Article(id=1245390151803847004, tenantId=1146029695717560320, journalId=1241701559352995854, issueId=1245390147664068826, articleNumber=null, orderNo=null, doi=10.13197/j.eeed.2024.0408, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1680624000000, receivedDateStr=2023-04-05, revisedDate=1685289600000, revisedDateStr=2023-05-29, acceptedDate=null, acceptedDateStr=null, onlineDate=1774853750420, onlineDateStr=2026-03-30, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774853750420, onlineIssueDateStr=2026-03-30, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774853750420, creator=13701087609, updateTime=1774853750420, updator=13701087609, issue=Issue{id=1245390147664068826, tenantId=1146029695717560320, journalId=1241701559352995854, year='2024', volume='44', issue='4', pageStart='1', pageEnd='233', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1774853749433, creator=13701087609, updateTime=1774854381443, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1245392798560662150, tenantId=1146029695717560320, journalId=1241701559352995854, issueId=1245390147664068826, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1245392798560662151, tenantId=1146029695717560320, journalId=1241701559352995854, issueId=1245390147664068826, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=79, endPage=88, ext={EN=ArticleExt(id=1245390152059699569, articleId=1245390151803847004, tenantId=1146029695717560320, journalId=1241701559352995854, language=EN, title=Wooden beam damage identification based on curvature mode and wavelet transform, columnId=null, journalTitle=Earthquake Engineering and Engineering Dynamics, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To address the limitations of curvature mode indicators in identifying minor structural damage, a method for structural damage identification that combines curvature mode and wavelet transform has been proposed. In this paper, ANSYS was used to establish a finite element model of the wooden beam before and after the damage and carry out modal analysis, and the curvature modes of the wooden beam before and after the damage was subjected to discrete wavelet transform to obtain the wavelet coefficient difference index. the damage location of the wooden beam was judged according to the peak of the wavelet coefficient difference mutation, and the damage degree of the wooden beam was estimated by fitting the relationship between the wavelet coefficient difference and the damage degree. The wooden beam test verified the index. The results show that the wavelet coefficient difference index can accurately identify the damaged location of wooden beams. The damage degree of wooden beams can be quantitatively estimated by fitting the relationship between the wavelet coefficient difference index and the damage degree. The research results provide a theoretical basis for wooden beam damage identification.

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为解决曲率模态指标对结构小损伤识别的局限性,提出了一种基于曲率模态和小波变换相结合的结构损伤识别方法。以简支木梁为研究对象,采用ANSYS建立木梁损伤前后有限元模型并进行模态分析,对木梁损伤前后的曲率模态进行离散小波变换得到小波系数差指标;根据小波系数差突变峰值判断木梁的损伤位置,通过拟合小波系数差与损伤程度的关系式估算木梁的损伤程度,并由木梁试验对该指标进行了验证。结果表明:小波系数差指标可以准确识别木梁的损伤位置,通过拟合小波系数差指标与损伤程度的关系式来定量估算木梁的损伤程度。该研究成果为木梁损伤识别提供了理论依据。

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孟昭博(1977—),男,教授,博士,主要从事古建筑保护及健康监测研究。E-mail:
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任现才(1996—),男,硕士研究生,主要从事古建筑保护研究。E-mail:

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任现才(1996—),男,硕士研究生,主要从事古建筑保护研究。E-mail:

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Comparison of various structural damage identification methods using vibration response[J]. Journal of Vibration Engineering, 2020, 33(4): 724-733. 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Material parameters of wooden beam

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参数弹性模量/MPa泊松比剪切模量/MPa密度/(kg/m3
ELERETμLRμLTμRTGLRGLTGRT
试验数值9752.172058.57452.900.4900.4100.353585.13731.41175.54508
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木梁材料参数

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参数弹性模量/MPa泊松比剪切模量/MPa密度/(kg/m3
ELERETμLRμLTμRTGLRGLTGRT
试验数值9752.172058.57452.900.4900.4100.353585.13731.41175.54508
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Frequency comparison of test wooden beam and finite element model

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阶数有限元模型计算值/Hz试验木梁计算值/Hz误差/%
一阶76.5575.241.74
二阶264.14260.481.41
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试验木梁与有限元模型频率对比

