Article(id=1222495714660307489, tenantId=1146029695717560320, journalId=1149653034449285133, issueId=1222495713427186326, articleNumber=null, orderNo=null, doi=10.16790/j.cnki.1009-9239.im.2021.04.017, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1593964800000, receivedDateStr=2020-07-06, revisedDate=1598198400000, revisedDateStr=2020-08-24, acceptedDate=null, acceptedDateStr=null, onlineDate=1769395291246, onlineDateStr=2026-01-26, pubDate=1618848000000, pubDateStr=2021-04-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1769395291246, onlineIssueDateStr=2026-01-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1769395291246, creator=13041195026, updateTime=1769395291246, updator=13041195026, issue=Issue{id=1222495713427186326, tenantId=1146029695717560320, journalId=1149653034449285133, year='2021', volume='54', issue='4', pageStart='1', pageEnd='108', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1769395290953, creator=13041195026, updateTime=1770971792201, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1229108038972534891, tenantId=1146029695717560320, journalId=1149653034449285133, issueId=1222495713427186326, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1229108038972534892, tenantId=1146029695717560320, journalId=1149653034449285133, issueId=1222495713427186326, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=102, endPage=108, ext={EN=ArticleExt(id=1222495715432059427, articleId=1222495714660307489, tenantId=1146029695717560320, journalId=1149653034449285133, language=EN, title=Research on Ultrasonic Testing of Internal Defects in Silicone Rubber Materials for Cable Joints, columnId=1192878364340924664, journalTitle=Insulating Materials, columnName=Test and Analysis, runingTitle=null, highlight=null, articleAbstract=

In the actual manufacturing and field installation, defects such as air, metal impurities, and uneven distribution are easily introduced into the silicone rubber insulation layer of cable joint, which endangers the safe operation of power grid system. At present, the detection of power equipment defects are mostly destructive tests, and the experimental results can only reflect the overall situation of equipment. As a non-destructive testing technology, ultrasonic testing can accurately locate and image defects inside the material, and reflect the changes of local performance inside the device. In this study, a set of ultrasonic testing platform were independently designed and built, and ultrasonic testing was conducted on the artificial silicone rubber samples with different defects. The results show that for flexible materials such as silicone rubber, ultrasonic testing can better image the bubbles, air gaps, and steel needle defects in the sample. Compared with similar X-ray testing, ultrasonic testing has an obvious amplification on the tiny bubbles defects. In addition, the ultrasonic testing technology can reflect the change of stress and density inside the material, and can accurately locate the specific depth of the defect according to the ultrasonic echo. This technology has broad application prospects in the location identification and online detection of internal defects in the silicone rubber insulation layer of cable joints.

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在实际生产制造与现场安装过程中,电缆接头硅橡胶绝缘层内极易引入空气、金属杂质与分布不均等缺陷,危害电网系统的安全运行。目前,对于电力设备缺陷的检测多为破坏性试验,且试验结果仅能反映设备的整体情况。超声检测作为一种无损检测技术,能够准确对材料内部的缺陷进行定位与成像,反映设备内部局部性能的变化。本研究自主设计搭建了一套超声检测平台,并对人工制作的含有不同缺陷的硅橡胶试样进行了超声检测。结果表明:对于硅橡胶类柔性材料,超声检测能够较好地对试样内的气泡、气隙与钢针等缺陷进行成像,且相较于X射线检测,超声检测对微小气泡缺陷有明显的放大作用。此外,超声检测技术能够反映出材料内部的应力与密度变化,且根据超声回波能够准确定位缺陷的具体深度。该技术在电缆接头硅橡胶绝缘层内部缺陷的定位识别与在线检测方面有广阔的应用前景。

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金海云(1971-),男(汉族),陕西西安人,教授,主要从事绝缘结构、电气材料、电介质物理和超疏水材料方面的研究。
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王若丞(1996-),男(汉族),江苏连云港人,硕士生,主要从事高电压与绝缘技术技术、高压电缆和无损检测的研究。

