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公开(公告)号:US11835547B2
公开(公告)日:2023-12-05
申请号:US17680340
申请日:2022-02-25
Applicant: National Cheng Kung University
Inventor: Yi-Chun Chen , Yi-De Liou , Yi-Hsin Weng
Abstract: The method for detecting mechanical and magnetic features comprises the steps of: aiming a probe of the sensor at a sample; defining several detected points for detection on the sample; detecting one of points and comprising the steps of: approaching the probe to the detected point from a predetermined height; contacting the probe with the detected point and applying a predetermined force on the detected point; making the probe far away from the detected point until to the predetermined height; shifting the probe to the next point for detection and repeating the detection; collecting the data of each of the detected points while the probe rapidly approaches to the points from the predetermined height; using a signal decomposition algorithm to transform the collected data to a plurality of data groups; and choosing a part of the data groups to be as data of feature distributions of the sample.
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公开(公告)号:US20230168275A1
公开(公告)日:2023-06-01
申请号:US17680340
申请日:2022-02-25
Applicant: National Cheng Kung University
Inventor: Yi-Chun Chen , Yi-De Liou , Yi-Hsin Weng
Abstract: The method for detecting mechanical and magnetic features comprises the steps of: aiming a probe of the sensor at a sample; defining several detected points for detection on the sample; detecting one of points and comprising the steps of: approaching the probe to the detected point from a predetermined height; contacting the probe with the detected point and applying a predetermined force on the detected point; making the probe far away from the detected point until to the predetermined height; shifting the probe to the next point for detection and repeating the detection; collecting the data of each of the detected points while the probe rapidly approaches to the points from the predetermined height; using a signal decomposition algorithm to transform the collected data to a plurality of data groups; and choosing a part of the data groups to be as data of feature distributions of the sample.
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