The behaviour of resin-bond diamond wheels in the grinding of advanced ceramics

Results are reported of the behaviour of the plane tangential grinding process using diamond grinding wheels. Grinding performance is analysed in terms of the wear behaviour of the wheel in the grinding of ceramic. Discussion of the results concentrates on the wear mechanism of the diamond wheel and the process of material removal.

Advanced ceramics: Evaluation of the mechanism of stock removal and ground surface quality

The aim of this work is to evaluate the mechanism of stock removal and the ground surface quality of advanced ceramics grounded by a plane tangential grinding process with diamond grinding wheels. The analysis of the grinding performance was done regarding the cutting surface wear behavior of the grinding wheel for ceramic workpieces. The discussion about the results emphasized the wear mechanism of the grinding wheel cutting surface and the cutting phenomenology of the grinding process. The grounded surface was evaluated using Scanning Electron Microscopy (SEM). © 1999 Society of Automotive Engineers, Inc.

Production grinding burn detection using acoustic emission and electric power signals

This work uses a monitoring system based on a PC platform, where the acoustic emission and electric power signals generated during the grinding process are used to investigate superficial burning occurrence in a surface grinding operation using two types of steel, three grinding conditions and an Al203 vitrified grinding wheel. Acoustic emission signals on the workpiece and grinding power were measured during a surface plunge operation until the grinding burn happened. From the results the standard deviation of the acoustic emission signal and the maximum electric power were calculated for each grinding pass. The proposed DPO parameter is the product between the power level and acoustic emission standard deviation. The results show that both signals can be used for burning detection, and the parameter DPO is the best indicator for the burning studied in this work. This can be explained by the high dispersion of the acoustic emission RMS level associated to the high power consumption when the grinding wheel lose its sharpness.

The improvement in grinding of inlet engine valves by the adoption of the most effective cuting fluid type

In this paper is presented an experimental research in which the grinding of seating surfaces of inlet engine valves was improved by the adoption of the most effective cutting fluid type, matching the new requirements of cutting fluid application. Four different types of cutting fluids (straight oil and three different types of soluble oils) were analyzed. As qualitative and quantitative evaluation parameters of the performance of the cutting fluids, the roughness, the grinding wheel wear, the cutting force and the workpiece residual stress were determined. As a conclusion, the straight oil was the cutting fluid that presented the best results in all of the parameters analyzed. Copyright © 2000 Society of Automotive Engineers, Inc.

Advanced ceramics: Evaluation of the mechanism of stock removal and ground surface quality

The aim of this work is to evaluate the mechanism of stock removal and the ground surface quality of advanced ceramics machined by a surface grinding process using diamond grinding wheels. The analysis of the grinding performance was done regarding the cutting surface wear behavior of the grinding wheel for ceramic workpieces. The ground surface was evaluated using Scanning Electron Microscopy (SEM). As a result it can be said that the mechanism of material removal in the grinding of ceramic is largely one of brittle fracture. The increase of the hmax can reduce the tangential force required by the process. Although, it results in an increase in the surface damage, reducing the mechanical properties of the ground component.

Rectificacion de aceros fragiles y ductiles: Parametros de entrada para obtener los mejores resultados

In this work, the behavior of the steel surface grinding process with conventional grinding wheels was studied for various grinding conditions and a fixed dressing condition. The input parameters (wheel speed, workpiece speed, depth of cut), that set up the grinding conditions were determined as a function of the characteristics of the grinding machine. A test bench was established where the grinding power was measured in real time as a function of the volume of material removed. The results showed that in the grinding of fragile steels with a soft wheel and medium grit size, the average power of the cut shows a tendency to increase and become stabilized. The surface roughness of the piece decreased in all the tests and was proportional to the increase in the number of active grits. In tests on the grinding of ductile steels with a soft wheel and fine grit size, the wheel became dull until the moment that the abrasive grits were released from the cut surface.

In-process thermal damage detection in grinding with monitoring via Internet

This work aims the development of a dedicated system for detection of burning in surface grinding process, where the process will constantly be monitored through the acoustic emission and electric power of the induction motor drive. Acquired by an analog-digital converter, algorithms process the signals and a control signal is generated to inform the operator or interrupt the process in case of burning occurrence. Moreover, the system makes possible the process monitoring via Internet. Additionally, a comparative study between parameters DPO and FKS is carried through. In the experimental work one type of. steel (ABNT-1020 annealed) and one type of grinding wheel referred to as TARGA, model ART 3TG80.3 NVHB, were employed.

