Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/108519
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Industrial and Systems Engineering | - |
dc.creator | Xu, Z | - |
dc.creator | Yip, LWS | - |
dc.creator | To, S | - |
dc.date.accessioned | 2024-08-19T01:58:53Z | - |
dc.date.available | 2024-08-19T01:58:53Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/108519 | - |
dc.description | 33rd CIRP Design Conference 2023, 17-19 May 2023, Sydney, Australia | en_US |
dc.language.iso | en | en_US |
dc.publisher | Elsevier | en_US |
dc.rights | © 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) | en_US |
dc.rights | The following publication Xu, Z., Yip, L. W. S., & To, S. (2023). Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection. Procedia CIRP, 119, 1210-1215 is available at https://doi.org/10.1016/j.procir.2023.04.012. | en_US |
dc.subject | Anomaly detection | en_US |
dc.subject | Condition monitoring | en_US |
dc.subject | Ultra-precision machining | en_US |
dc.title | Condition monitoring of three-axis ultra-precision milling machine tool for anomaly detection | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.spage | 1210 | - |
dc.identifier.epage | 1215 | - |
dc.identifier.volume | 119 | - |
dc.identifier.doi | 10.1016/j.procir.2023.04.012 | - |
dcterms.abstract | Accurately and continuously monitoring ultra-precision machining (UPM) process is the foundation for subsequent diagnosis and optimization, then facilitating energy-saving, efficient production, and high-quality machining. However, comprehensive monitoring of UPM process has hardly been investigated systematically in previous studies. To cover the gap, this study examined the linkages among these parameters monitored in UPM process using a five-layers network for the first time. Subsequently, we proposed an advanced monitoring platform that integrates G-code command, installation sensors, and controller interface. This proposed platform incorporated with anomalies detection algorithm was finally employed and validated on a three-axis ultra-preciisiion miilllliing machiine tooll. Results showed that this proposed platform could successfully achieve anomaly identification using power consumption and X/Y/Z components force signals. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Procedia CIRP, 2023, v. 119, p. 1210-1215 | - |
dcterms.isPartOf | Procedia CIRP | - |
dcterms.issued | 2023 | - |
dc.identifier.scopus | 2-s2.0-85169923061 | - |
dc.identifier.eissn | 2212-8271 | - |
dc.description.validate | 202408 bcch | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | Projects of Strategic Importance of The Hong Kong Polytechnic University | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Conference Paper |
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File | Description | Size | Format | |
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1-s2.0-S2212827123006431-main.pdf | 2.61 MB | Adobe PDF | View/Open |
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