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阶数有限元模型计算值/Hz试验木梁计算值/Hz误差/%
一阶76.5575.241.74
二阶264.14260.481.41
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基于曲率模态和小波变换的木梁损伤识别
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任现才 1 , 孟昭博 1 , 王鑫 2 , 柴山清 1 , 刘玉发 1
地震工程与工程振动 | 2024,44(4): 79-88
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地震工程与工程振动 | 2024, 44(4): 79-88
基于曲率模态和小波变换的木梁损伤识别
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任现才1 , 孟昭博1 , 王鑫2, 柴山清1, 刘玉发1
作者信息
  • 1.聊城大学 建筑工程学院,山东 聊城 252000
  • 2.天水师范学院 土木工程学院,甘肃 天水 741001
  • 任现才(1996—),男,硕士研究生,主要从事古建筑保护研究。E-mail:

通讯作者:

孟昭博(1977—),男,教授,博士,主要从事古建筑保护及健康监测研究。E-mail:
Wooden beam damage identification based on curvature mode and wavelet transform
Xiancai REN1 , Zhaobo MENG1 , Xin WANG2, Shanqing CHAI1, Yufa LIU1
Affiliations
  • 1.School of Architecture and Engineering, Liaocheng University, Liaocheng 252000, China
  • 2.School of Civil Engineering, Tianshui Normal University, Tianshui 741001, China
doi: 10.13197/j.eeed.2024.0408
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为解决曲率模态指标对结构小损伤识别的局限性,提出了一种基于曲率模态和小波变换相结合的结构损伤识别方法。以简支木梁为研究对象,采用ANSYS建立木梁损伤前后有限元模型并进行模态分析,对木梁损伤前后的曲率模态进行离散小波变换得到小波系数差指标;根据小波系数差突变峰值判断木梁的损伤位置,通过拟合小波系数差与损伤程度的关系式估算木梁的损伤程度,并由木梁试验对该指标进行了验证。结果表明:小波系数差指标可以准确识别木梁的损伤位置,通过拟合小波系数差指标与损伤程度的关系式来定量估算木梁的损伤程度。该研究成果为木梁损伤识别提供了理论依据。

曲率模态  /  损伤识别  /  小波系数差  /  木梁

To address the limitations of curvature mode indicators in identifying minor structural damage, a method for structural damage identification that combines curvature mode and wavelet transform has been proposed. In this paper, ANSYS was used to establish a finite element model of the wooden beam before and after the damage and carry out modal analysis, and the curvature modes of the wooden beam before and after the damage was subjected to discrete wavelet transform to obtain the wavelet coefficient difference index. the damage location of the wooden beam was judged according to the peak of the wavelet coefficient difference mutation, and the damage degree of the wooden beam was estimated by fitting the relationship between the wavelet coefficient difference and the damage degree. The wooden beam test verified the index. The results show that the wavelet coefficient difference index can accurately identify the damaged location of wooden beams. The damage degree of wooden beams can be quantitatively estimated by fitting the relationship between the wavelet coefficient difference index and the damage degree. The research results provide a theoretical basis for wooden beam damage identification.

