Paulo Roberto de Aguiar

Tool Condition Monitoring of Single-Point Dresser Using Acoustic Emission and Neural Networks Models

Identification and online monitoring of the dresser wear are necessary to guarantee a desired wheel surface and improve the effectiveness of grinding process to a satisfactory level. However, tool wear is a complex phenomenon occurring in several and different ways in cutting processes, and there is a lack of analytical models that can represent the tool condition. On the other hand, neural networks are considered as a good approach to resolve the absence of an analytical or empirical model. This paper describes a method to characterize the dresser wear condition from acoustic emission (AE) signal. To achieve this, some neural network models are proposed. Initially, a study on the frequency content of the raw AE signal was carried out to determine features that correlate the signal and dresser wear. The features of the signal were obtained from the root mean square and ratio of power statistics at nine frequency bands selected from AE spectra. Combinations of two frequency bands were evaluated as inputs to eight neural networks models, which have been compared with their classification ability. It could be verified that the combination of the frequency bands of 28-33 and 42-50 kHz best characterized the dresser wear condition. Some of the models produced very good results and can therefore ensure the ground part will be within project specifications.

Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics

Tool condition monitoring in grinding of advanced ceramics using neural networks.Acoustic emission and power signals were used in several statistical parameters.Results showed that the ANN were highly successful in estimating tool wear.Errors was less than 4%.The models will help to improve product quality and increase productivity. Grinding wheel wear, which is a very complex phenomenon, causes changes in most of the shapes and properties of the tool during machining, reducing the efficiency of the grinding operation and impairing workpiece quality. Therefore, monitoring the condition of the tool during the grinding process plays a key role in the quality of workpieces being manufactured. In this study, diamond tool wear was estimated during the grinding of advanced ceramics using intelligent systems composed of four types of neural networks. Experimental tests were performed on a surface grinding machine and tool wear was measured by the imprint method throughout the tests. Acoustic emission and cutting power signals were acquired during the tests and statistics were obtained from these signals. Training and validating algorithms were developed for the intelligent systems in order to automatically obtain the best estimation models. The combination of signals and statistics along with the intelligent systems brings an innovative aspect to the grinding process. The results indicate that the models are highly successful in estimating tool wear.

Automatic system for thermal damage detection in manufacturing process with internet monitoring

This work involved the development of a smart system dedicated to surface burning detection in the grinding process through constant monitoring of the process by acoustic emission and electrical power signals. A program in Visual Basic® for Windows® was developed, which collects the signals through an analog-digital converter and further processes them using burning detection algorithms already known. Three other parameters are proposed here and a comparative study carried out. When burning occurs, the newly developed software program sends a control signal warning the operator or interrupting the process, and delivers process information via the Internet. Parallel to this, the user can also interfere in the process via Internet, changing parameters and/or monitoring the grinding process. The findings of a comparative study of the various parameters are also discussed here.

Piezoelectric Transducers Assessed by the Pencil Lead Break for Impedance-Based Structural Health Monitoring

The pencil lead break (PLB) is a well-known method for characterizing acoustic emission sensors. In this paper, we analyze the effectiveness of this method in characterizing piezoelectric transducers for structural health monitoring (SHM) systems based on the electromechanical impedance (EMI) technique. Tests were carried out on aluminum beams of different sizes, and two types of transducers were considered: lead zirconate titanate ceramics and macrofiber composite devices. The experimental results indicate a clear relationship between the variation in the electrical impedance signature of the transducer and power spectral density obtained with the PLB method. Therefore, the PLB can be a simple and effective method for assessing the sensitivity of transducers for damage detection in SHM systems based on the EMI technique.

In-process grinding monitoring through acoustic emission

This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding processes. To accomplish such a goal, an experimental work was carried out for 15 runs in a surface grinding machine operating with an aluminum oxide grinding wheel and ABNT 1045 Steel as work material. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate data acquisition system working at 2.5 MHz was used to collect the raw acoustic emission instead of the root mean square value usually employed. Many statistical analyses have shown to be effective to detect burn, such as the root mean square (RMS), correlation of the AE, constant false alarm rate (CFAR), ratio of power (ROP) and mean-value deviance (MVD). However, the CFAR, ROP, Kurtosis and correlation of the AE have been presented more sensitive than the RMS.

