Research on Visual Detection Method of Cantilever Beam Cracks Based on Vibration Modal Shapes

Rongfeng Deng, Yubin Lin, Baoshan Huang, Hui Zhang, Fengshou Gu, Andrew D. Ball

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

A visual detection method is proposed in this paper to identify cracks in a cantilever beam crack. The method takes full advantages of high spatial resolution of image sensing, relying only on cost-effective ordinary frame rate camera to record the process of free vibration of the cantilever beam, and combines with singular value decomposition method to obtain the vibration mode shapes of the cantilever beam. Then modal shape differences from baseline are taken as the features for detection and diagnosis The effectiveness of the first-order vibration mode shape difference in cantilever beam crack size and location detection is verified by both simulation and experiment.

Original languageEnglish
Title of host publicationInternational Congress and Workshop on Industrial AI 2021
EditorsRamin Karim, Alireza Ahmadi, Iman Soleimanmeigouni, Ravdeep Kour, Raj Rao
PublisherSpringer, Cham
Pages434-444
Number of pages11
ISBN (Electronic)9783030936396
ISBN (Print)9783030936389
DOIs
Publication statusPublished - 7 Feb 2022
EventInternational Congress and Workshop on Industrial AI - Virtual, Online
Duration: 6 Oct 20217 Oct 2021

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364

Conference

ConferenceInternational Congress and Workshop on Industrial AI
Abbreviated titleIAI 2021
CityVirtual, Online
Period6/10/217/10/21

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