Hilbert–Huang Transform-Based Emitted Sound Signal Analysis for Tool Flank Wear Monitoring

2013 ◽  
Vol 38 (8) ◽  
pp. 2219-2226 ◽  
Author(s):  
J Emerson Raja ◽  
Loo Chu Kiong ◽  
Lim Way Soong
Keyword(s):  
Signal Analysis ◽  
Flank Wear ◽  
Sound Signal ◽  
Tool Flank Wear ◽  
Hilbert Huang Transform ◽  
Wear Monitoring

scholarly journals Tool Flank Wear Estimation using Emitted Sound Signal Analysis by PCA – SER Based Peak to Peak Measurements

2019 ◽  
Vol 8 (6) ◽  
pp. 5212-5216
Keyword(s):  
Tool Wear ◽  
Signal Analysis ◽  
Industry 4.0 ◽  
Flank Wear ◽  
Optimization Techniques ◽  
Tool Wear Monitoring ◽  
Tool Flank Wear ◽  
Wear Monitoring ◽  
Novel Method ◽  
Selection Of

The higher levels degrees of automation for industry 4.0 standards require optimization techniques in production activities including tool wear monitoring. The unmonitored tool may spoil the product if it is worn out more than the permitted levels or micro broken or cracked internally. A novel method suggested in this work utilizes neither extra ordinary calculation nor complex mathematical transformations in tool wear monitoring. This method follows no video capturing and image processing rather follows a simple sound wave monitoring captured at the time conversion process by a microphone. The SER a PCA variant technique with the purpose of used in selecting simply the higher velocity of principal components (PCs) in quantifying the feature extracted while separating noise from sound signals. A SER method is used for the selection of suitable PCs for consideration. The best methods of normalization suitable for the SER method is found and implemented the PCA-SER on signals after filter the signals by butter worth filter to remove noise. This proposed procedure resulted in wide differences and proper annotation in differentiating the degree of tool wear in fresh, slight and severely worn categories.

Tool flank wear monitoring using torsional–axial vibrations in drilling

2018 ◽  
Vol 13 (1) ◽  
pp. 107-118 ◽  
Author(s):  
R. S. Nakandhrakumar ◽  
D. Dinakaran ◽  
J. Pattabiraman ◽  
M. Gopal
Keyword(s):  
Flank Wear ◽  
Tool Flank Wear ◽  
Wear Monitoring ◽  
Axial Vibrations

A Fault Detection Approach Based on Sound Signal Analysis for Equipment Monitoring

2020 ◽  
pp. 129-139
Author(s):  
Weihai Sun ◽  
Lemei Han
Keyword(s):  
Fault Detection ◽  
Signal Analysis ◽  
Energy Analysis ◽  
Detection Method ◽  
Sound Signal ◽  
Practical Significance ◽  
Time Frequency ◽  
Detection Approach ◽  
Machine Fault ◽  
Learning Data

Machine fault detection has great practical significance. Compared with the detection method that requires external sensors, the detection of machine fault by sound signal does not need to destroy its structure. The current popular audio-based fault detection often needs a lot of learning data and complex learning process, and needs the support of known fault database. The fault detection method based on audio proposed in this paper only needs to ensure that the machine works normally in the first second. Through the correlation coefficient calculation, energy analysis, EMD and other methods to carry out time-frequency analysis of the subsequent collected sound signals, we can detect whether the machine has fault.

The influence of tool flank wear on residual stresses induced by milling aluminum alloy

2009 ◽  
Vol 209 (9) ◽  
pp. 4502-4508 ◽  
Author(s):  
Z.T. Tang ◽  
Z.Q. Liu ◽  
Y.Z. Pan ◽  
Y. Wan ◽  
X. Ai
Keyword(s):  
Aluminum Alloy ◽  
Residual Stresses ◽  
Flank Wear ◽  
Tool Flank Wear

Tool Life Analysis when Turning Ti-6Al-4V Using Vegetable Oil-Based Cutting Fluid

2017 ◽  
Vol 882 ◽  
pp. 36-40
Author(s):  
Salah Gariani ◽  
Islam Shyha ◽  
Connor Jackson ◽  
Fawad Inam
Keyword(s):  
Tool Wear ◽  
Tool Life ◽  
Vegetable Oil ◽  
Flank Wear ◽  
Cutting Speed ◽  
Fractional Factorial ◽  
Cutting Fluid ◽  
Depth Of Cut ◽  
Tool Flank Wear ◽  
Fluid Concentration

This paper details experimental results when turning Ti-6Al-4V using water-miscible vegetable oil-based cutting fluid. The effects of coolant concentration and working conditions on tool flank wear and tool life were evaluated. L27 fractional factorial Taguchi array was employed. Tool wear (VBB) ranged between 28.8 and 110 µm. The study concluded that a combination of VOs based cutting fluid concentration (10%), low cutting speed (58 m/min), feed rate (0.1mm/rev) and depth of cut (0.75mm) is necessary to minimise VBB. Additionally, it is noted that tool wear was significantly affected by cutting speeds. ANOVA results showed that the cutting fluid concentration is statistically insignificant on tool flank wear. A notable increase in tool life (TL) was recorded when a lower cutting speed was used.

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