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王若丞(1996-),男(汉族),江苏连云港人,硕士生,主要从事高电压与绝缘技术技术、高压电缆和无损检测的研究。

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王若丞(1996-),男(汉族),江苏连云港人,硕士生,主要从事高电压与绝缘技术技术、高压电缆和无损检测的研究。

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电缆接头硅橡胶材料内部缺陷的超声检测研究
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王若丞 , 康洪玮 , 贺云逸 , 王韦玉 , 孔波 , 金海云
绝缘材料 | 测试与分析 2021,54(4): 102-108
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绝缘材料 | 测试与分析 2021, 54(4): 102-108
电缆接头硅橡胶材料内部缺陷的超声检测研究
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王若丞, 康洪玮, 贺云逸, 王韦玉, 孔波, 金海云
作者信息
  • 西安交通大学 电力设备电气绝缘国家重点实验室,陕西 西安 710049
  • 王若丞(1996-),男(汉族),江苏连云港人,硕士生,主要从事高电压与绝缘技术技术、高压电缆和无损检测的研究。

通讯作者:

金海云(1971-),男(汉族),陕西西安人,教授,主要从事绝缘结构、电气材料、电介质物理和超疏水材料方面的研究。
Research on Ultrasonic Testing of Internal Defects in Silicone Rubber Materials for Cable Joints
Ruocheng WANG, Hongwei KANG, Yunyi HE, Weiyu WANG, Bo KONG, Haiyun JIN
Affiliations
  • State Key Laboratory of Electrical Insulation and Power Equipment, Xi'an Jiaotong University, Xi'an 710049, China
出版时间: 2021-04-20 doi: 10.16790/j.cnki.1009-9239.im.2021.04.017
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在实际生产制造与现场安装过程中,电缆接头硅橡胶绝缘层内极易引入空气、金属杂质与分布不均等缺陷,危害电网系统的安全运行。目前,对于电力设备缺陷的检测多为破坏性试验,且试验结果仅能反映设备的整体情况。超声检测作为一种无损检测技术,能够准确对材料内部的缺陷进行定位与成像,反映设备内部局部性能的变化。本研究自主设计搭建了一套超声检测平台,并对人工制作的含有不同缺陷的硅橡胶试样进行了超声检测。结果表明:对于硅橡胶类柔性材料,超声检测能够较好地对试样内的气泡、气隙与钢针等缺陷进行成像,且相较于X射线检测,超声检测对微小气泡缺陷有明显的放大作用。此外,超声检测技术能够反映出材料内部的应力与密度变化,且根据超声回波能够准确定位缺陷的具体深度。该技术在电缆接头硅橡胶绝缘层内部缺陷的定位识别与在线检测方面有广阔的应用前景。

超声检测  /  硅橡胶  /  缺陷  /  成像方法

In the actual manufacturing and field installation, defects such as air, metal impurities, and uneven distribution are easily introduced into the silicone rubber insulation layer of cable joint, which endangers the safe operation of power grid system. At present, the detection of power equipment defects are mostly destructive tests, and the experimental results can only reflect the overall situation of equipment. As a non-destructive testing technology, ultrasonic testing can accurately locate and image defects inside the material, and reflect the changes of local performance inside the device. In this study, a set of ultrasonic testing platform were independently designed and built, and ultrasonic testing was conducted on the artificial silicone rubber samples with different defects. The results show that for flexible materials such as silicone rubber, ultrasonic testing can better image the bubbles, air gaps, and steel needle defects in the sample. Compared with similar X-ray testing, ultrasonic testing has an obvious amplification on the tiny bubbles defects. In addition, the ultrasonic testing technology can reflect the change of stress and density inside the material, and can accurately locate the specific depth of the defect according to the ultrasonic echo. This technology has broad application prospects in the location identification and online detection of internal defects in the silicone rubber insulation layer of cable joints.