curvature mode  /  damage identification  /  wavelet coefficient difference  /  wooden beam
任现才, 孟昭博, 王鑫, 柴山清, 刘玉发. 基于曲率模态和小波变换的木梁损伤识别. 地震工程与工程振动, 2024 , 44 (4) : 79 -88 . DOI: 10.13197/j.eeed.2024.0408
Xiancai REN, Zhaobo MENG, Xin WANG, Shanqing CHAI, Yufa LIU. Wooden beam damage identification based on curvature mode and wavelet transform[J]. Earthquake Engineering and Engineering Dynamics, 2024 , 44 (4) : 79 -88 . DOI: 10.13197/j.eeed.2024.0408
木梁作为古建筑木结构的主要承重构件,在环境条件、突发灾害和人为破坏等因素的影响下,木梁容易产生破坏,从而影响古建筑木结构的安全性、适用性和耐久性,严重时会导致整个木结构倒塌。因此,对木梁结构损伤识别的研究具有重要意义。
在结构损伤识别中,首先要解决损伤时间、空间位置和损伤等级,应对诸多损伤识别方法进行研究[1-2]。结构损伤导致物理参数的改变,从而使结构的模态参数改变,因此,在损伤前后通过模态参数的变化识别损伤的位置和严重程度[3]。徐华东等[4]采用低阶曲率模态作为损伤识别指标,对木梁孔洞不同损伤位置、程度及数量进行识别,结果表明该损伤指标对木梁有较好的识别效果。HE等[5]以悬臂梁为例,利用有限元模拟和试验验证了曲率模态差指标能判断结构的损伤位置和损伤程度。梁栋等[6]通过数值仿真和试验验证了高斯曲率模态相关系数法有效定位桥梁支座的损伤位置。XIANG等[7]提出了基于曲率模态效用信息熵作为损伤识别指标,通过简支梁数值仿真和试验验证了该指标的有效性。任现才等[8]对木梁进行数值分析,研究了固有频率、曲率模态和曲率模态差3种指标对木梁损伤的敏感性,采用一阶曲率模态差指标研究了噪声污染和网格疏密对其识别精度的影响。然而已有研究学者发现曲率模态指标对小损伤识别效果不明显[9]
小波变换具有时域和频域对突变信号进行局部放大的特点,可识别结构发生微小损伤的位置和程度。孙增寿等[10]采用小波变换方法对损伤前后的曲率模式进行连续小波分析,建立了损伤前后小波系数残差指标判别了简支梁桥损伤部位及程度。宋子收等[11]利用bior6.8小波对结构损伤前后的曲率模态进行离散小波变换,采用高阶系数之差作为结构损伤的判别指标,通过两跨连续梁的数值模型进行结构的损伤定位研究。王鑫等[12]将小波包能谱法应用于西安钟楼木结构的损伤识别中,结果表明该方法能很好地判断结构的损伤位置。BAO等[13]以结构损伤前后曲率模态为基础,得到小波系数差指标,通过对简支梁的有限元模拟和试验验证,表明该指标能准确地判别结构的损伤部位和损伤程度。
综上所述,国内外学者对梁进行了大量研究工作,但对单个木梁的损伤识别研究较少。本文以简支木梁为研究对象,提出了一种基于曲率模态和小波变换的木梁损伤识别方法。该方法根据小波系数差指标的突变峰值判断木梁的损伤位置,通过拟合小波系数差指标与损伤程度的关系式估算木梁的损伤程度。
根据材料力学理论,梁的弯曲静力表达式为
式中:qx)为梁x截面处的曲率函数;ρx)为梁x截面处的曲率半径;Mx)为梁x截面处的弯矩;EIx)为梁x截面处的抗弯刚度。
依据材料力学理论,梁的任意截面x处曲率函数表达式为
式中:φ″ix)为第i阶曲率模态;qit)为模态坐标。
由式(1)、式(2)可知,结构损伤导致刚度EIx)降低,从而导致曲率模态振型φ″ix)增加。因此,可利用曲率模态振型的突变对结构进行损伤诊断。
为得到结构损伤前后的曲率模态,采用基于位移模态的中心差分方法进行计算[14]。在已知等间距离散单元节点的位移模态与振型的前提下,将曲率模态近似表示为[15]
式中:ϕij)为结构第i阶模态在j节点处的振型值;u、d分别为无损和有损状态;l为相邻节点的距离。
对于任意函数ft)∈L2R)的连续小波变换为[16]
式中:Wfab)为小波系数;ψx)为小波函数;ψx)为ψx)的共轭复数;ab分别为尺度因子和平移因子。
