Tri-axial Time-frequency Analysis for Tool Failures Detection in Deep Twist Drilling Process
Premature tool failure in deep drilling reduces product quality. By analyzing the deep drilling process signals through time and frequency domains in tri-axial vibrations, the early conditions before tool failure can be detected. From the experimental data, vibration time domain signals were analyze...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/6820/ http://umpir.ump.edu.my/id/eprint/6820/ http://umpir.ump.edu.my/id/eprint/6820/ http://umpir.ump.edu.my/id/eprint/6820/1/fkm-2016-razlan-Tri-axial%20time-frequency%20analysis.pdf |
| Summary: | Premature tool failure in deep drilling reduces product quality. By analyzing the deep drilling process signals through time and frequency domains in tri-axial vibrations, the early conditions before tool failure can be detected. From the experimental data, vibration time domain signals were analyzed by short-time Fourier transform to detect the tool wear mechanism. Results showed that tool wear accelerated before failure as increasing feed rate and cutting speed were recognized in the y- and z-axes in time–frequency analysis. |
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