Research on Registration Deviation Detection of Printed Glass LED Circuit Board

Tian Xi, Guo-sheng Zhang, Xiaoqiang Liu, Yang Li
{"title":"Research on Registration Deviation Detection of Printed Glass LED Circuit Board","authors":"Tian Xi, Guo-sheng Zhang, Xiaoqiang Liu, Yang Li","doi":"10.12783/dteees/peems2019/33979","DOIUrl":null,"url":null,"abstract":"To improve the registration accuracy, save the printing material, and optimize the printing space on printed glass circuit board for LED, the dual-cameras are introduced to capture the image of screen-printing plate. Considering the configuration of LED circuit, the dual-cameras are separately used to capture two parts of circuit image with 5mm × 4mm scale, which are from whole circuit with 200mm × 100mm scale. In this paper, the bolding pads are considered as the registration mark, the line fitting with global least square method is used to extract the image character points, and the registration deviation are calculated. According to this detection method, the registration printing experience results that the actual registration deviation ( 13μm in x-direction, 14μm in y-direction) satisfy the registration printing requirement of glass circuit board for LED (less than 30μm in x-direction, and less than 24μm in y-direction). Introduction Silver is used as the printing material in the most printed glass circuit boards that is printed by monochrome screen-printing machine in current. In this way, there is an issue that the silver bonding pad is possibly absorbed by the high temperature soldering, and peeled off from the glass substrate. To solve this issue, gold can be used as the bonding pad overprinted on the silver transmission line, because gold cannot be peeled off from sliver substrate by high temperature soldering. To improve the registration accuracy, it’s important to determine the position and shape of the registering mark. The common registering marks, such as the cross-shape mark [1], CMYK mark [2], independent solid circle mark [3] and star-shape mark [4], require to be printed individually, and occupy the printing space. In common, there is only one single camera in the registration system, therefore, it’s difficult to large the captured image scale and improve the registration accuracy at the same time. The Selection of Registering Mark The screen-printing plate for printed glass circuit board is shown in fig. 1, and the registration printing plate is shown in fig. 2. In this paper, to improve the registration accuracy, the dual-cameras with a resolution of 640 × 480, are applied in the experience device. The center distance of two cameras is 170mm. These two cameras are occupied to capture the field in 5mm × 4mm on the plate. Every pixel in this image is actually corresponding to 7.8μm in x-direction, and 8.3μm in y-direction. To save the printing material and optimize the printing space, according to the character of the circuit shape, the bonding pads are selected to be the registering mark, which is shown in fig. 3. In experience, the model of LED chip is ETi-KB358A-BL. According to the datasheet, the distance between each two bonding pads should be large than 240μm. Therefore, the maximum permission registration deviation should be 30μm in x-direction, and 24μm in y-direction. Figure 1. The printed screen plate for printed glass LED circuit board. Figure 2. The registration screen plate for printed glass LED circuit board. Figure 3. The registration mark. The Detection of Registration Deviation Pre-procession for Image Because glass is the rigid material, the substrate and the registering mark cannot be out of shape, and there are 3 steps for pre-procession [5]. And the pre-procession methods for printing screen plate and registration screen plate are same. Step1: grizzled procession [6], as shown in fig. 3-b, which transfers 3-channal colored image into 1-channal gray image. Step2: histogram equalization procession, as shown in fig. 3-c, which enhances the contrast by stretching contrast and increasing the pray difference between foreground and background. Step3: binarization procession, as shown in fig. 3-d, which obtains the binary image. Figure 4. Diagram for image pre-procession. Extraction of the Image Character Points There are 3 steps to extract the image character points. The extraction methods for printing screen plate and registration screen plate are same. Step1: For the data on the row direction in the binary image shown in fig. 5-a, calculating the average coordinate value of pixels with 0 value (black pixels), which mean the coordinate value of the middle points for each horizontal line in binary image. Calculating