对连续小波进行离散化,其二进制小波变换表示为
b = k2j时,上式为离散小波变换。
选用bior6.8小波对损伤前后曲率模态进行3层离散小波分析,获得小波系数后作差得到小波系数差:
式中:DWfij为结构损伤前后第j阶曲率模态下i节点处的小波系数差;分别为损伤前后第j阶曲率模态下i节点处的小波系数。
1)对木梁进行模态分析,得到损伤前后的一阶曲率模态。
2)选用bior6.8小波对损伤前后的一阶曲率模态进行3层离散小波变换,获得高频小波系数后作差,得到小波系数差指标。
3)根据小波系数差指标的突变峰值进行损伤定位,通过拟合小波系数差指标与损伤程度的关系式来估算木梁的损伤程度。
以简支木梁为例,梁长2200 mm,设计矩形截面木梁,梁宽160 mm,高200 mm。材料为杨木,对同一批杨木木梁进行木材材性试验,所有试验均按国家标准[17-18]进行采集、制作和试验,木梁材性试验结果如表1所示。
本文通过ANSYS有限元软件中的Solid185单元建立木梁构件的三维实体模型,单元尺寸为40 mm,木梁有限元模型如图1所示。
假定结构的损伤由截面高度减小引起,在有限元中通过减小单元截面尺寸来模拟损伤:在木梁底部沿着梁宽,建立长度为160 mm,宽度为40 mm,深度分别为2、5、10、20、30、40 mm的矩形槽体,通过布尔运算中体体相减的命令得到不同损伤工况下的木梁有限元模型。损伤程度S为矩形槽深度he与梁高度h之比[19],即S =he/h,损伤程度为1.0%、2.5%、5.0%、10%、15%、20%。损伤工况分为单处位置损伤和两处位置损伤,其中单处位置损伤在520~560 mm处,两处位置损伤在520~560 mm和1040~1080 mm处。
由于结构高阶模态不易实测到,因此以木梁的一阶位移阵型为原始数据,对其进行后续的损伤识别研究[20]。考虑到试验测点布置在木梁顶面中轴线上,分别提取不同工况木梁中轴线位置层面的中间顶面一条线上56个节点对应的位移振型数据值,模型中节点的间距为40 mm。根据节点与木梁模型对应的坐标关系,将位移振型转换至二维平面进行分析,对提取的一阶位移振型进行了振型最大幅值归一化处理,方便后续分析。将归一化后的一阶位移振型按式(3)和式(4)计算出各工况的一阶曲率模态,图2为单处损伤一阶曲率模态图。
图2可知,当损伤程度大于5%时,曲率模态在损伤位置产生了突变,可通过突变峰值来识别木梁损伤位置;当损伤程度小于5%时,曲率模态在损伤位置处突变不显著,很难进行损伤定位识别,表明该指标在结构小损伤情况下不敏感。因此对木梁一阶曲率模态数据采用bior6.8小波进行3层离散小波变换,求出高频小波系数后作差,得到单处位置损伤各工况下的小波系数差如图3所示。由于损伤位置位于两节点之间,小波系数差指标是取两突变节点中的极大值,因此小波系数差图中突变点的峰值位于损伤单元的两节点之一时,表明这一点附近存在损伤。
图3可知,采用小波系数差可以对曲率模态指标中微小突变的信号进行放大,同时有效减少了相邻单元的影响,识别效果更显著。在损伤位置处,小波系数差有显著的突变峰值,且小波系数差的峰值随着损伤程度的增大而增大。
为了验证小波系数差对两处位置损伤识别的敏感性,设定了木梁在520~560 mm和1040~1080 mm位置处同时存在损伤的工况。图4为两处位置损伤一阶曲率模态图。由图可知,与单处位置损伤结果一致,该指标在结构小损伤情况下不敏感,无法识别木梁损伤位置。因此对木梁一阶曲率模态数据采用bior6.8小波进行3层离散小波变换,求出高频小波系数后作差,得到两处位置损伤不同损伤程度的小波系数差如图5所示。
图5可知,小波系数差指标在两处位置损伤处都有较大的突变,在小损伤的情况下,仍能准确地判断出木梁结构的损伤位置,这表明小波系数差指标比曲率模态指标在木梁小损伤的定位效果更明显,而且小波系数差指标的峰值随着损伤程度增大而增大。
通过对木梁单处损伤和两处损伤定位发现,小波系数差随着损伤程度的增加而增加,通过拟合损伤位置处小波系数差指标与损伤程度的关系式来估算木梁的损伤程度。
对于单处位置损伤,通过ANSYS模拟了木梁在520~560 mm位置处30%的损伤程度。因为小波系数差指标为负值,为了便于分析,对其进行取绝对值。基于最小二乘法原理,利用Origin软件对不同工况下小波系数差指标与损伤程度的关系进行了3次多项式拟合,损伤拟合曲线如图6所示。