ultrasonic testing  /  silicone rubber  /  defects  /  imaging method
王若丞, 康洪玮, 贺云逸, 王韦玉, 孔波, 金海云. 电缆接头硅橡胶材料内部缺陷的超声检测研究. 绝缘材料, 2021 , 54 (4) : 102 -108 . DOI: 10.16790/j.cnki.1009-9239.im.2021.04.017
Ruocheng WANG, Hongwei KANG, Yunyi HE, Weiyu WANG, Bo KONG, Haiyun JIN. Research on Ultrasonic Testing of Internal Defects in Silicone Rubber Materials for Cable Joints[J]. Insulating Materials, 2021 , 54 (4) : 102 -108 . DOI: 10.16790/j.cnki.1009-9239.im.2021.04.017
随着城市规模不断扩大,国民经济不断发展,我国高压电缆的配置与使用范围愈为广泛,其中电力电缆接头起到连接与过渡的重要作用。硅橡胶广泛应用于高压电缆中间接头,作为主绝缘材料,具有高弹性、耐高低温性能好、电气性能优良等特点。但是由于电缆系统结构紧凑、现场安装工艺复杂、易引入缺陷等原因,电缆附件的故障率远高于电缆本体[1]。国家电网公司对电缆故障原因的统计表明,若不计外力破坏,由电缆附件绝缘破坏所引发的电缆线路故障占比高达70%[2-3]。由于长期的老化、不规范生产和现场安装,电缆接头绝缘层内部极易引入气泡、分层、金属杂质与分布不均等局部性缺陷。目前对电力设备的状态检测多集中于介电常数、局部放电、击穿电压、拉伸强度等传统参数试验,这些试验结果仅能反映材料的整体劣化程度,且需对原始设备进行破坏性取样。超声检测作为一种无损检测技术,具有成本低、使用方便、便于现场检测等优点,能够实现对材料内部缺陷的定位与成像,反映材料局部性能的变化,因而在电缆接头硅橡胶绝缘层内部缺陷的定位识别与在线检测方面有广阔的应用前景。
近年来,超声检测技术凭其各项优点在国内外电力设备运行状态检测中得到广泛的研究与应用。郝艳捧等[4-5]搭建了大电机定子线棒低频超声检测系统,研究了定子线棒中超声参数与老化状态的关系;H UENO等[6]利用环氧树脂的Landolt环法对超声检测系统的分辨率进行了细致的研究;谢从珍等[7]利用射频超声检波方式,根据回波幅值评估了复合绝缘子的内部缺陷;申巍等[8]使用5MH窄脉冲聚焦超声探头对环氧树脂气隙的相位、频率特征进行了提取;SONG W J等[9]通过超声A扫波形,对自制断路器绝缘拉杆缺陷试样进行了时域与频域的特征分析。
超声检测技术目前多应用于钢铁、铝合金、环氧树脂等刚性材料中,与金属以及多数复合材料不同,硅橡胶属于柔性材料,材料中的声衰减严重,超声波在其中的传播特性尚不明晰。因此有必要对超声波在硅橡胶内部的传播特性进行研究,选择适用于电缆接头硅橡胶绝缘层的超声检测方法,并对含有缺陷的样品进行成像检测,研究硅橡胶材料缺陷的超声特性。
超声波与光波相似,可以反射、折射、扩散,且能够被遮挡,因此可以用来检测设备内部的微小缺陷。脉冲回波法是目前最常用的超声检测方法。介质的特性声阻抗,即介质密度与声速的乘积,是重要的声学特性,如式(1)所示。声信号在介质中传播,当到达两种不同声阻抗介质的交界面时,一部分声波会穿过界面以一定的折射角进入另一种介质,而另一部分声波则会在界面处发生反射。声阻抗的变化将导致部分超声信号发生反射,因此超声探头可以依次接收到不同缺陷(如气泡、金属杂质或局部不均匀)界面反射的超声回波。若工件中存在缺陷,则超声表面波T与底面波B之间会出现缺陷波F,如图1所示。根据缺陷波在时间轴上的声程和幅值,可以判断缺陷的深度和大小。
