Experimental Study on the Relationship Between Acoustic Emission Signal and Grinding Wheel Wear

2019 ◽  
Author(s):  
Ning Ding ◽  
Jingsong Duan ◽  
Chao Liu ◽  
Shuna Jiang ◽  
Shanfu Cui
Keyword(s):  
Experimental Study ◽  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Grinding Wheel ◽  
Wheel Wear ◽  
Emission Signal ◽  
Grinding Wheel Wear ◽  
The Relationship

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.

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 Acoustic Emission Signal Detection in Process of Laser-Induced Backside Wet Etching of Sapphire

2017 ◽  
Vol 44 (4) ◽  
pp. 0402003
Author(s):  
罗志良 Luo Zhiliang ◽  
谢小柱 Xie Xiaozhu ◽  
魏昕 Wei Xin ◽  
胡伟 Hu Wei ◽  
任庆磊 Ren Qinglei ◽  
...  
Keyword(s):  
Experimental Study ◽  
Acoustic Emission ◽  
Signal Detection ◽  
Acoustic Emission Signal ◽  
Wet Etching ◽  
Emission Signal

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

An Investigation of Grinding and Wheel Loading Using Acoustic Emission

1984 ◽  
Vol 106 (1) ◽  
pp. 28-33 ◽  
Author(s):  
D. Dornfeld ◽  
He Gao Cai
Keyword(s):  
Acoustic Emission ◽  
Chip Thickness ◽  
Process Efficiency ◽  
Grinding Wheel ◽  
Force Measurements ◽  
Wheel Wear ◽  
Emission Signal ◽  
Wheel Loading ◽  
Loss Of Contact ◽  
Higher Sensitivity

This paper investigates the potential for using acoustic emission signal analysis for a monitoring technique for process automation as well as a sensitive tool for investigation of grinding fundamentals. The acoustic emission generated during the grinding process is analyzed to determine its sensitivity to process efficiency and the condition of the grinding wheel. Acoustic emission from surface grinding is used to measure wear-related loading of the grinding wheel and sparkout (or loss of contact) between the wheel and the work surface. A discussion of energy dissipation in grinding and the generation of acoustic emission is included. This investigation showed that the acoustic emission energy, (RMS)2, increases with the combined effects of wheel wear and loading, the signal energy, (RMS)2, is a function of the undeformed chip thickness and that the signal accurately detects work-wheel contact and sparkout with a higher sensitivity than force measurements.

scholarly journals Detection of damage to the power supply system of diesel engine under field conditions

2017 ◽  
Vol 170 (3) ◽  
pp. 159-163
Author(s):  
Paweł MAZURUK ◽  
Marcin WOJS ◽  
Piotr ORLIŃSKI ◽  
Mieczysław SIKORA
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Internal Combustion Engines ◽  
Fuel Injection ◽  
Injection System ◽  
Combustion Engines ◽  
Coefficient Variation ◽  
Emission Signal ◽  
Third Phase ◽  
The Relationship

Fuel injection system damages is a major problem for internal combustion engines. Approximately 70% of the injection system malfunction is due to injector damages. Authors of the article tested an uniqe method of diagnosis injectors by using an acoustic emission. The acoustic emission signal (EA) is a phenomenon used in various field of technology and it is a wave generated in solid materials. The EA signal was measured during operation of damaged and undamaged injectors body in a few series, analized and verified in term of result obtain in response signals. The relationship between the acoustic emission signal and the injectors operating phases has been determined. On base of coefficient variation of the duration in the third phase the value of which increases substantially when the injectors are damaged were found in ranges of 45%. For corect working injectors value of coefficient variation were found in range from 21% to 37%.

Discussion on the Relationship between Rockburst Proneness of Rock and its AE b-Value

2011 ◽  
Vol 137 ◽  
pp. 398-402
Author(s):  
Guang Zhang ◽  
Mo Xiao Li ◽  
Jing Xi Chen
Keyword(s):  
Acoustic Emission ◽  
Acoustic Emission Signal ◽  
Peak Stress ◽  
B Value ◽  
Uniaxial Compression Test ◽  
B Values ◽  
Emission Signal ◽  
Whole Process ◽  
In The Beginning ◽  
The Relationship

In order to strengthen the study on rockburst prediction and inquire the relationship between rockburst proneness of rock and its AE b-value, we select three typical rocks of volcanic, sedimentary, and metamorphic to conduct indoor rock mechanics test. Uniaxial compression test are carried to calculate the rockburst proneness of three kinds of rocks, at the meantime we collect the acoustic emission signal during the whole process by acoustic emission instrument. After analyzing the different AE features of all kinds of rocks, we find that the AE b-values of three kinds of rocks both develop in the beginning of two different loading conditions. The AE b-values of marble and sandstone change in a more stable way, and the b-value of granite decline at the 50% of the peak stress. The b-value of granite is the biggest and the sandstone’s is the smallest.

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.

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