图6可知,单处损伤位置处(520~560 mm)小波系数差指标与损伤程度的关系为
式中:x为损伤程度;y为小波系数差损伤指标。
对木梁单处损伤520~560 mm位置处的损伤深度进行50 mm的模拟(即损伤程度为25%)来验证拟合公式的适用性。
图7给出了木梁在单处损伤520~560 mm位置时损伤程度25%的小波系数差。由图7可知,在520~560 mm位置处小波系数差的绝对值为0.83026,将小波系数差的绝对值代入式(8),利用MATLAB求解得到在520~560 mm位置处的损伤程度为24.63%,仅有1.76%的误差。因此,可以通过式(8)估算木梁的损伤程度。
对于两处损伤,通过ANSYS模拟了木梁在520~560 mm和1040~1080 mm位置处30%的损伤程度。采用上述相同的方法,计算并绘制出两处位置损伤的损伤拟合曲线,如图8所示。
图8可知,两处损伤处小波系数差指标与损伤程度的关系为
式中:x为损伤程度;y1为520~560 mm位置处小波系数差损伤指标;y2为1040~1080 mm位置处小波系数差损伤指标。
对木梁两处损伤520~560 mm和1040~1080 mm位置处的损伤深度进行50 mm的模拟(损伤程度为25%)来验证拟合公式的适用性。图9给出了木梁在两处损伤520~560 mm和1040~1080 mm位置时损伤程度25%的小波系数差。由图可知,在520~560 mm和1040~1 080 mm位置处小波系数差的绝对值为0.59787和0.83205,将两处损伤位置处的小波系数差的绝对值代入式(9)和式(10),利用MATLAB求解得到在520~560 mm位置处的损伤程度为24.39%,仅有2.44%的误差;在1 040~1080 mm位置处的损伤程度为24.61%,仅有1.56%的误差。因此可通过式(9)和式(10)估算木梁的损伤程度。
为验证该方法的可行性,试验采用与数值模拟材质和尺寸相同的木梁为研究对象。木梁共划分20份,每份110 mm,试验通过改变木梁截面尺寸来模拟损伤,即:在木梁底部沿着梁宽,人工用电刨机开出长度为160 mm,宽度为40 mm,深度分别为2、5、10、20、30、40 mm的矩形槽,如图10所示。损伤程度S定义为矩形槽深度he与梁高度h之比[18],即S =he/h,损伤程度为1.0%、2.5%、5.0%、10%、15%、20%。损伤工况分为单处位置损伤(工况1~工况6)和两处位置损伤(工况7~工况12),其中单处位置损伤在480~520 mm(5号单元),两处位置损伤在480~520 mm和1040~1080 mm(5号单元和10号单元)。
采取单点激励与多点输出对木梁进行模态试验。使用力锤对木梁预先设置的参考点锤击,通过北京东方振动和噪声技术研究所的多个INV9822型加速度传感器分批采集结构的响应。在木梁净跨内平均布设19个加速度传感器,将磁力座用502胶粘贴到木梁顶面,在磁力座上安装加速度传感器。使用冲击力锤对8#加速度传感器测点处敲击3次,用慧系列多功能数据采集分析仪(型号INV306N2)及DASP(V11)信号分析软件采集和分析数据,木梁现场测试图和示意图如图11所示。
参照DASP&INV产品操作指南中EMA模态试验流程计算不同工况下木梁的固有频率和振型。表2比较了完好木梁有限元模型前2阶固有频率和试验前2阶固有频率。由表2可知,有限元模型一阶固有频率和试验木梁的一阶固有频率误差为1.74%,随模态阶数的增加而增加,最大值为1.41%,因此有限元模型和木梁试验结果可以互相验证。
采用DASP(V11)信号分析软件提取不同工况下的一阶位移振型,由于在测量过程中存在噪声干扰,采用小波阈值法对实测位移振型数据进行去噪处理,然后对去噪后的位移振型进行最大幅值归一化处理。将处理后的位移振型数据按式(3)~式(8)得到单处位置损伤各工况下的小波系数差如图12所示。由于损伤位置位于两节点之间,小波系数差取两突变节点中的极大值,因此小波系数差图中突变点的峰值位于损伤单元的两节点之一时,表明这一点附近存在损伤。
图12可知,采用小波系数差可有效克服曲率模态对小损伤识别效果不明显的问题,能准确地判断出木梁结构的损伤位置,且小波系数差的峰值随着损伤程度的增大而增大。对于工况1、2、3、4、5、6,木梁损伤位置发生在5号单元内,5号单元两端节点分别距梁端位置为0.44、0.55 m,小波系数差均在0.44 m处出现峰值,表明木梁在5号单元发生损伤。
