Application of MLP and Kohonen networks for recognition of wear patterns of single-point dressers

Grinding is a parts finishing process for advanced products and surfaces. However, continuous friction between the workpiece and the grinding wheel causes the latter to lose its sharpness, thus impairing the grinding results. This is when the dressing process is required, which consists of sharpening the worn grains of the grinding wheel. The dressing conditions strongly affect the performance of the grinding operation; hence, monitoring them throughout the process can increase its efficiency. The objective of this study was to estimate the wear of a single-point dresser using intelligent systems whose inputs were obtained by the digital processing of acoustic emission signals. Two intelligent systems, the multilayer perceptron and the Kohonen neural network, were compared in terms of their classifying ability. The harmonic content of the acoustic emission signal was found to be influenced by the condition of dresser, and when used to feed the neural networks it is possible to classify the condition of the tool under study.

Mechanical and tribological properties of a-C:H:F Thin Films

a-C:H films were grown by plasma-enhanced chemical vapor deposition in atmospheres composed by 30 % of acetylene and 70 % of argon. Radiofrequency signal (RF) was supplied to the sample holder to generate the depositing plasmas. Deposition time and pressure were chosen 300 s and 9.5 Pa, respectively, while the excitation power changed from 5 to 125 W. The films were exposed to a post-deposition treatment during 300 s in RF-plasmas (13.56 MHz, 70 W) excited from 13.33 Pa of SF6. Raman and X-ray photoelectron spectroscopy were used to evaluate the microstructure and chemical composition of the films. The thickness was measured by perfilometry. Hardness and friction coefficient were determined from nanoindentation and risk tests, respectively. With increasing power, the film thickness reduced, but a further shrinkage occurred upon the fluorination process. After that, the molecular structure was observed to vary with deposition power. Fluorine was detected in all samples replacing H atoms. Consistently with the elevation in the proportion of C atoms with sp3 hybridization, hardness increased from 2 to 18 GPa. Friction coefficient also increased with power due to the generation of dangling bonds during the fluorination process. © 2012 Springer Science+Business Media, LLC.

A Framework to Optimize Biodiversity Restoration Efforts Based on Habitat Amount and Landscape Connectivity

The effectiveness of ecological restoration actions toward biodiversity conservation depends on both local and landscape constraints. Extensive information on local constraints is already available, but few studies consider the landscape context when planning restoration actions. We propose a multiscale framework based on the landscape attributes of habitat amount and connectivity to infer landscape resilience and to set priority areas for restoration. Landscapes with intermediate habitat amount and where connectivity remains sufficiently high to favor recolonization were considered to be intermediately resilient, with high possibilities of restoration effectiveness and thus were designated as priority areas for restoration actions. The proposed method consists of three steps: (1) quantifying habitat amount and connectivity; (2) using landscape ecology theory to identify intermediate resilience landscapes based on habitat amount, percolation theory, and landscape connectivity; and (3) ranking landscapes according to their importance as corridors or bottlenecks for biological flows on a broader scale, based on a graph theory approach. We present a case study for the Brazilian Atlantic Forest (approximately 150 million hectares) in order to demonstrate the proposed method. For the Atlantic Forest, landscapes that present high restoration effectiveness represent only 10% of the region, but contain approximately 15 million hectares that could be targeted for restoration actions (an area similar to today's remaining forest extent). The proposed method represents a practical way to both plan restoration actions and optimize biodiversity conservation efforts by focusing on landscapes that would result in greater conservation benefits. © 2013 Society for Ecological Restoration.

Geological and geophysical data integration for delimitation of mineralized areas in a supergene manganese deposits

Geophysical methods are widely used in mineral exploration. This paper discusses the results of geological and geophysical studies in supergene manganese deposits of southern Brazil. Mineralized zones as described in geological surveys were characterized as of low resistivity (20 Omega.m) and high chargeability (30ms), pattern found also in oxides and sulfite mineral deposits. Pseudo-3D modeling of geophysical data allowed mapping at several depths. A relationship between high chargeability and low resistivity may define a pattern for high grade gonditic manganese ore. Large areas of high chargeability and high resistivity may result in accumulation of manganese and iron hydroxides, due to weathering of the gonditic ore, dissolution, percolation and precipitation.

Assessment of the Removal Capacity, Tolerance, and Anatomical Adaptation of Different Plant Species to Benzene Contamination

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Applying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South America

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Stability, characterization and functionality of proton conducting NiO-BaCe0.85-xNbxY0.15O3-delta cermet anodes for IT-SOFC application

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Magnetism in spin models for depleted honeycomb-lattice iridates: Spin-glass order towards percolation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Mechanical, thermal, and barrier properties of methylcellulose/cellulose nanocrystals nanocomposites

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Effect of ion irradiation on the structural properties and hardness of a-C:H:Si:O:F films

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Effects of acetylation and acetylation-hydroxypropylation (dual-modification) on the properties of starch from Carioca bean (Phaseolus vulgaris L.)

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

Electrical and Thermal study of carbon nanotubes reinforced poly (phenylene sulfide) nanostructured composites

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Electrical, mechanical, and thermal analysis of natural rubber/polyaniline-DBSA composite

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)