the absolute error between the column coordinates of all middle points of horizontal line and their average value, according to the threshold value of permission deviation, all the points with deviation larger than threshold value can be ignored. And applying the line fitting with least square method [7], the perpendicular line can be fitted by the left points as shown in fig. 5-b. Step2: For the data on the horizontal direction in the binary image shown in fig. 5-b, using the same method of step1, the horizontal line can be fitted as shown in fig. 5-c. Step3: The junction points of the perpendicular line and horizontal line that are fitted in step1 and step2, are the coordinate value of character points, as shown in fig. 5-d. Figure 5. Diagram of character point extraction procession. Deviation Value Calculating for Registration The coordinate value of character points mentioned above is in the image coordinate system, and the coordinate value of cameras and printing plate is in the world coordinate system. The mapping relationship between image coordinate system and world coordinate system should be determined [8], and then, the actual registration deviation can be calculated. This mapping relationship is shown in Eq. 1: [ i j 1 ] = N [ x y 1 ] (1) In this equation, i and j are image coordinates, x and y are the actual physical coordinates in the relation world coordinate system. Selecting N(N ≥ 4) relation points from image coordinate and world coordinate system, the homography matrix N (3 × 3) can be obtained. According to this homography matrix, the coordinate value of any point in image coordinate system can be transferred into the actual physical coordinate value in the world coordinate system. The coordinates of two character points captured firstly are seemed as the reference coordinates. Comparing the following coordinates value of character points, the deviation on x-direction, y-direction and rotation angle can be calculated. Then, this coordinate deviation can be provided to adjust the actual position of registration plate. Assuming the world coordinate of two firstly captured character points are A(xa , ya), B(xb , yb), and A(xa ′ , ya ′ ), B(xb ′ , yb ′ ) for the following two character points, which is shown in fig. 6. Figure 6. Deviation calculating. The deviation in x-direction, y-direction and rotation can be determined: The deviation on x-direction is ∆x = Δxa+Δxb 2 = |xa−xa ′ |+|xb−xb ′ | 2 (2) The deviation on y-direction is ∆y = Δya+Δyb 2 = |ya−ya ′ |+|yb−yb ′ | 2 (3) The deviation on rotation is Δθ = |θ1 − θ2| = |arctan |yb−ya| |xb−xa| − arctan |yb ′ −ya ′ | |xb ′ −xa ′ | | (4) Detection Experience of Registration The registration deviation detection algorithm [9] is coded on the platform of Visual Studio 2010 and OpenCV 3.0. In the experience, the captured screen plate image [10] is shown in fig. 7. Figure 7. The captured screen plate image. The pixel coordinates of points A, B, C, D are A(271, 394), B(369, 394), C(271, 77), and D(369, 77) separately. The world coordinates (μm) are A(2113.8, 3270.2), B(2878.2, 3270.2), C(2113.8, 639.1), D(2878.2, 639.1). Then, the homography matrix is N = | 0.254719 −0.00179 59.3197 −9.4802e 0.478092 82.8394 6.4975e −9.4398e 1 | This matrix means the mapping relationship between image coordinate system and world coordinate system. The dual-cameras capture two images scaled in 5mm × 4mm, in whole screen plate scaled in 200mm × 100mm. The deviation data experienced are shown in table1. Which indicates the actual average registration deviations are 13μm in x-direction and 14μm in y-direction. It’s satisfied the registration requirements of LED printed glass circuit board. Conclusion In this paper, using dual-cameras to capture the images of circuit, according to the shape character of LED circuit, the ponding pad images are selected as the new registration marks. Based on the experiences, the deviation of plate position is satisfied the requirements of LED printed glass circuit board. Table1. Experience Results [μm]. (xa , ya) (xb , yb) (xa , ya ) (xb , yb ) ∆x ∆y 1 (1026,3476) (4672,827) (1009,3466) (4659,815) 15 11 2 (997,3410) (4630,813) (987,3393) (4614,800) 13 15 3 (1011,3425) (4611,820) (999,3017) (4605,808) 9 10 4 (1048,3380) (4702,832) (1028,3361) (4686,823) 18 14 5 (1031,3496) (4685,845) (1018,3476) (4670,827) 14 19 6 (1005,3368) (4701,859) (990,3361) (4690,848) 13 9 7 (1028,3294) (4659,871) (1017,3287) (4636,854) 17 12 average / / / / 14 13 Acknowledgement This research was financially supported by Beijing Municipal Education Commission science general project (KM201610015001), and BIGC key science research project (Ea201604).","PeriodicalId":11369,"journal":{"name":"DEStech Transactions on Environment, Energy and Earth Science","volume":"20 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DEStech Transactions on Environment, Energy and Earth Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12783/dteees/peems2019/33979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