Z=ρc
式(1)中:Z为声阻抗;ρ为材料密度;c为超声在材料中的传播速度。
若将超声探头按照一定的扫查轨迹移动,记录每个检测点缺陷回波F的位置与幅值信息作为特征值,并在扫查结束后通过软件处理转换成颜色信息,最终以图像的形式显示出扫查试样的内部情况,如图2所示。
对电缆接头硅橡胶材料内部缺陷超声检测系统进行模块化设计,搭建了超声检测平台。系统主要分为超声信号收发模块、扫查路径控制模块和检测系统软件3个部分,并通过上位机发送命令控制整个系统的超声波收发、探头定位及信号处理,系统整体结构如图3所示。
超声在空气中的衰减十分严重,因此通常的超声测试都需要使用耦合剂,超声检测探头的布置根据耦合方式的不同分为接触法与浸泡法。采用接触法检测时需将探头紧压在试样表面,通常以凡士林、真空硅脂等作为耦合剂。而硅橡胶作为柔性材料,接触压力难以控制,从而影响到探头与试样表面的夹角与耦合剂厚度,导致检测重复性差。水浸法作为一种非接触法,不需要将探头紧压在试样表面,具有低衰减、对探头损耗小、重复性高等优点,因此本研究以蒸馏水为耦合剂,采用水浸法进行超声纵波缺陷检测。
超声信号收发模块的功能是控制探头收发超声信号,并将超声回波模拟信号转换成数字信号。对于同一材料,若超声探头主频率越大,则检测灵敏度越高,但声信号在材料内部的衰减也越严重。为研究不同频率超声纵波在硅橡胶材料中的衰减特性,在室温25℃条件下,分别使用中心频率为1、2.5、5 MHz的超声探头对不同厚度(10、30、50、100 mm)的无缺陷块状硅橡胶试样进行测试,测试时使探头与试样表面距离相同,保证表面波高度一致,测量试样底面波的幅值。超声探头接收的声压与压电效应产生的电压成正比,因此可得出不同频率的超声纵波在各厚度硅橡胶材料内部的衰减特性,如图4所示。根据图4进行综合对比,选用主频率为1 MHz的超声纵波探头进行测试。为了防止信号重建过程中的失真,采样频率必须满足奈奎斯特定律,考虑信号采集与处理效率,最终使用Pico公司的2207B型数字示波器,以125 MS/s的采样频率进行数据采集。
扫查路径控制模块是自动检测系统的基础,用于确保超声波探头按照预定路径移动的同时,在规定的位置收发超声信号。扫描路径和步长会影响超声成像的效率和精度。电缆附件绝缘层内部缺陷的尺寸一般在毫米级,因此当扫查行进步长为微米级时,能够良好地重现缺陷形貌。本系统采用两台步进电机和控制器分别驱动X、Y轴的运动,采用闭环控制,研制出步长最小为2.5 μm的二维扫描装置,控制超声探头以“弓”字形路径进行扫描。
整套系统通过计算机发送命令,控制超声信号收发仪以一定的频率发送和接收超声信号,并将超声探头与双轴扫查系统连接,实现探头的轨迹扫查与定位。超声信号收发仪对收到的回波模拟信号进行放大,传输到与之连接的数字示波器中,并通过计算机处理转换为数字信号,如图5所示。图6为搭建的超声检测平台实物图。
检测系统软件使用C++与MATLAB语言联合编写,软件的系统框架如图7所示。该软件主要实现了系统参数设置、硬件设备控制、超声信号处理、图像显示与数据存储等功能,根据数据分析缺陷回波的特征参数,生成二维彩色图像。
经数字滤波器采集的超声回波信号是带限信号,采样信号的频率上限为70 MHz,远高于所使用的超声波频率。因此,采集到的信号中还含有高次谐波和高频噪声,需要使用数字滤波器对信号进行滤波处理。选用汉宁窗对数据进行加窗,设计了64阶低通滤波器,截止频率为5 MHz,阻带衰减为60 dB,其滤波效果如图8所示。
