公开(公告)号：US20210356369A1

公开(公告)日：2021-11-18

申请号：US17391017

申请日：2021-08-01

Applicant: NCS Testing Technology CO.,LTD

Inventor： Haizhou WANG ,  Qun REN ,  Lei ZHAO ,  Xuejing SHEN ,  Hui WANG ,  Dongling LI ,  Weihao WAN ,  Wenyu ZHANG ,  Xing YU ,  Lixia YANG

IPC: G01N3/12

Abstract: The present invention discloses a high throughput statistical characterization method of metal micromechanical properties, which comprises: grinding and polishing a metal sample until specular reflection finish satisfies a test requirement; marking position coordinates of a to-be-measured area on the metal sample by a microhardness tester to ensure the comparison of the same to-be-measured area; conducting an isostatic pressing strain test on the to-be-measured area by an isostatic pressing technology; and comparing high throughput characterization of components, microstructures, microdefects and three-dimensional surface morphology of the metal sample before and after isostatic pressing strain to obtain the full-view-field cross-scale high throughput statistical characterization of micromechanical property uniformity of the metal sample.

公开(公告)号：US20200294760A1

公开(公告)日：2020-09-17

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

IPC: H01J37/22 ,  H01J37/28 ,  H01J37/34 ,  H01J37/20 ,  G06T15/08 ,  G06T11/20 ,  C23C14/34

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.

公开(公告)号：US20220205922A1

公开(公告)日：2022-06-30

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

IPC: G01N21/67 ,  H01J49/06 ,  C23C14/34 ,  H01J49/12 ,  H01J49/04

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.

公开(公告)号：US20210063376A1

公开(公告)日：2021-03-04

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

IPC: G01N33/204 ,  G01N1/32 ,  G06T7/11 ,  G01N1/40 ,  G06T7/62

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.