofuniform corrosion will enable us to understand the corrosion mechanism better and better, anddo well in the protection and monitoring of corrosion.
After reading a large number of domestic and foreign research literature on the corrosionacoustic emission we establish our own experimental system of extraction of uniformcorrosion on the acoustic emission signals. The experiment monitored the rupture process ofHydrogen bubble, the metal dissolution and the process of resultant flaking. According to theanalysis by the acoustic emission parameters, we study into the acoustic emissioncharacteristics of the bubble formation process and the metal dissolution in the metal uniformcorrosion. According to the theoretical knowledge of the wavelet analysis and thecharacteristics of the actual acoustic emission, we exclude the interference of the noise signalby using the threshold noise reduction method. We use the four-layer wavelet packet methoddecompose of the signal after the noise reduction processing, and extract the energy of eachnode as input of neural network. And we select the “compact” Wavelet Neural Network. Wemake morlet wavelet function as the hidden layer activation function. According to theapplication of the reverse spread error network learning and training process, we adjust thenetwork parameters following the direction of gradient descent. While avoiding the network into the local optimal solution, we have reached the pattern recognition between the processof metal dissolution and bubble rupture of uniform corrosion.
金属储罐底板的腐蚀现象包括点蚀和均匀腐蚀两部分。两种腐蚀现象都能对金属储罐底板造成严重的破坏，引发裂纹产生、腐蚀穿孔，进而导致介质泄漏，引起严重的事故。均匀腐蚀的发展速度虽然缓慢，但腐蚀面积大，并且均匀腐蚀过程中的气泡产生过程和金属溶解过程所产生的声发射信号具有代表性。Q235钢为金属储罐常用底板材料，对其均匀腐蚀过程中产生的声发射信号进行研究，探讨腐蚀声源的产生机制，有利于进行腐蚀防护与监测。
本文经在查阅大量国内外腐蚀声发射研究文献后，建立了一套提取均匀腐蚀声发射信号的实验系统。分别对均匀腐蚀过程中气泡产生、破裂过程和金属溶解、生成物剥落过程进行声发射信监测。利用声发射参数分析法，分析了Q235均匀腐蚀气泡产生过程和金属溶解过程的声发射特征。运用小波分析在信号去噪和特征提取中的相关理论知识，结合实际声发射信号的特点采用阈值去噪方法剔出了噪声信号的干扰，并对降噪处理后的信号进行四层小波包分解，提取分解后各节点能量作为神经网络的输入。在结构上选取“紧致型”的小波神经网络，以Morlet小波函数作为隐含层激励函数，网络学习训练过程基于误差的逆向传播，按照梯度下降方向调整网络参数，同时避免了网络陷入局部最优解中,达到了对均匀腐蚀过程中金属溶解与气泡破裂过程的模式识别。
In the production process of the oil industry, the security of industrial equipment hasalways been an important position. And for the safety of production equipment, the corrosionof metal materials is the biggest hidden trouble. the complex environment that metalequipment contact with accelerated corrosion phenomena, and the accidents in productionincreases. The occurring of an accident in the production process is bound to cause lossing theproperty of the state as well as the adverse impact to the society. And a lot of manpower andresources were put into the corrosion protection and monitoring every year in the wholeworld.
In general, the corrosion of the metal tank bottom includes two parts, the pitting and theuniform corrosion. Both of the two corrosions can cause serious damage to the metal tankbottom. For example causing cracks and corrosion perforation, which can led to a media leakand causing a serious accident. Although the rate of the development of uniform corrosion isrelatively slow, the corrosion area is relatively large. And AE signals Collected from theprocess of bubble formation process and the metal dissolution process is representative in theuniform corrosion. The studying of acoustic emission signals generated in the process ofuniform corrosion will enable us to understand the corrosion mechanism better and better, anddo well in the protection and monitoring of corrosion.