Control of thermal damage in grinding by digital signal processing of raw acoustic emission

Grinding process is usually the last finishing process of a precision component in the manufacturing industries. This process is utilized for manufacturing parts of different materials, so it demands results such as low roughness, dimensional and shape error control, optimum tool-life, with minimum cost and time. Damages on the parts are very expensive since the previous processes and the grinding itself are useless when the part is damaged in this stage. This work aims to investigate the efficiency of digital signal processing tools of acoustic emission signals in order to detect thermal damages in grinding process. 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 e VC131 steels. The acoustic emission signals were acquired from a fixed sensor placed on the workpiece holder. A high sampling rate acquisition system at 2.5 MHz was used to collect the raw acoustic emission instead of root mean square value usually employed. In each test AE data was analyzed off-line, with results compared to inspection of each workpiece for burn and other metallurgical anomaly. A number of statistical signal processing tools have been evaluated.

Study of thresholds to burning in surface grinding process

This work aims at finding out the threshold to burning in surface grinding process. Acoustic emission and electric power signals are acquired from an analog-digital converter and processed through algorithms in order to generate a control signal to inform the operator or interrupt the process in the case of burning occurrence. The thresholds that dictate the situation of burn and non-burn were studied as well as a comparison between the two parameters was carried out. In the experimental work one type of steel (ABNT-1045 annealed) and one type of grinding wheel referred to as TARGA model 3TG80.3-NV were employed. Copyright © 2005 by ABCM.

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. Copyright © 2006 by ABCM.

Microtensile bond strength between a quartz fiber post and a resin cement: Effect of post surface conditioning

Purpose: To test the bond strength between a quartz-fiber-reinforced composite post (FRC) and a resin cement. The null hypothesis was that the bond strength can be increased by using a chairside tribochemical silica-coating system. Materials and Methods: Thirty quartz-FRCs (Light-Post) were divided into 3 groups according to the post surface treatment: G1) Conditioning with 32% phosphoric acid (1 min), applying a silane coupling agent; G2) etching with 10% hydrofluoric acid (1 min), silane application; G3) chairside tribochemical silica coating method (CoJet System): air abrasion with 30-μ SiO x-modified Al2O3 particles, silane application. Thereafter, the posts were cemented into a cylinder (5 mm diameter, 15 mm height) with a resin cement (Duo-Link). After cementation, the specimens were stored in distilled water (37°C/24 h) and sectioned along the x and y axes with a diamond wheel under cooling (Lab-cut 1010) to create nontrimmed bar specimens. Each specimen was attached with cyanoacrylate to an apparatus adapted for the microtensile test. Microtensile testing was conducted on a universal testing machine (1 mm/min). The data obtained were submitted to the one-way ANOVA and Tukey test (α = 0.05). Results: A significant influence of the conditioning methods was observed (p < 0.0001). The bond strength of G3 (15.14 ± 3.3) was significantly higher than the bond strengths of G1 (6.9 ± 2.3) and G2 (12.60 ± 2.8) (p = 0.000106 and p = 0.002631, respectively). Notwithstanding the groups, all the tested specimens showed adhesive failure between the resin cement and FRC. Conclusion: The chairside tribochemical system yielded the highest bond strength between resin cement and quartz-fiber post. The null hypothesis was accepted (p < 0.0001).

Global analysis of aerodynamics deflectors efficiency in the grinding process

The conventional, grinding methods in some cases are not very efficient because the arising of thermal damages in the pieces is very common. Optimization methods of cutting fluid application in the grinding zone are essential to prevent thermal problems from interaction of the wheel grains with the workpiece. surface. The optimization can happen through the correct selection of the cut parameters and development of devices that eliminate air layer effects generated around the grinding wheel. This article will collaborate with the development of an experimentation methodology which allows evaluating, comparatively, the performance of the deflectors in the cutting region to minimize the air layer effect of the high speed of the grinding wheel. The air layers make the cutting fluid jet to dissipate in the machine. An optimized nozzle was used in order to compare the results with the conventional method (without baffles or deflectors) of cutting fluid application. The results showed the high eficciency of the deflectors or baffles in the finish results. Copyright © 2006 by ABCM.

Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

Compactação do solo e intervalo hídrico ótimo no crescimento da parte aérea e produtividade da cultura do milho

The aim of this work was to evaluate the effect of soil compaction caused by tractor wheel traffic on the limiting water range (LLWR), shoot growth and levels of compaction and four replications in a completely randomized experimental design. Soil samples with preserved structure were collected in the layers: 0.02-0.05; 0.08-0.11; 0.15-0.18 and 0.22-0.25m to determine macroporosity, microporosity, total porosity, bulk density, resistance to penetration and LLWR. The evaluated corn parameters were: plant and first spike height, steam diameter, number of spikes per plant, plant dry matter, dry matter of 1000 seeds and seed productivity. The soil compaction restricted all corn parameters except the number of spikes per plant and dry matter of 1000 seeds. The LLWR was reduced by the soil resistance to penetration, even in the tilled soil with bulk density of 1.12 Mg m-3. Only the treatment with 11 Mg tractor, repeated four times on the area, demonstrated bulk density above critical bulk density in the LLWR that was 1.37 Mg m-3, where the seed productivity was significantly smaller.

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 software's 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. Copyright © 2009, Inderscience Publishers.