DocumentCode
2572992
Title
Model-based monitoring and failure detection methodology for ball-nose end milling
Author
Huang, Sheng ; Goh, Kiah Mok ; Shaw, Kah Chuan ; Wong, Yoke San ; Hong, Geok Soon
Author_Institution
Singapore Inst. of Manuf. Technol., Singapore
fYear
2007
fDate
25-28 Sept. 2007
Firstpage
155
Lastpage
160
Abstract
This paper presents a model-based monitoring and failure detection approach in ball-nose end milling process. A mechanistic force model has been established for high speed milling on hardened stavax steel with 6 mm micro-grain tungsten carbide 2 flute ball-nose end mill. The threshold curve can be obtained off-line based on the process model as the cutting engagement conditions along the tool path are determined at the simulation stage. The measured cutting forces are monitored on-line to detect the faults by comparing them with the threshold curve at machining stage. If a fault is detected at certain position along the tool path, an intelligent predictive method is utilized to predict whether this fault will result in catastrophic failure. Experimental results are provided to demonstrate the feasibility of this approach.
Keywords
computerised monitoring; cutting; fault diagnosis; hardening; milling; production engineering computing; ball-nose end milling; cutting engagement conditions; failure detection methodology; intelligent predictive method; mechanistic force model; micrograin tungsten carbide flute ball-nose; model-based monitoring; online monitoring; stavax steel hardening; Acoustic sensors; Condition monitoring; Engines; Fault detection; Force sensors; Machining; Metalworking machines; Milling machines; Predictive models; Solid modeling;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Technologies and Factory Automation, 2007. ETFA. IEEE Conference on
Conference_Location
Patras
Print_ISBN
978-1-4244-0825-2
Electronic_ISBN
978-1-4244-0826-9
Type
conf
DOI
10.1109/EFTA.2007.4416766
Filename
4416766
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