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Stress concentration and large displacements are usual problems in the components of the structure of agricultural machinery such harvesters coffee, and that finite element method (FEM) can be a tool to minimize its effects. The goal of this paper is to get results of stresses and displacements of a coffee harvester structure by using FEM for static simulation. The main parts of the coffee harvester analyzed were: engine frame, body right and left sides, front and rear end, main beam, coffee reservoir, wheels and fuel tank. Two different design concepts of a coffee harvester machine were analyzed (structure with rear wheels aligned and misaligned) and the results were compared. It was observed that the model with rear wheels misaligned showed maximum displacement lower than the model with rear wheels aligned. Although higher stress was found in the rear wheels misaligned, it was observed that average stresses for the misaligned wheels design were lower in most structural components analyzed. Based on FEM results, the coffee harvester machine with misaligned rear wheels was built and subjected to operational tests without showing any structural failure.

A method for detecting and classifying faults in an aluminum cantilever beam is proposed in this paper. The method uses features based on second-, third-and fourthorder statistics, which are extracted from the vibration signals generated by the cantilever beam. Fisher's discriminant ratio (FDR) is used for feature selection, and an artificial neural network is used for fault detection and classification. Three different degrees of faults (low, medium and high) were applied to the cantilever beam, and the proposed pattern recognition system was able to classify the faults, reaching performances ranging from 88 to 100 %. Moreover, the use of higher-order statistics-based features combined with FDR led to a compact feature space and provided satisfactory results.

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This paper presents the main applications of electric vehicles in rural areas, pointing out the trends and challenges for the future. Technological conditions and difficulties faced by the industry for a wide dissemination of this technology are discussed. The paper described the main researches with proposals to overcome the problems of implementing electric tractors, as supply and electricity storage. Technical and economic comparisons between conventional internal combustion tractors and electric tractors are also presented and discussed. The paper showed the existence of barriers to the implementation of electric vehicles in rural areas, as well as the need for batteries technological evolution, which have high costs and for that reason they are very heavy for these purposes, but there are already systems that can be applied to minimize dependence of fossil fuels in this sector and increase the use of sustainable energy.

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PIV (particle image velocimetry) has been spreading in studies that use the movement of particles to monitor the displacement of an object or the flow of a fluid by means of velocity vectors using optical techniques and second order statistics. PIV is also known as laser speckle velocimetry when associated with speckle patterns. This technique has been used in works involving fluids, in general, building a map of velocity vectors representing the flow under analysis. This paper presents an approach by using PIV associated to speckle patterns for deformation measurements in a cantilever beam (ASTM A36 steel), one of the most common examples used in civil engineering, without the introduction of external particles. Results showed that the difference between PIV associated to speckle patterns and the analytic displacement values is increased along the beam length for a load of 1.96 N as an evidence of sensitivity of the proposed measurement method. This indicates that PIV is also capable for detecting displacement fields associated with laser speckle patterns in solid mechanics generating a map of deformation as an additional option for non-destructive tests.