After reading a large number of domestic and foreign research literature on the corrosionacoustic emission we establish our own experimental system of extraction of uniformcorrosion on the acoustic emission signals. The experiment monitored the rupture process ofHydrogen bubble, the metal dissolution and the process of resultant flaking. According to theanalysis by the acoustic emission parameters, we study into the acoustic emissioncharacteristics of the bubble formation process and the metal dissolution in the metal uniformcorrosion. According to the theoretical knowledge of the wavelet analysis and thecharacteristics of the actual acoustic emission, we exclude the interference of the noise signalby using the threshold noise reduction method. We use the four-layer wavelet packet methoddecompose of the signal after the noise reduction processing, and extract the energy of eachnode as input of neural network. And we select the “compact” Wavelet Neural Network. Wemake morlet wavelet function as the hidden layer activation function. According to theapplication of the reverse spread error network learning and training process, we adjust thenetwork parameters following the direction of gradient descent. While avoiding the network into the local optimal solution, we have reached the pattern recognition between the processof metal dissolution and bubble rupture of uniform corrosion.
引文
[l]陈匡民．过程装备腐蚀与防护[M]．北京：化学工业出版社，2007．1~5．
[2]韩磊．基于虚拟仪器的腐蚀电化学测试系统的研制及应用[D]．天津：天津大学，2005．3~20．
[3]周玉波,邵丽艳等．腐蚀监测技术现状及发展趋势[J].海洋科学，2005，29(7)：77~80．
[4]耿荣生，傅刚强．金属点蚀过程声发射源机制研究[J]．声学学报，2002，27(4):369~372．
[5] M.Fregonese，H.Idrissi，H.Mazille，L.Renaud，Y.Cetre．Initiation and propagation stepsin pitting corrosion of austenitic stainless steels：monitoring by acoustic emission[J]．Corrosion Science，43(2001)str．627~641．
[6] Heiple CR，Carpenter SH．Acoustic Emission[M]．Mathiews JR，ed．New York：1981
[7] PollockAA．Acoustic emission distribution[A]．InternationalAdvances in NondestructiveTesting(Vol.7)[R]．1981．215~239．
[8] Miller Ronnie K，Mcintire Paul，eds．Nondestructive Testing Handbook(Vol.5)AcouticEmission Testing[M]．Second editon，Columbus：American Society for NondestrutiveTesting，1987．
[9] A．Cakir，S．Tuncell，A.Aydin．AE response of205L SS during SSR testunderpotentiostatic control [J]．Corrosion Science41，1175~1183，1999．
[10] R.S.Geng．Corrosion-related Acoustic Emission and Its Identification[J]．BeijingAeronautical Technology Research Centre，Beijing100076，China．
[11] G.Dai，B.O.Zhang，G.L.Jin．AE Characterization during Stress Corrosion Cracking on16MnR Steel[J]．Progress in Acoustic Emission，The Japanese Society for NDI1988，566~537．
[12]李伟．低碳钢点蚀声学监测与信号处理技术研究[D]．大庆：大庆石油学院，2006．3~50．
[13] C.jirarungsatian，A.Prateepasen．Pitting and uniform corrosion source recognition usingacoustic emission parameters[J]．Corrosion Science，2010(52)：187~197．
