Invention Grant
- Patent Title: Monitoring bolt tightness using percussion and machine learning
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Application No.: US17051476Application Date: 2019-04-24
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Publication No.: US11885703B2Publication Date: 2024-01-30
- Inventor: Gangbing Song , Qingzhao Kong , Siu Chun Michael Ho , Furui Wang
- Applicant: University of Houston System
- Applicant Address: US TX Houston
- Assignee: UNIVERSITY OF HOUSTON SYSTEM
- Current Assignee: UNIVERSITY OF HOUSTON SYSTEM
- Current Assignee Address: US TX Houston
- Agency: Jackson Walker LLP
- International Application: PCT/US2019/028896 2019.04.24
- International Announcement: WO2019/212822A 2019.11.07
- Date entered country: 2020-10-29
- Main IPC: G01N29/04
- IPC: G01N29/04 ; G01L5/24 ; G06N5/04 ; G06N5/01

Abstract:
The systems and methods described herein are for monitoring the tightness of bolts. The systems and methods may be used with a mechanism to apply a percussive tap and with a recording or monitoring device for detecting and recording the acoustic signals that are generated by the percussive tap. The acoustic signals generated by percussive taps applied to bolts in various looseness states are analyzed and a machine learning model is developed that allows for determining bolt looseness based on the acoustic signals.
Public/Granted literature
- US20210231515A1 MONITORING BOLT TIGHTNESS USING PERCUSSION AND MACHINE LEARNING Public/Granted day:2021-07-29
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