To improve the registration accuracy, save the printing material, and optimize the printing space on printed glass circuit board for LED, the dual-cameras are introduced to capture the image of screen-printing plate. Considering the configuration of LED circuit, the dual-cameras are separately used to capture two parts of circuit image with 5mm × 4mm scale, which are from whole circuit with 200mm × 100mm scale. In this paper, the bolding pads are considered as the registration mark, the line fitting with global least square method is used to extract the image character points, and the registration deviation are calculated. According to this detection method, the registration printing experience results that the actual registration deviation ( 13μm in x-direction, 14μm in y-direction) satisfy the registration printing requirement of glass circuit board for LED (less than 30μm in x-direction, and less than 24μm in y-direction). Introduction Silver is used as the printing material in the most printed glass circuit boards that is printed by monochrome screen-printing machine in current. In this way, there is an issue that the silver bonding pad is possibly absorbed by the high temperature soldering, and peeled off from the glass substrate. To solve this issue, gold can be used as the bonding pad overprinted on the silver transmission line, because gold cannot be peeled off from sliver substrate by high temperature soldering. To improve the registration accuracy, it’s important to determine the position and shape of the registering mark. The common registering marks, such as the cross-shape mark [1], CMYK mark [2], independent solid circle mark [3] and star-shape mark [4], require to be printed individually, and occupy the printing space. In common, there is only one single camera in the registration system, therefore, it’s difficult to large the captured image scale and improve the registration accuracy at the same time. The Selection of Registering Mark The screen-printing plate for printed glass circuit board is shown in fig. 1, and the registration printing plate is shown in fig. 2. In this paper, to improve the registration accuracy, the dual-cameras with a resolution of 640 × 480, are applied in the experience device. The center distance of two cameras is 170mm. These two cameras are occupied to capture the field in 5mm × 4mm on the plate. Every pixel in this image is actually corresponding to 7.8μm in x-direction, and 8.3μm in y-direction. To save the printing material and optimize the printing space, according to the character of the circuit shape, the bonding pads are selected to be the registering mark, which is shown in fig. 3. In experience, the model of LED chip is ETi-KB358A-BL. According to the datasheet, the distance between each two bonding pads should be large than 240μm. Therefore, the maximum permission registration deviation should be 30μm in x-direction, and 24μm in y-direction. Figure 1. The printed screen plate for printed glass LED circuit board. Figure 2. The registration screen plate for printed glass LED circuit board. Figure 3. The registration mark. The Detection of Registration Deviation Pre-procession for Image Because glass is the rigid material, the substrate and the registering mark cannot be out of shape, and there are 3 steps for pre-procession [5]. And the pre-procession methods for printing screen plate and registration screen plate are same. Step1: grizzled procession [6], as shown in fig. 3-b, which transfers 3-channal colored image into 1-channal gray image. Step2: histogram equalization procession, as shown in fig. 3-c, which enhances the contrast by stretching contrast and increasing the pray difference between foreground and background. Step3: binarization procession, as shown in fig. 3-d, which obtains the binary image. Figure 4. Diagram for image pre-procession. Extraction of the Image Character Points There are 3 steps to extract the image character points. The extraction methods for printing screen plate and registration screen plate are same. Step1: For the data on the row direction in the binary image shown in fig. 5-a, calculating the average coordinate value of pixels with 0 value (black pixels), which mean the coordinate value of the middle points for each horizontal line in binary image. Calculating