[14] Green.A.T，Lockman.C.S，Steele.R.K．Acoustic verification of structural integrity ofPolaris chambers[J]．Mordern Plastics．1964，41(11)：137~139，178，180．
[15] Egle.D.M，Taro.C.A．Analysis of acoustic-emission strain waves[J]．The Journal ofthe Acoustical Society of America．1967，41(2)：321~328．
[16] Prine.D.W．Inspection of nuclear reactor welding by acoustic emission[J]．WeldingDesign and Fabrication．1977，50(1)：67~74．
[17] Landis.E， Ouyang.C， Shan.S.P． Acoustic emission source locations inconcrete[A]．ASCE Engineering Mechanics Specialty Conference[C]．1991：1051~1055．
[18] Rice.A．Characteristics of acoustic emission sensors employed for tool conditionmonitoring[A]．Proceedings of the Seventh Workshop on Supervising and Diagnostics ofMachining Systems[C]．1996：241~252．
[19] Ravindra.H.V．Some aspects of acoustic emission signal processing[J]．Journal ofMaterials Processing Technology．2001，109：242~247．
[20] Paulo.R，Aguiar.P.J.A，Semi.E.C．In-process grinding moinitoring by acousticemission[A]2004，ICASSP04，(5)：405~408．
[21] GB/T18182-2000．金属压力容器声发射检测及结果评价方法．北京：中国标准出版社出版，2000．
[22] Shiwa.M．Analysis of acoustic emission waveforms[J]．Acoustic Emission．1990，10(2)：35~41．
[23] Lim.J，Micro.K.T．Cracking in stainless steel pipe detection by using acoustice missionand crest factor technique[A]Instrumentation and MeasurementTechnology ConferenceWarsaw，Poland，May1~3，2007[C]，IEEE Xplore：1~3．
[24]沈功田．金属压力容器的声发射源特性及识别方法的研究[D]．北京：清华大学机械系，1998．
[25]赵静荣．声发射信号处理系统与源识别方法的研究[D]．长春：吉林大学，2010．
[26]冯哲圣，杨邦朝．电化学点蚀信号的小波分析研究[J]．仪器仪表学报，2003，24(3)：253~259．
[27]高志明，宋小平等．小波分析在腐蚀电化学瞬态检测中的应用[J]．中国腐蚀与防护学报，2001，21(4)：245~250．
[28]戴光，李宝玉，李伟．金属腐蚀染噪声发射信号的小波分析[J]．化工机械，2004，31(5)：285~289
[29]李录平，邹新元，唐月清．小波变化在声发射信号特征参数监测中的应用[J]．振动与冲击，2001，20(2)：67~71
[30]张晓峰，李功燕．应用小波分析提取故障诊断信号的特定频段[J]．振动与冲击，2004，23(4)：47~53．
[31] GangQi，Wavelet-based acoustic emission analysis of composites[D]，Texas TechUniversity，1996.．
[32]崔岩，李小仰，彭华新，等．基于声发射小波分析的非连续增强金属华复合材料界面表征，科学通报，1998，43(6)：656~657．
[33] Qing-Qing Ni，et al．Wavelet transform of acoustic emission signals in failure of modelcomposites [J]．Engineering Fracture Mechanic，2002，69：717-728．
[34] Changming Chen，Radovan Kovacevic，Dragana Jandgric，Wavelet transform analysisof acoustic emission in monitoring friction stir welding of6061aluminum[J]．International Journal of Machine Tools&Manufacture，43，2003：1383~1390．
[35] Hyunjo Jeong．Young-Su Jang，Wavelet analysis of plate wave propagation in compositelaminates[J]．Composite Struetures，2000(49)：443~450．
[36] Yang Li，Zhou Yi-Chun，wavelet analysis of acoustic emission Signals from thermalbarrier coatings[J]．Trans．Nonferrous Met．Soc．China，2002(16)：270~275．
[37] Eng Teik Ng，Gang Qi，Material fatigue behavior characterization using thewavelet-based AE technique a case study of acrylic bone cement[J]．EngineeringFraeture Mechanics．2001(68)：1477~1492．
[38] Gang Qi．Alan Barhorst，Javad Hashemi etl，Discrete wavelet decomposition ofacoustic emission signals from carbon-fiber-reinforced composites[J]． CompositesScience and Technology．1997：57：389~403．