对超声回波进行FIR滤波后,截取回波信号中表面波与底面波之间的部分,找出幅值绝对值最大的点,记录该点幅值的绝对值A与表面波的时间差Δt,并通过式(2)计算缺陷处的深度d。记录各回波检测点的二维坐标(x,y),以及各点处的幅值特征值A(x,y)和深度特征值d(x,y)。当试样的C扫描完成后,每个检测点(x,y)都能对应一个幅值特征值和深度特征值,构成一个检测点特征值矩阵。按照成像精度p对检测点进行分组,以每组若干个检测点的特征值平均值为一个成像像素点的特征值A′(i,j),形成像素点特征值矩阵,如图9所示。
d=vΔt/2
式(2)中,v为超声在硅橡胶中的传播速度,取1 000 m/s。
检测点矩阵转化为像素矩阵后,取矩阵中的最大值Amax和最小值Amin,并将特征值由小到大分成256个区间,分别对应于整数0~255,通过式(3)即可计算出每个像素点的8 bit灰度值。最后将灰度值转变为RGB值,实现对缺陷成像的彩图映射。
Gray(i,j)=255[A'(i,j)-A'min]A'max-A'min 
式(3)中:Gray(i, j)为像素点(i, j)处的灰度值;A′(i, j)为像素点(i, j)处的幅值特征值;Amin为像素矩阵幅值特征值中的最小值;Amax为像素矩阵幅值特征值中的最大值。
为了验证超声检测系统的检测能力,人工制作了3块尺寸为200 mm×200 mm×30 mm的方形硅橡胶试样,如图10所示,内部分别含有气泡、气隙和钢针缺陷,以模拟电缆接头生产安装时硅橡胶绝缘层内的各种缺陷。
使用模压法制作缺陷试样的过程中,在硅橡胶完全固化成形前,通过针管在指定位置注射定量的空气,并迅速压平表面,从而制得含气泡缺陷试样。气隙与钢针尺寸固定,而气泡形貌不可控,因此在检测气泡试样时,需用X射线检测辅助分析。图11显示了气泡缺陷试样的超声检测与X射线检测结果,检测范围为60 mm×60 mm,超声检测精度为0.1 mm。由图11可见,超声检测硅橡胶试样缺陷的位置与X射线基本吻合,且颜色沿缺陷中心径向逐渐变浅。这是由于气泡缺陷与硅橡胶的界面并不平整,而是一个类球面,如图12所示。当超声信号传递方向与界面切面垂直时,超声探头能够接收到所有在缺陷界面处反射的超声回波,因此回波幅值较大,成像颜色也较深。而当探头逐渐远离气泡缺陷中心点时,超声信号的传递方向不再与界面切面垂直,超声回波不再以原传递方向返回,而是以一定的角度进行反射,所以探头仅能接收到部分回波,波形幅值较小,成像颜色也较浅。
图11还可以看出,超声检测的缺陷尺寸比X射线检测的略大。由于针管注入的高压气泡在材料内部形成了球状高应力场,使得气泡缺陷周围的部分材料出现了应力集中与密度变化,最终改变了缺陷周围硅橡胶声阻抗,从而在超声检测图像上表现出异常。与现有文献中金属、环氧等刚性材料的内部缺陷扫查结果不同,硅橡胶内的高压气泡缺陷附近出现了涟漪状的图像,很好地佐证了气泡对硅橡胶等高弹性材料内部分布的影响。对于一些形状较小、位置靠近或是深处的缺陷,X射线检测图像较为模糊,对这类气泡缺陷难以识别。因此,相较于X射线检测,超声检测不仅能检出硅橡胶试样中的气泡缺陷,且能反映出材料内部均匀程度的变化,对小尺寸气泡缺陷的识别更为突出,实际检出率高于X射线检测。
在硅橡胶试样固化成型前,预先水平埋入薄铁片,即将成型前缓慢将薄铁片从侧边抽出,以制造距上表面25 mm的气隙缺陷。因此气隙缺陷周围的硅橡胶材料较为均匀,几乎不会出现局部的应力集中。埋入试样内的铁片形状为梯形,深度为37.5 mm,宽度为48 mm。超声检测范围为60 mm×60 mm,检测精度为0.1 mm,缺陷的扫查结果如图13所示。从图13可以看出,气隙缺陷的超声检测图像轮廓清晰,且没有出现图11中的涟漪状图像,表明预埋入处理的气隙缺陷周围硅橡胶材料分布较为均匀,声阻抗变化较小。经测量,超声检测出气隙缺陷长底边的边长为49.1 mm,宽度为38.7 mm,略大于埋入薄铁片的实际尺寸。底边相对放大了2.3%,放大长度为1.1 mm;高相对放大了3.2%,放大长度均为1.2 mm。这是由于超声探头存在一定的焦区直径[9],当探头移动到缺陷边缘时,缺陷回波不会立即消失,回波的幅值存在一个渐变的过程,因此对于大面积的气隙缺陷总存在一个约为1 mm的放大。
