892 resultados para Acoustic Emission, Source Separation, Condition Monitoring, Diesel Engines, Injector Faults


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

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

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

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Considering the constant technological developments in the aeronautical, space, automotive, shipbuilding, nuclear and petrochemical fields, among others, the use of materials with high strength mechanical capabilities at high temperatures has been increasingly used. Among the materials that meet the mechanical strength and corrosion properties at temperatures around 815 degrees C one can find the nickel base alloy Pyromet 31V (SAE HEV8). This alloy is commonly applied in the manufacturing of high power diesel engines exhaust valves where it is required high resistance to sulphide, corrosion and good resistance to creep. However, due to its high mechanical strength and low thermal conductivity its machinability is made difficult, creating major challenges in the analysis of the best combinations among machining parameters and cutting tools to be used. Its low thermal conductivity results in a concentration of heat at high temperatures in the interfaces of workpiece-tool and tool-chip, consequently accelerating the tools wearing and increasing production costs. This work aimed to study the machinability, using the carbide coated and uncoated tools, of the hot-rolled Pyromet 31V alloy with hardness between 41.5 and 42.5 HRC. The nickel base alloy used consists essentially of the following components: 56.5% Ni, 22.5% Cr, 2,2% Ti, 0,04% C, 1,2% Al, 0.85% Nb and the rest of iron. Through the turning of this alloy we able to analyze the working mechanisms of wear on tools and evaluate the roughness provided on the cutting parameters used. The tests were performed on a CNC lathe machine using the coated carbide tool TNMG 160408-23 Class 1005 (ISO S15) and uncoated tools TNMG 160408-23 Class H13A (ISO S15). Cutting fluid was used so abundantly and cutting speeds were fixed in 75 and 90 m/min. to feed rates that ranged from 0.12, 0.15, 0.18 and 0.21 mm/rev, and cutting depth of 0.8mm. The results of the comparison between uncoated tools and coated ones presented a machined length of just 30% to the first in relation to the performance of the second. The coated tools has obtained its best result for both 75 and 90 m/min. with feed rate of 0.15 mm/rev, unlike the uncoated tool which obtained its better results to 0.12 mm/rev.

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Condition monitoring is used to increase machinery availability and machinery performance, reducing consequential damage, increasing machine life, reducing spare parts inventories, and reducing breakdown maintenance. An efficient real time vibration measurement and analysis instruments is capable of providing warning and predicting faults at early stages. In this paper, a new methodology for the implementation of vibration measurement and analysis instruments in real time based on circuit architecture mapped from a MATLAB/Simulink model is presented. In this study, signal processing applications such as FIR filters and fast Fourier transform are treated as systems, which are implemented in hardware using a system generator toolbox, which translates a Simulink model in a hardware description language - HDL for FPGA implementations.

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

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Composites, made of lead zirconate titanate (PZT) ceramic powder and castor oil-based polyurethane (PU), were prepared in the film form. The films were obtained in the thickness range 100-300 mum using up to 50/50 vol.% of ceramic. Another composite (PZT/C/PU) was obtained by adding a small amount (1.0 vol.%) of graphite (C) to the PZT/PU composite. By increasing the conductivity of PU-containing graphite, polarization of PZT could be carried out with better efficiency. A comparison of piezo- and pyroelectric activities and spatial distribution of polarization between graphite doped and undoped composites reveal the advantages of using semiconductor filler. These composites were used as sensors to detect acoustic emission (AE). The detection was made using two simulated sources of AE, i.e., ball bearing drop and pencil lead break. PZT/C/PU composite was able to detect both flexural and extensional components of wave vibration. (C) 2002 Elsevier B.V. B.V. All rights reserved.

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In this article some considerations obtained during the utilization of rotor response analysis techniques in hydraulic powerplants are discussed. An applied research work was carried out in two hydraulic turbines analysing the rotor response both theoretically and experimentally. A developed mathematical model was used to simulate the rotordynamic behaviour of Francis and Kaplan turbines. The main dynamical effects that appear during the operation of the machines are discussed too. A series of measurements were carried out in the turbines using impact hammers to determine the modal behaviour of the units. The tests were carried out with the machine still and in operation. Some results and the comparison with the theory is presented in this article. The improved theoretical model was used for a sensitivity analysis of the different bearings to the main excitations that fake place during the machine operation. From this analysis, the best measuring points for condition monitoring were determined.