[39] Q Wang，F chu．Experimental determination of the rubbing location by means ofacoustic emission and wavelet transform[J]． Journal of Sound and Vibration，2001．248(l)：91~103．
[40] T.Warren Liao，Chi-Fen Tian，J.Qu，P.J.Blau，Awavelet-based methodology for grindingwheel condition monitoring[J]． International Journal of Machine Tools&Manufacture．47．2007：580~592．
[41]何建平，王宁．基于小波变换的岩体AE波形特征研究.工矿自动化[J]，2007(4)：14~18．
[42]金解放，赵奎，王晓军，等．岩石声发射信号处理小波基选择的研究[J]．矿业研究与开发，2007，27(2)：12~16．
[43] Yuyama S，Kishi T，Hismaatsu Y．Effect of environments，mechanical conditions andsensitization on cracks growth and AE behavior during corrosion fatigue process ofsensitized304stainless steel[J]．Japan Inst．Metals，1982，46(5)：509~512．
[44] Knopoff L．Surface motion of thick plate[J]．Appl．phys，1958，29(4)：661~670
[45] Gorman M R．Plat wave acoustic emission[J]．JASA，1991，90(l)：358~364．
[461刘永辉，张佩芬，金属腐蚀学原理[M]．北京：航空工业出版社，1993，85~94
[47]朗道A.A，李弗席兹E.M．连续介质力学，第三册[M]．北京：人民教育出版社，1962，67~89．
[48]耿荣生.利用模拟声发射源评价飞机雷达罩胶接质量[J]．声学学报，1999，24(4):367~372．
[49] Dunegan H L，ModalAnalysis ofAcoustic Emission Signals[J]．Journal ofAcousticEmission，1998(15)，l~4．
[50] Prosser W H，Gorman M R．Plate mode velocities in graphite/epoxy plates[J]．JASA，1994，96(2)：902~907．
[51] Victotov IA．Rayleigh and Lamb Waves[M]．New York：Plenum Press，1967．
[52]徐志敏．小波网络的研究及其应用[D]．济南：山东师范大学硕士学位论文，2005．
[53]仲京臣．基于小波神经网络的故障诊断研[D]．青岛：中国海洋大学硕士学位论文，2004．
[54]张正刚．基于小波神经网络的故障诊断方法研[D]．大庆：大庆石油学院硕士学位论文，2005．
[55] Rouhani.R， Mehra.R.K． Model Algorithmic Control Basic TheoreticalProperties．Automatica，1982，18(4)：401~414．
[56] Clarke.D.W， et al． Generalized Predictive Control-Part1and Part2BasicAlgorithm． Automatica，1987，23(2)：137~148．
[57] Lelic.M.A，Zarrop.M.B．Generalized Pole Placement Self-tuning Controller．Int JControl，1987，46(2)：547~568．
[58] Ydsti.B.E．Extended Horizon Adaptive Control.．Budapest：Proc IFAC9th Wordongress，1981，2：911~915．
[59] De Keyser R M C． et al．A Self-tuning Multi-step．Predictior ApplicationAutomatica．1981，117(1)：167~174．
[60]王祖和，杨毅．施工项目成本动态测算系统研究[J]．管理工程学报，2003，1：75~78
[61]李一军，叶强，李钥．基于BP神经网络的产品报价决策支持方法及其报价风险研究[J]．管理工程学报，2003，4：33~36．
[62]孙金丽，郑立群，张世英．基于神经网络的工程造价估算方法及其Excel实现[J]．基建优化，2003，1：30~40．
[2]韩磊．基于虚拟仪器的腐蚀电化学测试系统的研制及应用[D]．天津：天津大学，2005．3~20．
[3]周玉波,邵丽艳等．腐蚀监测技术现状及发展趋势[J].海洋科学，2005，29(7)：77~80．
[4]耿荣生，傅刚强．金属点蚀过程声发射源机制研究[J]．声学学报，2002，27(4):369~372．
[5] M.Fregonese，H.Idrissi，H.Mazille，L.Renaud，Y.Cetre．Initiation and propagation stepsin pitting corrosion of austenitic stainless steels：monitoring by acoustic emission[J]．Corrosion Science，43(2001)str．627~641．
[6] Heiple CR，Carpenter SH．Acoustic Emission[M]．Mathiews JR，ed．New York：1981
[7] PollockAA．Acoustic emission distribution[A]．InternationalAdvances in NondestructiveTesting(Vol.7)[R]．1981．215~239．
[8] Miller Ronnie K，Mcintire Paul，eds．Nondestructive Testing Handbook(Vol.5)AcouticEmission Testing[M]．Second editon，Columbus：American Society for NondestrutiveTesting，1987．
