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An audio signal based model for condition monitoring of sheet metal stamping process
conference contribution
posted on 2015-06-15, 00:00 authored by Kongalage Nishchitha Indivarie Ubhayaratne, Yong XiangYong Xiang, Michael PereiraMichael Pereira, Bernard RolfeBernard RolfeTool condition monitoring is an important factor in ensuring manufacturing efficiency and product quality. Audio signal based methods are a promising technique for condition monitoring. However, the influence of interfering signals and background noise has hindered the use of this technique in production sites. Blind signal separation (BSS) has the potential to solve this problem by recovering the signal of interest out of the observed mixtures, given that the knowledge about the BSS model is available. In this paper, we discuss the development of the BSS model for sheet metal stamping with a mechanical press system, so that the BSS techniques based on this model can be developed in future. This involves conducting a set of specially designed machine operations and developing a novel signal extraction technique. Also, the link between stamping process conditions and the extracted audio signal associated with stamping was successfully demonstrated by conducting a series of trials with different lubrication conditions and levels of tool wear.
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Event
IEEE Industrial Electronics and Applications. Conference (10th : 2015 : Auckland, New Zealand)Pagination
1267 - 1272Publisher
IEEELocation
Auckland, New ZealandPlace of publication
Piscataway, N.J.Publisher DOI
Start date
2015-06-15End date
2015-06-17ISBN-13
9781467373173Language
engPublication classification
E Conference publication; E1 Full written paper - refereedCopyright notice
2015, IEEETitle of proceedings
ICIEA 2015: Proceedings of the 10th IEEE Conference on Industrial Electronics and ApplicationsUsage metrics
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