Material removal monitoring in precision cylindrical plunge grinding using acoustic emission signal

2013 ◽  
Vol 228 (4) ◽  
pp. 715-722 ◽  
Author(s):  
Chen Jiang ◽  
Haolin Li ◽  
Yunfei Mai ◽  
Debao Guo
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Material Removal ◽  
Grinding Force ◽  
Force Model ◽  
Precision Grinding ◽  
Emission Signal ◽  
Proposed Model ◽  
Acoustic Emission Sensing ◽  
Series Of Experiments

A mathematical model of the acoustic emission signal during a grinding cycle is proposed for the monitoring of material removal in precision cylindrical grinding. Acoustic emission signals generated during precision grinding are sensitive to forces in grinding and present opportunities in accurate and reliable process monitoring. The proposed model is developed on the basis of a traditional grinding force model. Using the developed model, a series of experiments were performed to demonstrate the effectiveness of the acoustic emission-sensing approach in estimating the time constant and material removal in grinding. Results indicate that acoustic emission measurements can be used in the prediction of material removal in precision grinding with excellent sensitivity.

Estimation of the Time Constant of Precision Plunge Grinding in Dwell Period Based on Acoustic Emission Measurement

2013 ◽  
Vol 690-693 ◽  
pp. 3262-3265 ◽  
Author(s):  
Chen Jiang ◽  
De Bao Guo ◽  
Hao Lin Li
Keyword(s):  
Acoustic Emission ◽  
Time Constant ◽  
Emission Measurement ◽  
Precision Grinding ◽  
Plunge Grinding ◽  
Emission Signal ◽  
Acoustic Emission Sensing ◽  
Acoustic Emission Measurement ◽  
Grinding System ◽  
Dwell Period

Our previous work presented a method for estimating the time constant of grinding system in infeed period. To monitor the precision cylindrical plunge grinding process in dwell period, an estimation of the time constant of grinding system in the dwell period, using acoustic emission signal, is presented in this paper. Acoustic emission signals generated during precision grinding are sensitivity and present challenges for accurate and reliable process monitoring. Experiments demonstrate the results of the acoustic emission sensing approach in estimating the time constant in the dwell period of cylindrical plunge grinding.

Estimation of the Time Constant of Plunge Grinding of C45 in Infeed Period with Properties of Mechanical Materials Based on Acoustic Emission Measurement

2013 ◽  
Vol 648 ◽  
pp. 182-185 ◽  
Author(s):  
Chen Jiang ◽  
Hao Lin Li ◽  
Yun Fei Mai ◽  
Yu Lun Chi
Keyword(s):  
Acoustic Emission ◽  
Time Constant ◽  
Grinding Process ◽  
Emission Measurement ◽  
Precision Grinding ◽  
Emission Signal ◽  
Acoustic Emission Sensing ◽  
Grinding Conditions ◽  
Acoustic Emission Measurement ◽  
Grinding System

To monitor the precision cylindrical grinding process, an estimation of the time constant of grinding system, using acoustic emission signal, is presented during infeed period in this paper. Acoustic emission signals generated during precision grinding are sensitivity and present challenges for accurate and reliable process monitoring. Experiments demonstrate the results of the acoustic emission sensing approach in estimating the time constant. This estimation of the time constant can be used to analyze the properties of mechanical materials of the workpiece with the same grinding conditions.

Research of the cold resistance of metals by indentation with registration of an acoustic emission signal

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Low Temperatures ◽  
Cold Resistance ◽  
Emission Signal ◽  
Impact Bending ◽  
Artificial Neural

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]

Sign in / Sign up

Export Citation Format

Share Document