[9] A．Cakir，S．Tuncell，A.Aydin．AE response of205L SS during SSR testunderpotentiostatic control [J]．Corrosion Science41，1175~1183，1999．
[10] R.S.Geng．Corrosion-related Acoustic Emission and Its Identification[J]．BeijingAeronautical Technology Research Centre，Beijing100076，China．
[11] G.Dai，B.O.Zhang，G.L.Jin．AE Characterization during Stress Corrosion Cracking on16MnR Steel[J]．Progress in Acoustic Emission，The Japanese Society for NDI1988，566~537．
[12]李伟．低碳钢点蚀声学监测与信号处理技术研究[D]．大庆：大庆石油学院，2006．3~50．
[13] C.jirarungsatian，A.Prateepasen．Pitting and uniform corrosion source recognition usingacoustic emission parameters[J]．Corrosion Science，2010(52)：187~197．
[14] Green.A.T，Lockman.C.S，Steele.R.K．Acoustic verification of structural integrity ofPolaris chambers[J]．Mordern Plastics．1964，41(11)：137~139，178，180．
[15] Egle.D.M，Taro.C.A．Analysis of acoustic-emission strain waves[J]．The Journal ofthe Acoustical Society of America．1967，41(2)：321~328．
[16] Prine.D.W．Inspection of nuclear reactor welding by acoustic emission[J]．WeldingDesign and Fabrication．1977，50(1)：67~74．
[17] Landis.E， Ouyang.C， Shan.S.P． Acoustic emission source locations inconcrete[A]．ASCE Engineering Mechanics Specialty Conference[C]．1991：1051~1055．
[18] Rice.A．Characteristics of acoustic emission sensors employed for tool conditionmonitoring[A]．Proceedings of the Seventh Workshop on Supervising and Diagnostics ofMachining Systems[C]．1996：241~252．
[19] Ravindra.H.V．Some aspects of acoustic emission signal processing[J]．Journal ofMaterials Processing Technology．2001，109：242~247．
[20] Paulo.R，Aguiar.P.J.A，Semi.E.C．In-process grinding moinitoring by acousticemission[A]2004，ICASSP04，(5)：405~408．
[21] GB/T18182-2000．金属压力容器声发射检测及结果评价方法．北京：中国标准出版社出版，2000．
[22] Shiwa.M．Analysis of acoustic emission waveforms[J]．Acoustic Emission．1990，10(2)：35~41．
[23] Lim.J，Micro.K.T．Cracking in stainless steel pipe detection by using acoustice missionand crest factor technique[A]Instrumentation and MeasurementTechnology ConferenceWarsaw，Poland，May1~3，2007[C]，IEEE Xplore：1~3．
[24]沈功田．金属压力容器的声发射源特性及识别方法的研究[D]．北京：清华大学机械系，1998．
[25]赵静荣．声发射信号处理系统与源识别方法的研究[D]．长春：吉林大学，2010．
[26]冯哲圣，杨邦朝．电化学点蚀信号的小波分析研究[J]．仪器仪表学报，2003，24(3)：253~259．
[27]高志明，宋小平等．小波分析在腐蚀电化学瞬态检测中的应用[J]．中国腐蚀与防护学报，2001，21(4)：245~250．
[28]戴光，李宝玉，李伟．金属腐蚀染噪声发射信号的小波分析[J]．化工机械，2004，31(5)：285~289
[29]李录平，邹新元，唐月清．小波变化在声发射信号特征参数监测中的应用[J]．振动与冲击，2001，20(2)：67~71
[30]张晓峰，李功燕．应用小波分析提取故障诊断信号的特定频段[J]．振动与冲击，2004，23(4)：47~53．
[31] GangQi，Wavelet-based acoustic emission analysis of composites[D]，Texas TechUniversity，1996.．
[32]崔岩，李小仰，彭华新，等．基于声发射小波分析的非连续增强金属华复合材料界面表征，科学通报，1998，43(6)：656~657．
[33] Qing-Qing Ni，et al．Wavelet transform of acoustic emission signals in failure of modelcomposites [J]．Engineering Fracture Mechanic，2002，69：717-728．
[34] Changming Chen，Radovan Kovacevic，Dragana Jandgric，Wavelet transform analysisof acoustic emission in monitoring friction stir welding of6061aluminum[J]．International Journal of Machine Tools&Manufacture，43，2003：1383~1390．