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The main purpose of this work is the development of computational tools in order to assist the on-line automatic detection of burn in the surface grinding process. Most of the parameters currently employed in the burning recognition (DPO, FKS, DPKS, DIFP, among others) do not incorporate routines for automatic selection of the grinding passes, therefore, requiring the user's interference for the choice of the active region. Several methods were employed in the passes extraction; however, those with the best results are presented in this article. Tests carried out in a surface-grinding machine have shown the success of the algorithms developed for pass extraction. Copyright © 2007 by ABCM.

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Grinding - the final machining process of a workpiece - requires large amounts of cutting fluids for the lubrication, cooling and removal of chips. These fluids are highly aggressive to the environment. With the technological advances of recent years, the worldwide trend is to produce increasingly sophisticated components with very strict geometric and dimensional tolerances, good surface finish, at low costs, and particularly without damaging the environment. The latter requirement can be achieved by recycling cutting fluids, which is a costly solution, or by drastically reducing the amount of cutting fluids employed in the grinding process. This alternative was investigated here by varying the plunge velocity in the plunge cylindrical grinding of ABNT D6 steel, rationalizing the application of two cutting fluids and using a superabrasive CBN (cubic boron nitride) grinding wheel with vitrified binder to evaluate the output parameters of tangential cutting force, acoustic emission, roughness, roundness, tool wear, residual stress and surface integrity, using scanning electron microscopy (SEM) to examine the test specimens. The performance of the cutting fluid, grinding wheel and plunge velocity were analyzed to identify the best machining conditions which allowed for a reduction of the cutting fluid volume, reducing the machining time without impairing the geometric and dimensional parameters, and the surface finish and integrity of the machined components.

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The present paper evaluates meta-heuristic approaches to solve a soft drink industry problem. This problem is motivated by a real situation found in soft drink companies, where the lot sizing and scheduling of raw materials in tanks and products in lines must be simultaneously determined. Tabu search, threshold accepting and genetic algorithms are used as procedures to solve the problem at hand. The methods are evaluated with a set of instance already available for this problem. This paper also proposes a new set of complex instances. The computational results comparing these approaches are reported. © 2008 IEEE.

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This paper studies the use of different population structures in a Genetic Algorithm (GA) applied to lot sizing and scheduling problems. The population approaches are divided into two types: single-population and multi-population. The first type has a non-structured single population. The multi-population type presents non-structured and structured populations organized in binary and ternary trees. Each population approach is tested on lot sizing and scheduling problems found in soft drink companies. These problems have two interdependent levels with decisions concerning raw material storage and soft drink bottling. The challenge is to simultaneously determine the lot sizing and scheduling of raw materials in tanks and products in lines. Computational results are reported allowing determining the better population structure for the set of problem instances evaluated. Copyright 2008 ACM.

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This paper discusses the investigation of an abrasive process for finishing flat workpieces, based on the combination of important grinding and lapping characteristics. Instead of loose abrasive grains between the workpiece and the lapping plate, a resinoid grinding wheel of hot-pressed silicon carbide is placed on the plate of a device resembling a lapping machine. The resin bond grinding wheel is dressed with a single-point diamond. In addition to keeping the plate flat, dressing also plays the role of interfering in the behavior of the process by varying the overlap factor (Ud). It was found that the studied process simplify the set-up and can be controlled more easily than in lapping, whose is a painstaking process. The surface roughness and flatness deviation proved comparable to those of lapping, or even finer than it, with the additional advantage of a less contaminated workpiece surface with a shiny appearance. The process was also monitored by acoustic emission (AE), which indicates to be a promissing and suitable technique for use in this process. Copyright © 2008 by ASME.

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This paper introduces a methodology for predicting the surface roughness of advanced ceramics using Adaptive Neuro-Fuzzy Inference System (ANFIS). To this end, a grinding machine was used, equipped with an acoustic emission sensor and a power transducer connected to the electric motor rotating the diamond grinding wheel. The alumina workpieces used in this work were pressed and sintered into rectangular bars. Acoustic emission and cutting power signals were collected during the tests and digitally processed to calculate the mean, standard deviation, and two other statistical data. These statistics, as well the root mean square of the acoustic emission and cutting power signals were used as input data for ANFIS. The output values of surface roughness (measured during the tests) were implemented for training and validation of the model. The results indicated that an ANFIS network is an excellent tool when applied to predict the surface roughness of ceramic workpieces in the grinding process.