公开(公告)号：US20220065728A1

公开(公告)日：2022-03-03

申请号：US17405423

申请日：2021-08-18

Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE

Inventor： Hung-Chih CHANG ,  Yao-Long TSAI ,  Li-Hua WANG

IPC: G01M3/24 ,  G06N3/04 ,  G01S19/01

Abstract: An acoustic resonance diagnostic method for detecting structural degradation is provided. The method includes steps as follows: Firstly, a training model is built using a deep neural network. At least two training acoustic signals are inputted to the training model to carry a training. A diagnostic model is built according to a result of the training using a convolutional neural network. An under-test sound wave signal is captured from an under-test section of an under-test structure through direct contact, non-contact, or indirect contact. A structural degradation state of the under-test section is determined according to the under-test sound wave signal through the diagnostic model.

公开(公告)号：US20240419569A1

公开(公告)日：2024-12-19

申请号：US18399266

申请日：2023-12-28

Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE

Inventor： Hung-Chih CHANG ,  Yao-Long TSAI ,  Li-Hua WANG

IPC: G06F11/27 ,  G01N29/12 ,  G01N29/265 ,  G01N29/46

Abstract: A structure detecting apparatus used for receiving at least one under-test acoustic signal of an under-test structure and determining a structural state of the at least one under-test structure includes a communication interface, a filter amplifier circuit and a logic circuit. The communication interface is used to receive the at least one under-test acoustic signal. The filter amplifier circuit is used to filter the at least one under-test acoustic signal and output at least one filtered-and-amplified signal. The logic circuit includes a diagnostic model configured with a convolutional neural network (CNN) and is used to determine the structural state of the at least one under-test structure based on the at least one filtered-and-amplified signal.

公开(公告)号：US20190145850A1

公开(公告)日：2019-05-16

申请号：US16111033

申请日：2018-08-23

Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE

Inventor： Yao-Long TSAI ,  Li-Hua WANG

IPC: G01M3/24 ,  G01M3/28

CPC classification number: G01M3/243 ,  F16L55/07 ,  F16L2201/30 ,  F17D1/08 ,  F17D5/02 ,  G01M3/2807 ,  G01M5/0025 ,  G01M5/0033 ,  G01M5/0066 ,  G01M7/00 ,  G01N29/043 ,  G01N29/045 ,  G01N29/4427 ,  G01N29/4472 ,  G01N2291/0258 ,  G01N2291/044 ,  G01N2291/2634

Abstract: A method for detecting a deterioration defect of a structural part using a structural unit includes: defining a first base structural unit and obtaining N first base modal parameters of the first base structural unit; detecting a respective one of M first subject structural units of a subject structural part by each of M first sensors to obtain N first actual modal parameters of each of the M first subject structural units; calculating N first subject modal parameters of each of the M first subject structural units according to the N first actual modal parameters of each of the M first subject structural units and M*N first predetermined ratios; and comparing the N first subject modal parameters of each of the M first subject structural units to the N first base modal parameters to determine whether each of the M first subject structural units has a deterioration defect.

公开(公告)号：US20190017895A1

公开(公告)日：2019-01-17

申请号：US15855944

申请日：2017-12-27

Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE

Inventor： Yao-Long TSAI ,  Li-Hua WANG

IPC: G01M3/28

CPC classification number: G01M3/2807 ,  F17D5/06 ,  G01M5/0025 ,  G01M5/0033 ,  G01M5/0066 ,  G01N29/11 ,  G01N29/4427 ,  G01N29/4445 ,  G01N29/46 ,  G01N2291/015 ,  G01N2291/0258

Abstract: A method for detecting deterioration of a structural part includes: detecting a waveform of time domain of the structural part by a sensor disposed on the structural part; performing a conversion of time domain to frequency domain for the waveform of time domain by a processor electrically connected to the sensor so as to obtain an actual modal parameter of each of a plurality of modals related to a waveform of frequency domain of the structural part; comparing the actual modal parameter of each of the plurality of modals to modal parameter information stored in a database to determine whether a deterioration defect exists in the structural part; and determining a degree and a position of the deterioration defect when the deterioration defect exists in the structural part.

公开(公告)号：US20220291175A1

公开(公告)日：2022-09-15

申请号：US17830859

申请日：2022-06-02

Applicant: INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE

Inventor： Hung-Chih CHANG ,  Yao-Long TSAI ,  Li-Hua WANG

IPC: G01N29/12 ,  G01N29/14 ,  G01N29/34 ,  G06N3/04 ,  G06N3/08 ,  G06N20/10

Abstract: An acoustic resonance diagnostic method for detecting structural degradation is provided. The method includes steps as follows: Firstly, a training model is built using a deep neural network. At least two training acoustic signals are inputted to the training model to carry a training. A diagnostic model is built according to a result of the training using a CNN. A plurality of under-test sound wave signals are captured from an under-test section of an under-test structure. An AI is used to filter data invalid for detecting structural degradation from the under-test sound wave signals. A structural degradation state of the under-test section is determined according to a remaining portion of the under-test sound wave signals through the diagnostic model.