[35] Hyunjo Jeong．Young-Su Jang，Wavelet analysis of plate wave propagation in compositelaminates[J]．Composite Struetures，2000(49)：443~450．
[36] Yang Li，Zhou Yi-Chun，wavelet analysis of acoustic emission Signals from thermalbarrier coatings[J]．Trans．Nonferrous Met．Soc．China，2002(16)：270~275．
[37] Eng Teik Ng，Gang Qi，Material fatigue behavior characterization using thewavelet-based AE technique a case study of acrylic bone cement[J]．EngineeringFraeture Mechanics．2001(68)：1477~1492．
[38] Gang Qi．Alan Barhorst，Javad Hashemi etl，Discrete wavelet decomposition ofacoustic emission signals from carbon-fiber-reinforced composites[J]． CompositesScience and Technology．1997：57：389~403．
[39] Q Wang，F chu．Experimental determination of the rubbing location by means ofacoustic emission and wavelet transform[J]． Journal of Sound and Vibration，2001．248(l)：91~103．
[40] T.Warren Liao，Chi-Fen Tian，J.Qu，P.J.Blau，Awavelet-based methodology for grindingwheel condition monitoring[J]． International Journal of Machine Tools&Manufacture．47．2007：580~592．
[41]何建平，王宁．基于小波变换的岩体AE波形特征研究.工矿自动化[J]，2007(4)：14~18．
[42]金解放，赵奎，王晓军，等．岩石声发射信号处理小波基选择的研究[J]．矿业研究与开发，2007，27(2)：12~16．
[43] Yuyama S，Kishi T，Hismaatsu Y．Effect of environments，mechanical conditions andsensitization on cracks growth and AE behavior during corrosion fatigue process ofsensitized304stainless steel[J]．Japan Inst．Metals，1982，46(5)：509~512．
[44] Knopoff L．Surface motion of thick plate[J]．Appl．phys，1958，29(4)：661~670
[45] Gorman M R．Plat wave acoustic emission[J]．JASA，1991，90(l)：358~364．
[461刘永辉，张佩芬，金属腐蚀学原理[M]．北京：航空工业出版社，1993，85~94
[47]朗道A.A，李弗席兹E.M．连续介质力学，第三册[M]．北京：人民教育出版社，1962，67~89．
[48]耿荣生.利用模拟声发射源评价飞机雷达罩胶接质量[J]．声学学报，1999，24(4):367~372．
[49] Dunegan H L，ModalAnalysis ofAcoustic Emission Signals[J]．Journal ofAcousticEmission，1998(15)，l~4．
[50] Prosser W H，Gorman M R．Plate mode velocities in graphite/epoxy plates[J]．JASA，1994，96(2)：902~907．
[51] Victotov IA．Rayleigh and Lamb Waves[M]．New York：Plenum Press，1967．
[52]徐志敏．小波网络的研究及其应用[D]．济南：山东师范大学硕士学位论文，2005．
[53]仲京臣．基于小波神经网络的故障诊断研[D]．青岛：中国海洋大学硕士学位论文，2004．
[54]张正刚．基于小波神经网络的故障诊断方法研[D]．大庆：大庆石油学院硕士学位论文，2005．
[55] Rouhani.R， Mehra.R.K． Model Algorithmic Control Basic TheoreticalProperties．Automatica，1982，18(4)：401~414．
[56] Clarke.D.W， et al． Generalized Predictive Control-Part1and Part2BasicAlgorithm． Automatica，1987，23(2)：137~148．
[57] Lelic.M.A，Zarrop.M.B．Generalized Pole Placement Self-tuning Controller．Int JControl，1987，46(2)：547~568．
[58] Ydsti.B.E．Extended Horizon Adaptive Control.．Budapest：Proc IFAC9th Wordongress，1981，2：911~915．
[59] De Keyser R M C． et al．A Self-tuning Multi-step．Predictior ApplicationAutomatica．1981，117(1)：167~174．
[60]王祖和，杨毅．施工项目成本动态测算系统研究[J]．管理工程学报，2003，1：75~78
[61]李一军，叶强，李钥．基于BP神经网络的产品报价决策支持方法及其报价风险研究[J]．管理工程学报，2003，4：33~36．
[62]孙金丽，郑立群，张世英．基于神经网络的工程造价估算方法及其Excel实现[J]．基建优化，2003，1：30~40．