Cutting-tools degradation assessment for structural-steel machining centers

Tsung Ren Huang; Hao Ting Chen; Min Chun Pan

doi:10.1115/IMECE2020-24643

Cutting-tools degradation assessment for structural-steel machining centers

Tsung Ren Huang, Hao Ting Chen, Min Chun Pan

機械工程學系

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

摘要

To assess cutting-tools degradation, mounted accelerometers and current clamp probes were used to acquire machining vibration for both the band-saw machine and the drilling machine, of which a structural-steel machining center is composed. Significant features were first extracted through spectral analysis, and tool degradation assessment was conducted through using a supervised learning scheme, self-organizing map. The results reveal that 10% remaining useful life can be predicted before the band-saws and drills wore out.

原文	???core.languages.en_GB???
主出版物標題	Advanced Manufacturing
發行者	American Society of Mechanical Engineers (ASME)
ISBN（電子）	9780791884492
DOIs	https://doi.org/10.1115/IMECE2020-24643
出版狀態	已出版 - 2020
事件	ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020 - Virtual, Online 持續時間: 16 11月 2020 → 19 11月 2020

出版系列

名字	ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
卷	2B-2020

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020
城市	Virtual, Online
期間	16/11/20 → 19/11/20

存取文件

10.1115/IMECE2020-24643

智動雷射加工系統暨聯網服務整合計畫－智動雷射加工系統暨聯網服務整合計畫(2/3)
Tung, P.-C. (PI)
1/12/19 → 31/10/20
研究計畫: Research

引用此

@inproceedings{5ee95e310aef45dbae35f17e2675407d,

title = "Cutting-tools degradation assessment for structural-steel machining centers",

abstract = "To assess cutting-tools degradation, mounted accelerometers and current clamp probes were used to acquire machining vibration for both the band-saw machine and the drilling machine, of which a structural-steel machining center is composed. Significant features were first extracted through spectral analysis, and tool degradation assessment was conducted through using a supervised learning scheme, self-organizing map. The results reveal that 10% remaining useful life can be predicted before the band-saws and drills wore out.",

keywords = "Feature extraction, Remaining useful life, Self-organizing map, Structural-steel machining, Tool degradation assessment",

author = "Huang, {Tsung Ren} and Chen, {Hao Ting} and Pan, {Min Chun}",

note = "Publisher Copyright: {\textcopyright} 2020 The Author(s). This is an Open Access article under the CC BY license.; ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020 ; Conference date: 16-11-2020 Through 19-11-2020",

year = "2020",

doi = "10.1115/IMECE2020-24643",

language = "???core.languages.en_GB???",

series = "ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)",

publisher = "American Society of Mechanical Engineers (ASME)",

booktitle = "Advanced Manufacturing",

}

Huang, TR, Chen, HT & Pan, MC 2020, Cutting-tools degradation assessment for structural-steel machining centers. 於 Advanced Manufacturing. ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE), 卷 2B-2020, American Society of Mechanical Engineers (ASME), ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020, Virtual, Online, 16/11/20. https://doi.org/10.1115/IMECE2020-24643

Cutting-tools degradation assessment for structural-steel machining centers. / Huang, Tsung Ren; Chen, Hao Ting; Pan, Min Chun.
Advanced Manufacturing. American Society of Mechanical Engineers (ASME), 2020. (ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE); 卷 2B-2020).

研究成果: 書貢獻/報告類型 › 會議論文篇章 › 同行評審

TY - GEN

T1 - Cutting-tools degradation assessment for structural-steel machining centers

AU - Huang, Tsung Ren

AU - Chen, Hao Ting

AU - Pan, Min Chun

PY - 2020

Y1 - 2020

N2 - To assess cutting-tools degradation, mounted accelerometers and current clamp probes were used to acquire machining vibration for both the band-saw machine and the drilling machine, of which a structural-steel machining center is composed. Significant features were first extracted through spectral analysis, and tool degradation assessment was conducted through using a supervised learning scheme, self-organizing map. The results reveal that 10% remaining useful life can be predicted before the band-saws and drills wore out.

AB - To assess cutting-tools degradation, mounted accelerometers and current clamp probes were used to acquire machining vibration for both the band-saw machine and the drilling machine, of which a structural-steel machining center is composed. Significant features were first extracted through spectral analysis, and tool degradation assessment was conducted through using a supervised learning scheme, self-organizing map. The results reveal that 10% remaining useful life can be predicted before the band-saws and drills wore out.

KW - Feature extraction

KW - Remaining useful life

KW - Self-organizing map

KW - Structural-steel machining

KW - Tool degradation assessment

UR - http://www.scopus.com/inward/record.url?scp=85101245590&partnerID=8YFLogxK

U2 - 10.1115/IMECE2020-24643

DO - 10.1115/IMECE2020-24643

M3 - 會議論文篇章

AN - SCOPUS:85101245590

T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)

BT - Advanced Manufacturing

PB - American Society of Mechanical Engineers (ASME)

T2 - ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020

Y2 - 16 November 2020 through 19 November 2020

ER -

Cutting-tools degradation assessment for structural-steel machining centers

摘要

出版系列

???event.eventtypes.event.conference???

存取文件

指紋

專案

智動雷射加工系統暨聯網服務整合計畫－智動雷射加工系統暨聯網服務整合計畫(2/3)

引用此