An Intelligent Grinding Wheel Wear Monitoring System Based on Acoustic Emission

2017 ◽  
Vol 261 ◽  
pp. 195-200 ◽  
Author(s):  
Ning Ding ◽  
Chang Long Zhao ◽  
Xi Chun Luo ◽  
Jian Shi
Keyword(s):  
Neural Network ◽  
Acoustic Emission ◽  
Monitoring System ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Grinding Wheel Wear ◽  
Wear Monitoring ◽  
Grinding Machine ◽  
Ae Signals ◽  
Wear Condition

Acoustic emission (AE) signals can provide tool condition that is critical to effective process control. However, how to process the data and extract useful information are challenging tasks. This paper presented an intelligent grinding wheel wear monitoring system which was embedded in a surface grinding machine. An AE sensor was used to collect the grinding signals. The grinding wheel wear condition features were extracted by a proposed novel method based on statistics analysis of the average wavelet decomposition coefficient. The detailed signal characteristics during different wear condition are described. A BP neural network was used to classify the conditions of the grinding wheel wear. The inputs of the neural network were the three extracted features, and the outputs were three different states of grinding wheel condition, namely primary wear, intermediate wear and serious wear. The intelligent monitoring system was evaluated through grinding experiments. The results indicate that the effectiveness of the proposed method for extracting features of AE signals and developed intelligent grinding wheel wear monitoring system are satisfied.

Wear Monitoring on Microcrystalline Aluminum Oxide Grinding Wheels on Profile Grinding with the Aid of Acoustic Emission

2014 ◽  
Vol 894 ◽  
pp. 95-103 ◽  
Author(s):  
Lucas Benini ◽  
Walter Lindolfo Weingaertner ◽  
Lucas da Silva Maciel
Keyword(s):  
Acoustic Emission ◽  
Wear Behavior ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Profile Grinding ◽  
Grinding Wheel Wear ◽  
Abrasive Grains ◽  
Profile Deviation ◽  
Synthetic Materials ◽  
External Cylindrical Grinding

The localized wear on grinding wheel edges is a common phenomenon on profile grinding since the abrasive grains are less attached to the bond. The grinding wheel wear depends heavily on the process parameters, workpiece and wheel composition, causing changes on the process and profile deviation behaviors. In order to cope with these uncertainties, many natural and synthetic materials have been used in different grinding processes. However, the influence of mixed compositions of different types of abrasive grains on external cylindrical grinding is not well known. In order to assess this relation, a methodology procedure was developed providing an overview of the cinematic edges behavior on a progressive wheel wear. The methodology procedure is based on the acoustic emission technology, using a transducer with a 50 μm radius diamond tip. The tip, when in contact with a rotating grinding wheel, enables the evaluation of the cinematic cutting edges. The abrasive grain density was evaluated for different grinding wheel compositions and specific wear removal values. Furthermore, these results were compared to the profile deviation observed on the same tool, allowing the assessment of the influence of different microcrystalline corundum grains on the overall grinding wheel wear behavior.

Experimental Study on Intelligent Monitoring of Diamond Grinding Wheel Wear

2008 ◽  
Vol 392-394 ◽  
pp. 714-718 ◽  
Author(s):  
Bo Zhao ◽  
Bao Yu Du ◽  
W.D. Liu
Keyword(s):  
Condition Monitoring ◽  
Time Domain ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Intelligent Monitoring ◽  
Diamond Grinding Wheel ◽  
Grinding Wheel Wear ◽  
Diamond Grinding ◽  
Characteristic Signal ◽  
Wear Condition

In order to research the relationship between grinding wheel wear and the signal of grinding strength and grinding vibration, the grinding strength signal and grinding vibration signal under different wear condition were carried on digital processing by time-domain, frequency-domain, and wavelet-pocket analysis, and characteristic signal reflecting grinding wheel wear condition was obtained. Grinding wheel wear was monitored by time-domain statistics average value of grinding strength and energy value of three layers wavelet-pocket decomposition frequency band. The method how to set design parameters of neural network is introduced, and their value in condition monitoring network is determined. Mapping model of grinding wheel wear and characteristic signal is established. Recognition effect is satisfied in the experiment of grinding wheel wear condition monitoring. It confirmed the model is reliable and effective. The result shows that the new intelligent monitoring method is effective on monitoring grinding wheel deactivation condition. One new method of diamond grinding wheel wear condition monitoring under precision and ultra-precision grinding is introduced.