Utilization of minimum quantity lubrication (MQL) with water in CBN grinding of steel

The use of cutting fluids is fundamental to machining processes, mainly when it comes to high heat generation, which is the case of grinding. Thus, lubrication and cooling provided by cutting fluids improve the final quality of the workpiece. However, cutting fluid usage provide some drawbacks concerning environmental, costs and health issues. Therefore, new methods for application and optimization of cutting fluids are being researched aiming to reduce the amount of fluid used, as well as the minimization of cutting fluid hazards. The present study analyzes the behavior of a recently proposed optimization method, up to now only tested in turning, which consists of adding water to minimum quantity lubrication (MQL). Three different proportions were tested in this study: 1/1, 1/3 and 1/5 parts of oil per parts of water. The following output variables were evaluated: surface roughness, roundness errors, grinding power and diametric wheel wear. Also, optical microscopy and microhardness measurements were conducted, in order to detect burns and surface alterations. The obtained results were also compared to conventional (flood coolant) cooling-lubrication and traditional MQL (without water). MQL with water (1/5) presented better results of surface roughness and roundness errors, when compared to traditional MQL, and the results are very close to when using flood coolant. For grinding power and wheel wear, the results for MQL with water (1/5) were the best among the tested conditions.

Performance of aerodynamic baffles in cylindrical grinding analyzed on the basis of air layer pressure and speed

Over the years, grinding has been considered one of the most important manufacturing processes. Grinding is a high precision process, and the loss of a single workpiece in this stage of the production is unacceptable, for the value added to the material is very high due to many processes it has already undergone prior to grinding. This study aims to contribute toward the development of an experimental methodology whereby the pressure and speed of the air layer produced by the high rotation of the grinding wheel is evaluated with and without baffles, i.e., in an optimized grinding operation and in a traditional one. Tests were also carried out with steel samples to check the difference in grinding wheel wear with and without the use of baffles. Keywords : grinding, aerodynamic baffle, optimized process

Monitoring the dressing operation in the grinding process

This work was based on a methodology of development and experimentation, and involved monitoring the dressing operation by processing the acoustic emission and electric power signals to detect the optimal dressing moment. Dressing tests were performed in a surface grinding machine with an aluminium grinding wheel. Dressing analysis software was developed and used to process the signals collected earlier in order to analyse not only the dressing parameters but also the softwares ability to indicate the instant when the dressing operation could be concluded. Parameters used in the study of burn in grinding were implemented in order to ascertain if they would also prove efficient in monitoring dressing. A comparative study revealed that some parameters are capable of monitoring the dressing operation. It was possible to verify the parameters effectiveness that today are utilised in burning to monitor dressing as well as to create new parameters for monitoring this operation.

A study on the viability of minimum quantity lubrication with water in grinding of ceramics using a hybrid-bonded diamond wheel:

With the currently strict environmental law in present days, researchers and industries are seeking to reduce the amount of cutting fluid used in machining. Minimum quantity lubrication is a potential alternative to reduce environmental impacts and overall process costs. This technique can substantially reduce cutting fluids in grinding, as well as provide better performance in relation to conventional cutting fluid application (abundant fluid flow). The present work aims to test the viability of minimum quantity lubrication (with and without water) in grinding of advanced ceramics, when compared to conventional method (abundant fluid flow). Measured output variables were grinding power, surface roughness, roundness errors and wheel wear, as well as scanning electron micrographs. The results show that minimum quantity lubrication with water (1:1) was superior to conventional lubrication-cooling in terms of surface quality, also reducing wheel wear, when compared to the other methods tested.

Application of the Minimum Quantity Lubrication (MQL) technique in the plunge cylindrical grinding operation

Precision cylindrical grinding is used extensively in the manufacture of precision components in the metal-mechanical industry in general. Modern CNC grinding machines have improved this process with respect to the positioning and rigidity of the machine-workpiece-tool system, allowing the production of high precision parts with low dimensional tolerances. Besides the difficulties inherent to the process, awareness has grown in recent years regarding the environmental issues of cutting fluids. As a response, the industry has begun to seek alternative lubrication and cooling methods. Among the various existing techniques, Minimum Quantity Lubrication (MQL) has been considered as an alternative. This technique can be understood as a combination of conventional lubrication and cooling methods and dry machining, in which a small quantity of lubricating oil mixed with compressed air flow is delivered in the wheel-workpiece interface. The MQL technique is already widely employed in machining processes with tools of defined geometry (e.g. turning), in which produces very satisfactory results. However, the MQL technique has been little explored in grinding processes (non-defined tool geometry), in which the really effective heat removal methods are required due to the frictional heat generation in the grinding zone. Consequently, the aim of this study was to evaluate the plunge cylindrical internal grinding operation when using the MQL technique and the conventional cooling method. Roughness and roundness were the outputparameters. As a result, it was found that the best values of roughness Ra were obtained with the conventional lubrication method. The MQL technique applied as proposed was not able to flush the chips away from the grinding zone, leading to the highest Ra values. No significant differences were detected among the cooling methods when analyzing the roundness results. The workpiece fixture method selected was responsible for the overall unsatisfactory results.