Development and applications of a drilling process monitoring system for pneumatic drills

2002 ◽  
Author(s):  
Jun Sugawara
Keyword(s):  
Monitoring System ◽  
Process Monitoring ◽  
Drilling Process

In-Process Monitoring and Estimation of Tool Wear on CNC Turning by Applying Multi-Sensor with Back Propagation Technique

2011 ◽  
Vol 291-294 ◽  
pp. 3036-3043 ◽  
Author(s):  
Somkiat Tangjitsitcharoen ◽  
Channarong Rungruang
Keyword(s):  
Acoustic Emission ◽  
Tool Wear ◽  
Monitoring System ◽  
Process Monitoring ◽  
Back Propagation ◽  
Force Sensor ◽  
Accelerometer Sensor ◽  
Cnc Turning ◽  
Propagation Technique ◽  
Cnc Turning Process

The aim of this research is to propose and develop the in-process monitoring system of the tool wear for the carbon steel (S45C) in CNC turning process by utilizing the multi-sensor which are the force sensor, the sound sensor, the accelerometer sensor and the acoustic emission sensor. The progress of the tool wear results in the larger cutting force, the higher amplitude of the acceleration signal, and the higher power spectrum densities of sound and acoustic emission signals. Hence, their signals have been integrated via the neural network with the back propagation technique to monitor the tool wear. The experimentally obtained results showed that the in-process monitoring system proposed and developed in this research can be effectively used to estimate the tool wear level with the higher accuracy and reliability.

scholarly journals A new versatile in-process monitoring system for milling

2006 ◽  
Vol 46 (15) ◽  
pp. 2026-2035 ◽  
Author(s):  
Mathieu Ritou ◽  
Sebastien Garnier ◽  
Benoit Furet ◽  
Jean-Yves Hascoet
Keyword(s):  
Monitoring System ◽  
Process Monitoring

scholarly journals Frequency Analysis and Process Monitoring in Drilling of Composite Materials

2004 ◽  
Vol 13 (4) ◽  
pp. 096369350401300 ◽  
Author(s):  
D. Kim ◽  
M. Ramulu
Keyword(s):  
Time Series ◽  
Composite Materials ◽  
Carbon Fiber ◽  
Process Monitoring ◽  
Frequency Analysis ◽  
Thermoplastic Composites ◽  
Time Series Models ◽  
Drilling Process ◽  
Fiber Reinforced ◽  
Drilling Force

Drilling experiments were conducted using carbide and cryogenic treated carbide drills into carbon fiber-reinforced thermoplastic composites, namly Graphite/PIXA-M (PIXA-M) composites. Drilling force signals were collected from all conditions and analysed using fast Fourier transformations and autoregressive (AR) time series models. Power spectrums were used to examine the cutting characteristics in the drilling process. AR coefficients were used to distinguish the cutting signals of autoclaved and induction heated PIXA-M composites, and conventional and cryogenic treated carbide drills.

Sign in / Sign up

Export Citation Format

Share Document