the absolute error between the column coordinates of all middle points of horizontal line and their average value, according to the threshold value of permission deviation, all the points with deviation larger than threshold value can be ignored. And applying the line fitting with least square method [7], the perpendicular line can be fitted by the left points as shown in fig. 5-b. Step2: For the data on the horizontal direction in the binary image shown in fig. 5-b, using the same method of step1, the horizontal line can be fitted as shown in fig. 5-c. Step3: The junction points of the perpendicular line and horizontal line that are fitted in step1 and step2, are the coordinate value of character points, as shown in fig. 5-d. Figure 5. Diagram of character point extraction procession. Deviation Value Calculating for Registration The coordinate value of character points mentioned above is in the image coordinate system, and the coordinate value of cameras and printing plate is in the world coordinate system. The mapping relationship between image coordinate system and world coordinate system should be determined [8], and then, the actual registration deviation can be calculated. This mapping relationship is shown in Eq. 1: [ i j 1 ] = N [ x y 1 ] (1) In this equation, i and j are image coordinates, x and y are the actual physical coordinates in the relation world coordinate system. Selecting N(N ≥ 4) relation points from image coordinate and world coordinate system, the homography matrix N (3 × 3) can be obtained. According to this homography matrix, the coordinate value of any point in image coordinate system can be transferred into the actual physical coordinate value in the world coordinate system. The coordinates of two character points captured firstly are seemed as the reference coordinates. Comparing the following coordinates value of character points, the deviation on x-direction, y-direction and rotation angle can be calculated. Then, this coordinate deviation can be provided to adjust the actual position of registration plate. Assuming the world coordinate of two firstly captured character points are A(xa , ya), B(xb , yb), and A(xa ′ , ya ′ ), B(xb ′ , yb ′ ) for the following two character points, which is shown in fig. 6. Figure 6. Deviation calculating. The deviation in x-direction, y-direction and rotation can be determined: The deviation on x-direction is ∆x = Δxa+Δxb 2 = |xa−xa ′ |+|xb−xb ′ | 2 (2) The deviation on y-direction is ∆y = Δya+Δyb 2 = |ya−ya ′ |+|yb−yb ′ | 2 (3) The deviation on rotation is Δθ = |θ1 − θ2| = |arctan |yb−ya| |xb−xa| − arctan |yb ′ −ya ′ | |xb ′ −xa ′ | | (4) Detection Experience of Registration The registration deviation detection algorithm [9] is coded on the platform of Visual Studio 2010 and OpenCV 3.0. In the experience, the captured screen plate image [10] is shown in fig. 7. Figure 7. The captured screen plate image. The pixel coordinates of points A, B, C, D are A(271, 394), B(369, 394), C(271, 77), and D(369, 77) separately. The world coordinates (μm) are A(2113.8, 3270.2), B(2878.2, 3270.2), C(2113.8, 639.1), D(2878.2, 639.1). Then, the homography matrix is N = | 0.254719 −0.00179 59.3197 −9.4802e 0.478092 82.8394 6.4975e −9.4398e 1 | This matrix means the mapping relationship between image coordinate system and world coordinate system. The dual-cameras capture two images scaled in 5mm × 4mm, in whole screen plate scaled in 200mm × 100mm. The deviation data experienced are shown in table1. Which indicates the actual average registration deviations are 13μm in x-direction and 14μm in y-direction. It’s satisfied the registration requirements of LED printed glass circuit board. Conclusion In this paper, using dual-cameras to capture the images of circuit, according to the shape character of LED circuit, the ponding pad images are selected as the new registration marks. Based on the experiences, the deviation of plate position is satisfied the requirements of LED printed glass circuit board. Table1. Experience Results [μm]. (xa , ya) (xb , yb) (xa , ya ) (xb , yb ) ∆x ∆y 1 (1026,3476) (4672,827) (1009,3466) (4659,815) 15 11 2 (997,3410) (4630,813) (987,3393) (4614,800) 13 15 3 (1011,3425) (4611,820) (999,3017) (4605,808) 9 10 4 (1048,3380) (4702,832) (1028,3361) (4686,823) 18 14 5 (1031,3496) (4685,845) (1018,3476) (4670,827) 14 19 6 (1005,3368) (4701,859) (990,3361) (4690,848) 13 9 7 (1028,3294) (4659,871) (1017,3287) (4636,854) 17 12 average / / / / 14 13 Acknowledgement This research was financially supported by Beijing Municipal Education Commission science general project (KM201610015001), and BIGC key science research project (Ea201604).