Experimental evaluation on grinding wheel wear through vibration and acoustic emission

Wear ◽  
1998 ◽  
Vol 217 (1) ◽  
pp. 7-14 ◽  
Author(s):  
A. Hassui ◽  
A.E. Diniz ◽  
J.F.G. Oliveira ◽  
J. Felipe ◽  
J.J.F. Gomes
Keyword(s):  
Acoustic Emission ◽  
Experimental Evaluation ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Grinding Wheel Wear

Pressure-based in-process measurement by the null method for automatic compensation of wheel wear during surface grinding

2003 ◽  
Vol 217 (2) ◽  
pp. 153-159 ◽  
Author(s):  
K Furutani ◽  
N T Hieu ◽  
N Ohguro ◽  
T Nakamura
Keyword(s):  
Pressure Sensor ◽  
Hydrodynamic Pressure ◽  
Surface Grinding ◽  
Grinding Wheel ◽  
Contact Method ◽  
Automatic Compensation ◽  
Wheel Wear ◽  
Process Measurement ◽  
Grinding Wheel Wear ◽  
Grinding Machine

This paper deals with automatic compensation of grinding wheel wear in wet grinding by pressure-based in-process measurement. A pressure sensor is set close to a grinding wheel with a small gap. When grinding fluid is dragged into the gap by the rotation, the wear of the grinding wheel can be predicted by using hydrodynamic pressure that has been generated, which corresponds to the gap thickness and topography of the surface. This method was applied to a numerically controlled surface grinding machine. Some characteristics of the pressure were measured. The pressure sensor was repositioned to keep the pressure constant with the null method. The spindle was also repositioned according to the sensor displacement, which was equal to the worn thickness of the grinding wheel. The error of the ground depth with compensation was less than the feeding step for the compensation. The measurement performance by the null method was compared with that obtained without compensation, with compensation by a deflection method and by the contact method.

A Study on Monitoring System for Grinding Wheel Status Based on Acoustic Emission Technology

2011 ◽  
Vol 52-54 ◽  
pp. 2051-2055
Author(s):  
Pei Jiang Li ◽  
Ting You
Keyword(s):  
Acoustic Emission ◽  
High Speed ◽  
Grinding Wheel ◽  
Signal Acquisition ◽  
Wheel Wear ◽  
Processing Efficiency ◽  
Emission Signal ◽  
Grinding Wheel Wear ◽  
Upper Computer

The grinding wheel wear status is an important guarantee for the processing efficiency and processing quality of precision and super precision grinding. In this paper, a USB acoustic emission signal acquisition system is designed for online monitoring of grinding wheel status. In the system, CPLD is used as the controller, and a high-speed A/D converter is used to implement the synchronous acquisition of acoustic emission array signals. The collected data are sent into FIFO, and CY7C68013A is used for USB data transmission with upper computer. The sampling frequency of the system can be 10 MHz, and USB transmission speed can reach 40M/S. It is proved that it can meet the monitoring requirements of grinding wheel wear status well by the grinding processing.

scholarly journals Optimization of Replaced Grinding Wheel Diameter for Minimum Grinding Cost in Internal Grinding

2019 ◽  
Vol 9 (7) ◽  
pp. 1363 ◽  
Author(s):  
Thi-Hong Tran ◽  
Xuan-Hung Le ◽  
Quoc-Tuan Nguyen ◽  
Hong-Ky Le ◽  
Tien-Dung Hoang ◽  
...  
Keyword(s):  
Simulation Experiment ◽  
Depth Of Cut ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Grinding Wheel Wear ◽  
Internal Grinding ◽  
Optimization Study ◽  
Grinding Machine ◽  
The Cost ◽  
Cost Components

This paper shows an optimization study on calculating the optimum replaced wheel diameter in internal grinding of stainless steel. In this work, the effects of the input factors, including the initial diameter, the grinding wheel width, the ratio between the length and the diameter of the work-pieces, the dressing depth of cut, the wheel life and the radial grinding wheel wear per dress on the optimum replaced grinding wheel diameter were considered. Also, the effects of cost components, including the cost of the grinding machine and the wheel cost were examined. Moreover, to estimate the influences of these parameters on the optimum replaced diameter, a simulation experiment was given and conducted by programming. From the results of the study, a regression equation was proposed to calculate the optimum replaced diameter.

Paper 15: A Prediction of Some Causes and Effects of Cam Profile Errors

1967 ◽  
Vol 182 (12) ◽  
pp. 145-151
Author(s):  
J. H. C. Brittain ◽  
R. Horsnell
Keyword(s):  
Numerical Methods ◽  
Valve Train ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Grinding Wheel Wear ◽  
Valve Motion ◽  
Cam Profile ◽  
Machine Setting ◽  
Grinding Machine ◽  
Profile Errors

In the paper numerical methods are developed to enable a cam copy grinding machine to be analysed. A method for computing the former profile necessary to produce a cam specified by a required valve motion is described. The effects of grinding wheel wear and of machine setting errors on the profile of a production cam are investigated. Use is made of the dynamic analysis of Barkan in predicting the influence of these profile errors on the dynamics of a valve train. Finally, the possibility of changing the diameter of the former roller to compensate for grinding wheel wear is considered.

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