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公开(公告)号:US11927511B2
公开(公告)日:2024-03-12
申请号:US17586729
申请日:2022-01-27
Inventor: Dongling Li , Lei Zhao , Haizhou Wang , Xuejing Shen , Qingqing Zhou , Weihao Wan , Haozhou Feng
IPC: G01N1/28 , G01N23/223 , G01N33/204
CPC classification number: G01N1/286 , G01N23/223 , G01N33/204 , G01N2001/2866 , G01N2001/2893
Abstract: The present application relates to a method for statistical distribution characterization of dendritic structures in original position of single crystal superalloy, and relates to the technical field of analysis of metal material composition and microstructure, comprising the following steps: step 1, processing a to-be-tested sample and determining a calibration coefficient; step 2, obtaining a two-dimensional element content distribution map of the to-be-tested sample; and step 3, determining the number and average spacing of primary dendrites. A composition distribution region analyzed in the present application is larger than the area of a distribution region of the traditional microscopic analysis method, and the sample preparation is simple. The distribution, number and average spacing of the primary dendrites can be obtained without metallographic corrosion sampling. Therefore, the present invention has the advantages of large statistical field of view, high efficiency and complete information, and the statistical data is more accurate and reliable.
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公开(公告)号:US10804073B2
公开(公告)日:2020-10-13
申请号:US16669274
申请日:2019-10-30
Applicant: THE NCS TESTING TECHNOLOGY CO., LTD.
Inventor: Haizhou Wang , Xing Yu , Xuejing Shen , Yunhai Jia , Xiaojia Li , Yuhua Lu , Weihao Wan , Jianqiu Luo , Dongling Li , Lei Zhao
Abstract: An apparatus and method for a large-scale high-throughput quantitative characterization and three-dimensional reconstruction of a material structure. The apparatus having a glow discharge sputtering unit, a sample transfer device, a scanning electron microscope unit and a GPU computer workstation. The glow discharge sputtering unit can achieve large size (cm order), nearly flat and fast sample preparation, and controllable achieve layer-by-layer ablation preparation along the depth direction of the sample surface; rapid scanning electron microscopy (SEM) can achieve large-scale and high-throughput acquisition of sample characteristic maps. The sample transfer device is responsible for transferring the sample between the glow discharge sputtering source and the scanning electron microscope in an accurately positioning manner. The GPU computer workstation performs splicing, processing, recognition and quantitative distribution characterization on the acquired sample characteristic maps, and carries out three-dimensional reconstruction of the structure of the sample prepared by layer-by-layer sputtering.
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公开(公告)号:US12019025B2
公开(公告)日:2024-06-25
申请号:US17315235
申请日:2021-05-07
Applicant: NCS Testing Technology CO., LTD
Inventor: Xing Yu , Haizhou Wang , Xuejing Shen , Xiaojia Li , Yifei Zhu , Weihao Wan , Yuhua Lu , Hui Wang , Qun Ren , Yongqing Wang , Zhenzhen Wan
CPC classification number: G01N21/67 , C23C14/3435 , H01J49/0459 , H01J49/06 , H01J49/12
Abstract: An apparatus and a method for preparing glow discharge sputtering samples for materials microscopic characterization are provided. The apparatus includes a glow discharge sputtering unit, a glow discharge power supply, a gas circuit automatic control unit, a spectrometer, and a computer. The structure of the glow discharge sputtering unit is optimized to be more suitable for sample preparation by simulation. By adding a magnetic field to the glow discharge plasma, uniform sample sputtering is realized within a large size range of the sample surface. The spectrometer monitors multi-element signal in a depth direction of the sample sputtering, so that precise preparation of different layer microstructures is realized. In conjunction with the acquisition of the sample position marks and the precise spatial coordinates (x, y, z) information, the correspondence between the surface space coordinates and the microstructure of the sample is conveniently realized.
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公开(公告)号:US11506650B2
公开(公告)日:2022-11-22
申请号:US17009117
申请日:2020-09-01
Applicant: The NCS Testing Technology Co., Ltd.
Inventor: Dongling Li , Weihao Wan , Jie Li , Haizhou Wang , Lei Zhao , Xuejing Shen , Yunhai Jia
Abstract: The invention belongs to the technical field of quantitative statistical distribution analysis for micro-structures of metal materials, and relates to a method for automatic quantitative statistical distribution characterization of dendrite structures in a full view field of metal materials. According to the method based on deep learning in the present invention, dendrite structure feature maps are marked and trained to obtain a corresponding object detection model, so as to carry out automatic identification and marking of dendrite structure centers in a full view field; and in combination with an image processing method, feature parameters in the full view field such as morphology, position, number and spacing of all dendrite structures within a large range are obtained quickly, thereby achieving quantitative statistical distribution characterization of dendrite structures in the metal material. The method is accurate, automatic and efficient, involves a large amount of quantitative statistical distribution information, and is statistically more representative as compared with the traditional measurement of feature sizes of dendrite structures in a single view field.
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