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印刷玻璃LED电路板配准偏差检测研究
为了提高LED玻璃印刷电路板的配准精度,节省印刷材料,优化印刷空间,采用双摄像头对丝网印版进行图像采集。考虑到LED电路的配置,采用双摄像头分别采集两部分规模为5mm × 4mm的电路图像,分别来自规模为200mm × 100mm的整个电路。本文以抱垫为配准标记,采用全局最小二乘法进行直线拟合提取图像特征点,并计算配准偏差。根据该检测方法,配准印刷经验表明,实际配准偏差(x方向13μm, y方向14μm)满足LED玻璃电路板的配准印刷要求(x方向小于30μm, y方向小于24μm)。目前大多数单色丝网印刷机印刷的玻璃电路板都采用银作为印刷材料。这样,就有一个问题,银键合垫可能被高温焊接吸收,并从玻璃基板上剥离。为了解决这个问题,可以使用金作为覆印在银传输线上的键合垫,因为金不能通过高温焊接从银衬底上剥离。为了提高配准精度,必须确定配准标记的位置和形状。常见的配准标记,如十字形标记[1]、CMYK标记[2]、独立实心圆标记[3]、星形标记[4]等,需要单独打印,占用打印空间。通常,配准系统中只有一台相机,因此很难在扩大捕获图像规模的同时提高配准精度。玻璃印刷电路板的丝网印版如图1所示,配准印版如图2所示。为了提高配准精度,本文将分辨率为640 × 480的双摄像头应用于体验装置中。两台摄像机的中心距离为170mm。这两台相机被占用来捕捉板上5mm × 4mm的场。该图像中的每个像素在x方向上对应7.8μm,在y方向上对应8.3μm。为节省打印材料,优化打印空间,根据电路形状的特点,选择键合垫作为配准标记,如图3所示。根据经验,LED芯片的型号为ti - kb358a - bl。根据数据表,两个焊盘之间的距离应大于240μm。因此,x方向最大权限配准偏差为30μm, y方向最大权限配准偏差为24μm。图1所示。印刷屏板用于印刷玻璃LED电路板。图2。用于印刷玻璃LED电路板的配准屏板。图3。注册号。由于玻璃是刚性材料,基板和配准标记不能变形,因此对图像进行预处理[5]分为3步。印版和套印版的预处理方法是相同的。Step1:灰化处理[6],如图3b所示,将3路彩色图像转换为1路灰度图像。Step2:直方图均衡化处理,如图3-c所示,通过拉伸对比度,增大前景与背景的差值来增强对比度。Step3:二值化处理,如图3- 3所示,得到二值化图像。图4。图像预处理示意图。图像特征点的提取图像特征点的提取分为三个步骤。印网版和套印网版的提取方法相同。Step1:对于图5-a所示二值图像中行方向上的数据,计算0值像素(黑色像素)的平均坐标值,即二值图像中每条水平线的中点坐标值。计算水平线所有中间点的列坐标与其平均值之间的绝对误差,根据权限偏差阈值,所有偏差大于阈值的点可以忽略。采用最小二乘法[7]进行直线拟合,可以用图5-b所示的左侧点拟合垂直线。Step2:对于图5-b所示二值图像中水平方向的数据,使用与step1相同的方法,可以得到如图5-c所示的水平线拟合。 Step3:在step1和step2中拟合的垂线和水平线的连接点为特征点的坐标值,如图5-d所示。图5。字符点提取处理流程图。上述字符点的坐标值在图像坐标系中,相机和印版的坐标值在世界坐标系中。首先确定图像坐标系与世界坐标系的映射关系[8],然后计算出实际配准偏差。这种映射关系如式1所示:[i j 1] = N [x y 1](1)式中,i和j为图像坐标,x和y为关系世界坐标系中的实际物理坐标。