Please use this identifier to cite or link to this item: https://repository.monashhealth.org/monashhealthjspui/handle/1/52487
Title: Eddy current-based identification and depth investigation of microdefects in steel filaments.
Authors: Tran K.S.;Shirinzadeh B.;Smith J. 
Monash Health Department(s): Monash University - School of Clinical Sciences at Monash Health
Institution: (Tran, Shirinzadeh) Robotics and Mechatronics Research Laboratory (RMRL), Department of Mechanical and Aerospace Engineering, Monash University, Melbourne, VIC 3800, Australia
(Smith) Department of Surgery, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC 3800, Australia
Issue Date: 7-Sep-2024
Copyright year: 2024
Place of publication: Switzerland
Publication information: Sensors (Basel, Switzerland). 24(16) (no pagination), 2024. Date of Publication: 06 Aug 2024.
Journal: Sensors
Abstract: In the field of quality control, the critical challenge of analyzing microdefects in steel filament holds significant importance. This is particularly vital, as steel filaments serve as reinforced fibers in the use and applications within various component manufacturing industries. This paper addresses the crucial requirement of identifying and investigating microdefects in steel filaments. Eddy current signals are used for the identification of microdefects, and an in-depth investigation is conducted. The core objective is to establish the relationship between the depth of defects and the signals detected through the eddy current sensing principle. The threshold of the eddy current instrument was set at 10%, corresponding to a created depth of 20 microm, to identify defective specimens. A total of 30 defective samples were analyzed, and the phase angles between the experimental and theoretical results were compared. The depths of defects ranged from 20 to 60 microm, with one sample having a depth exceeding 75 microm. The calculated threshold of 10.18% closely aligns with the set threshold of 10%, with a difference of only 1.77%. The resulting root mean square error (RMSE) was found to be 10.53 degrees, equivalent to 3.49 microm for the difference in depth and phase between measured results and estimated results. This underscores the methodology's accuracy and its applicability across diverse manufacturing industries.
DOI: http://monash.idm.oclc.org/login?url=https://dx.doi.org/10.3390/s24165101
PubMed URL: 39204797 [https://www.ncbi.nlm.nih.gov/pubmed/?term=39204797]
URI: https://repository.monashhealth.org/monashhealthjspui/handle/1/52487
Type: Article
Type of Clinical Study or Trial: Observational study (cohort, case-control, cross sectional, or survey)
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