Robust Wheel Wear Monitoring System for Cylindrical Traverse Grinding

2020 ◽  
Vol 25 (5) ◽  
pp. 2220-2229
Author(s):  
Bin Zhang ◽  
Christopher Katinas ◽  
Yung C. Shin
Keyword(s):  
Monitoring System ◽  
Wheel Wear ◽  
Wear Monitoring ◽  
Traverse Grinding

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.

Tool Wear Monitoring of High Speed Milling Based on Vibratory Signal Processing

2014 ◽  
Vol 565 ◽  
pp. 36-45
Author(s):  
Hadjadj Abdechafik ◽  
Kious Mecheri ◽  
Ameur Aissa
Keyword(s):  
Signal Processing ◽  
Tool Wear ◽  
Monitoring System ◽  
High Speed ◽  
Milling Process ◽  
Machining Performance ◽  
High Speed Milling ◽  
Tool Wear Estimation ◽  
On Line ◽  
Wear Monitoring

The objective of this study is to develop a process of treatment of the vibratory signals generated during a horizontal high speed milling process without applying any coolant in order to establish a monitoring system able to improve the machining performance. Thus, many tests were carried out on the horizontal high speed centre (PCI Météor 10), in given cutting conditions, by using a milling cutter with only one insert and measured its frontal wear from its new state that is considered as a reference state until a worn state that is considered as unsuitable for the tool to be used. The results obtained show that the first harmonic follow well the evolution of frontal wear, on another hand a wavelet transform is used for signal processing and is found to be useful for observing the evolution of the wavelet approximations through the cutting tool life. The power and the root mean square (RMS) values of the wavelet transformed signal gave the best results and can be used for tool wear estimation. All this features can constitute the suitable indicators for an effective detection of tool wear and then used for the input parameters of an on-line monitoring system. Nevertheless we noted the remarkable influence of the machining cycle on the quality of measurements by the introduction of a bias on the signal; this phenomenon appears in particular in horizontal milling and in the majority of studies is ignored

An Intelligent System for Online Optimization of the Cylindrical Traverse Grinding Operation

2006 ◽  
Vol 220 (3) ◽  
pp. 355-363 ◽  
Author(s):  
B W Kruszyński ◽  
P Lajmert
Keyword(s):  
Material Removal ◽  
Intelligent System ◽  
Removal Rate ◽  
Feedforward Neural Network ◽  
Grinding Process ◽  
Grinding Temperature ◽  
Optimization Scheme ◽  
Wheel Wear ◽  
Simulation Research ◽  
Traverse Grinding

This paper presents an intelligent system for optimization of the cylindrical traverse grinding process whose objective is to maximize the material removal rate with constraints on workpiece out-of-roundness and waviness errors, on surface finish, and on grinding temperature. A theoretical analysis of wheel wear development in the traverse grinding process is presented. Next, the results of an experimental test are discussed to establish the most efficient strategy for grinding allowance removal. In the optimization scheme a feedforward neural network is employed to obtain a model which describes relations between the process input parameters and the grinding results. Then this model is used to optimize adaptively the traverse grinding process. The performance of the proposed optimization system is evaluated by simulation research.

Wear performance and its online monitoring of the semimetal brake lining for automobiles

2014 ◽  
Vol 66 (1) ◽  
pp. 100-105 ◽  
Author(s):  
Yan Yin ◽  
Jiusheng Bao ◽  
Lei Yang
Keyword(s):  
Experimental Data ◽  
Wear Rate ◽  
Monitoring System ◽  
Online Monitoring ◽  
Electronic Control Unit ◽  
Wear Performance ◽  
Content Type ◽  
Disc Brakes ◽  
Wear Monitoring ◽  
Brake Lining

Purpose – In order to improving the braking reliability and assuring the driving safety of automobiles, this paper aims at the wear performance and its online monitoring of its brake lining. Design/methodology/approach – The wear performance of the semimetal brake lining for automobiles was investigated on a self-made braking tester for disc brakes. Based on the experimental data, an intelligent forecasting model for the wear rate was established by the artificial neural network (ANN) technology. And by taking it as a core, an online braking wear monitoring system for automobiles was designed. Findings – It is shown that the wear rate rises obviously with the increasing of both initial braking velocity and braking pressure. By the contrast, the initial braking velocity affects the wear rate more seriously. The ANN model trained by the experimental data shows favorable capability for predicting of the wear rate. The big forecasting errors at high velocity and heavy load should be attributed to the jumping of the wear rate at this period. Based on the existed sensors and electronic control unit system of automobiles, the online braking wear monitoring system can be established easily by the ANN technology. Originality/value – A self-made braking tester for disc brakes was used to test the wear performance, which can simulate better the actual disc braking conditions than the standard pin-on-disc friction tester. An online braking wear monitoring system was designed to help improving the braking reliability and safety of automobiles.

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