从图像坐标和世界坐标系中选取N(N≥4)个关系点,得到单应性矩阵N(3 × 3)。根据这个单应性矩阵,可以将图像坐标系中任意一点的坐标值转换为世界坐标系中实际的物理坐标值。首先捕获的两个特征点的坐标作为参考坐标。对比以下字符点的坐标值,可以计算出在x方向、y方向和旋转角度上的偏差。然后,可以提供这个坐标偏差来调整配准板的实际位置。假设首先捕获的两个字符点的世界坐标为A(xa, ya), B(xb, yb),以及下面两个字符点的A(xa ', ya '), B(xb ', yb '),如图6所示。图6。偏差计算。在y方向上方向偏差和旋转可以确定:方向上的偏差是∆x =Δxa +Δxb 2 = | xa−xa ' | + | xb−xb的| 2 (2)y方向上的偏差是∆y =Δya +Δ2 = |丫−ya ' | + | yb−yb的| 2(3)旋转的偏差是Δθ= |θ1−θ2 | = |反正切| yb−丫| | xb xa |−−反正切| yb−丫的| | xb−xa的| |(4)登记注册偏差检测算法的检测经验[9]是编码在Visual Studio 2010和OpenCV 3.0的平台。在实验中,捕获的屏板图像[10]如图7所示。图7。所捕获的屏板图像。点A、B、C、D的像素坐标分别为A(271, 394)、B(369, 394)、C(271, 77)、D(369, 77)。世界坐标(μm)为A(2113.8, 3270.2), B(2878.2, 3270.2), C(2113.8, 639.1), D(2878.2, 639.1)。则,单应性矩阵为N = | 0.254719−0.00179 59.3197−9.4802e 0.478092 82.8394 6.4975e−9.4398e 1 |,该矩阵表示图像坐标系与世界坐标系的映射关系。双摄像头拍摄两幅图像,尺寸为5mm × 4mm,整屏尺寸为200mm × 100mm。经历的偏差数据如表1所示。由此可知,实际平均配准偏差在x方向上为13μm,在y方向上为14μm。满足LED印刷玻璃电路板的配准要求。本文采用双摄像头采集电路图像,根据LED电路的形状特点,选择池垫图像作为新的配准标记。根据经验,板材位置偏差满足LED印刷玻璃电路板的要求。表1。体验结果[μm]。(xa, ya) (xb, yb) (xa, ya) (xb,yb)∆x∆y 1(1026,3476)(4672,827)(1009,3466)(4659,815) 15 11 2(997,3410)(4630,813)(987,3393)(4614,800) 13 15 3(1011,3425)(4611,820)(999,3017)(4605,808) 9 104(1048,3380)(4702,832)(1028,3361)(4686,823) 18 14 5(1031,3496)(4685,845)(1018,3476)(4670,827) 14 19 6(1005,3368)(4701,859)(990,3361)(4690,848) 13 7(1028,3294)(4659,871)(1017,3287)(4636,854) 17 12平均/ / / / 14 13致谢本研究由北京市教育局资助项目编号:KM201610015001,重点科研项目编号:Ea201604。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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