公开(公告)号：US12026075B2

公开(公告)日：2024-07-02

申请号：US18073300

申请日：2022-12-01

Applicant: ASUSTEK COMPUTER INC.

Inventor： Cheng-Wei Gu ,  Shu-Chiao Liao ,  Ming-Hung Chung ,  Yao-Hsun Huang ,  Yuan-I Tseng ,  Hung-Ju Lin

IPC: G06F11/273 ,  G06F1/3296

CPC classification number: G06F11/2733 ,  G06F1/3296

Abstract: A power supply health check system for checking a health state of an under-test power supply is provided. The under-test power supply supplies power to a main board which has a voltage signal during operation. The health check system includes a detecting module, a deep learning model, and a processing unit. The detecting module is electrically connected to the main board to detect the voltage signal and convert the voltage signal into a digital signal. The deep learning model is established by using frequency-domain voltage data of a plurality of healthy power. The processing unit is configured to: collect the digital signal and store the digital signal as under-test time-domain voltage data; convert the under-test time-domain voltage data into under-test frequency-domain voltage data; and calculate, based on the under-test frequency-domain voltage data and the deep learning model, a health indicator for determining the health state of the under-test power supply.

公开(公告)号：US20230341464A1

公开(公告)日：2023-10-26

申请号：US17979860

申请日：2022-11-03

Applicant: ASUSTeK COMPUTER INC.

Inventor： Hung-Ju Lin ,  Yuan-I Tseng ,  Cheng-Wei Gu ,  Shu-Chiao Liao

IPC: G01R31/317 ,  G01R31/28 ,  G06K9/62

CPC classification number: G01R31/31708 ,  G01R31/2841 ,  G06K9/6256

Abstract: A signal abnormality detection system and a method thereof are provided. The signal abnormality detection system includes a signal sensor and a computing device. The signal sensor generates a sample signal to be tested through sensing. The computing device is signal-connected to the signal sensor to receive the sample signal to be tested, perform a correction on the sample signal to be tested, and perform a time-frequency transform on a one-dimensional signal generated after the correction to generate a two-dimensional time-frequency signal. The computing device reconstructs the two-dimensional time-frequency signal by using an abnormality detection model to calculate a reconstructed difference value. The computing device performs comparison to determine whether the reconstructed difference value is greater than a detection threshold to determine whether the sample signal to be tested is an abnormal sample.