与单处损伤相同,得到两处损伤不同损伤程度的小波系数差如图13所示。
图13可知,在两处位置损伤情况下,小波系数差指标能准确定位5号单元和10号单元发生损伤。即使在小损伤的情况下,也能确定其损伤位置,表明小波系数差指标在小损伤的定位效果优于曲率模态指标,而且小波系数差指标的峰值随着损伤程度增大而增大。对于工况7、8、9、10、11、12,试验中木梁损伤位置在5号单元和10号单元内,5号单元两端节点分别距梁端为0.44 m和0.55 m,10号单元两端节点分别距梁端为0.99 m和1.10 m,图中横坐标为梁长,而小波系数差指标均在0.44 m和1.10 m处出现峰值,表明木梁在该位置附近出现损伤,结合实际损伤位置,可知木梁在5号单元和10号单元发生损伤。
通过对木梁进行单处位置损伤和两处位置损伤定位发现,小波系数差指标随着损伤程度的增大而增大,因此通过拟合小波系数差指标与损伤程度的关系式来估算木梁的损伤程度。
以单处损伤为例,基于最小二乘法原理,采用Origin软件拟合不同工况下小波系数差与损伤程度的关系曲线,其中拟合多项式次数取3,480~520 mm位置(5号单元)处的损伤拟合曲线如图14所示。对损伤程度1.0%、2.5%、5.0%、10%、20%对应的小波系数差值进行了拟合,15%损伤程度的小波系数差值未参与拟合,目的是让15%损伤程度的小波系数差值作为验证拟合公式的适用性。
图14可知,单处损伤处小波系数差指标与损伤程度的关系为
式中:x为损伤程度;y为480~520 mm位置(5号单元)处小波系数差损伤指标。
为了验证拟合公式的适用性,将480~520 mm位置(5号单元)处的小波系数差的绝对值代入式(11),利用MATLAB求解得到在480~520 mm位置(5号单元)处的损伤程度为14.51%,仅有3.27%的误差;因此可通过式(11)估算木梁的损伤程度。
本文以简支木梁为研究对象,对损伤前后一阶曲率模态进行3层离散小波变换,提出了利用小波系数差损伤指标来识别不同工况下木梁损伤位置和损伤程度,并通过数值仿真和木梁试验验证该方法的有效性,得出以下结论:
1)在单处损伤和两处损伤情况下,小波系数差指标能够准确地识别出木梁结构的损伤位置,通过拟合小波系数差指标与损伤程度的关系式来定量估算木梁的损伤程度。
2)结合简支木梁损伤识别试验结果发现,识别结果与数值仿真结果一致,该损伤指标能够识别出损伤位置,并估算出损伤程度,研究结果为木梁损伤识别研究提供参考。
  • 国家自然科学基金项目(52068063)
  • 山东省自然科学基金面上项目(ZR2020ME240)
  • 甘肃省自然科学基金项目(21JR1RE286)
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2024年第44卷第4期
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doi: 10.13197/j.eeed.2024.0408
  • 接收时间:2023-04-05
  • 首发时间:2026-03-30
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  • 收稿日期:2023-04-05
  • 修回日期:2023-05-29
基金
国家自然科学基金项目(52068063)
山东省自然科学基金面上项目(ZR2020ME240)
甘肃省自然科学基金项目(21JR1RE286)
作者信息
    1.聊城大学 建筑工程学院,山东 聊城 252000
    2.天水师范学院 土木工程学院,甘肃 天水 741001

通讯作者:

孟昭博(1977—),男,教授,博士,主要从事古建筑保护及健康监测研究。E-mail:
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2种不同金属材料的力学参数

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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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