除缺陷成像分析外,超声检测还可根据缺陷回波的波形图计算缺陷的具体位置。气隙缺陷回波图像如图14所示,根据式(2)计算,气隙缺陷距试样表面约24.6 mm,相对误差仅为1.6%。
在试样侧表面垂直扎入钢针,用以模拟运行安装时电缆接头绝缘层内的金属杂质缺陷。钢针直径为1 mm,埋入长度为30 mm,位置距上表面10 mm。超声检测范围为40 mm×20 mm,检测精度为0.05 mm,扫查结果如图15所示。由于钢针扎入时对周围高弹性硅橡胶材料的挤压,尤其是针尖与钢针侧边的应力最为集中,使得扫查图像呈花瓶状。经测量,扫查图像中缺陷部分长度为30.7 mm,略大于钢针实际埋入深度,相对误差为2.3%。此外,根据钢针缺陷的波形图(如图16所示)计算可得,钢针距试样上表面10.2 mm,相对误差为2%。
为研究硅橡胶内部缺陷的超声特性,自主设计与搭建了一套超声检测平台,并对人工制作的含有不同缺陷的硅橡胶试样进行了超声检测,主要得到如下结论:
(1)超声检测的缺陷图像能够清晰地还原硅橡胶内部气泡缺陷的形貌与位置,相较于X射线检测,尤其是对小气泡有明显的放大作用,使得气泡缺陷更容易检测与识别。超声检测不仅能够检测出硅橡胶内部的气泡缺陷,还可以反映出材料局部的应力与密度变化。
(2)对于大面积的气隙缺陷,超声检测能够良好地还原缺陷形貌,且根据缺陷回波波形计算出气隙缺陷的具体深度,误差仅为1.6%。
(3)对于人工刺入的钢针缺陷,由于钢针穿刺挤压造成硅橡胶局部材料特性变化,使得缺陷扫查的整体形貌呈花瓶状。扫查结果缺陷长度略大于实际埋入长度,相对误差为2.3%,缺陷深度与实际位置相对误差为2%。
(4)超声检测技术作为一种无损检测手段,能够较好地对硅橡胶类柔性材料内部的各种缺陷进行检测识别,有望成为电缆接头绝缘层运行状态的新型检测方法。
  • 国家电公司科技项目(520900180032)
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2021年第54卷第4期
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doi: 10.16790/j.cnki.1009-9239.im.2021.04.017
  • 接收时间:2020-07-06
  • 首发时间:2026-01-26
  • 出版时间:2021-04-20
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  • 收稿日期:2020-07-06
  • 修回日期:2020-08-24
基金
国家电公司科技项目(520900180032)
作者信息
    西安交通大学 电力设备电气绝缘国家重点实验室,陕西 西安 710049

通讯作者:

金海云(1971-),男(汉族),陕西西安人,教授,主要从事绝缘结构、电气材料、电介质物理和超疏水材料方面的研究。
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https://castjournals.cast.org.cn/joweb/jycl/CN/10.16790/j.cnki.1009-9239.im.2021.04.017
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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