Fabrication of binder-free ultrafine WC-6CO composites by coupled multi-physical fields activation technology

A novel sintering method, named as coupled multi-physical fields activation technology, has been introduced for the forming of various material powder systems. Compared with the conventional ones, this technique presents more advantages: lower sintering temperature, shorter forming time, and remarkable inhibition of the grains coarsening. In the study, the cylinders of Φ4.0mm×4.0mm had been formed with ultrafine WC-6Co powders. The relative properties of sintered WC-6Co cemented carbides, such as hardness and the microstructures, had been obtained. The study has shown that a relative density, 97.80%, of the formed samples, could been achieved when the case of temperature 850℃, heating rate 50℃/s, pressure 75MPa and Electro-heating loop 6 times, were used. More importantly, the circumscription for the growth of grain size of WC, attributed to the effect of electrical field, renders coupled multi-physical fields activation technology applicable for getting WC-6Co cemented carbides with fine grain size and good properties

A Ranking Distance Based Diversity Measure for Multiple Classifier Systems

International audienceMultiple classifier fusion belongs to the decision-level information fusion, which has been widely used in many pattern classification applications, especially when the single classifier is not competent. However, multiple classifier fusion can not assure the improvement of the classification accuracy. The diversity among those classifiers in the multiple classifier system (MCS) is crucial for improving the fused classification accuracy. Various diversity measures for MCS have been proposed, which are mainly based on the average sample-wise classification consistency between different member classifiers. In this paper, we propose to define the diversity between member classifiers from a different standpoint. If different member classifiers in an MCS are good at classifying different classes, i.e., there exist expert-classifiers for each concerned class, the improvement of the accuracy of classifier fusion can be expected. Each classifier has a ranking of classes in term of the classification accuracies, based on which, a new diversity measure is implemented using the ranking distance. A larger average ranking distance represents a higher diversity. The new proposed diversity measure is used together with each single classifier's performance on training samples to design and optimize the MCS. Experiments, simulations , and related analyses are provided to illustrate and validate our new proposed diversity measure

Sur la décombinaison de fonctions de croyance

International audienceThe evidence combination is a kind of decision-level information fusion in the theory of belief functions. Given two basic belief assignments (BBAs) originated from different sources, one can combine them using some combination rule, e.g., Dempster's rule to expect a better decision result. If one only has a combined BBA, how to determine the original two BBAs to combine? This can be considered as a defusion of information. This is useful, e.g., one can analyze the difference or dissimilarity between two different information sources based on the BBAs obtained using evidence decombination. Therefore, in this paper, we research on such a defusion in the theory of belief functions. We find that it is a well-posed problem if one original BBA and the combined BBA are both available, and it is an under-determined problem if both BBAs to combine are unknown. We propose an optimization-based approach for the evidence decombination according to the criteria of divergence maximization. Numerical examples are provided illustrate and verify our proposed decombination approach, which is expected to be used in applications such the difference analysis between information sources in information fusion systems when the original BBAs are discarded, and performance evaluation of combination rules

Microstructure evolution and surface cleaning of Cu nanoparticles during micro-fields activated sintering technology

For the purpose of extensive utilization of powder metallurgy to micro/nano- fabrication of materials, the micro gear was prepared by a novel method, named as micro- forming fields activated sintering technology (Micro-FAST). Surface-cleaning of particles, especially during the initial stage of sintering, is a crucial issue for the densification mechanism. However, up to date, the mechanism of surface-cleaning is too complicated to be known. In this paper, the process of surface-cleaning of Micro-FAST was studied, employing the high resolution transmission electron microscopy (HRTEM) for observation of microstructure of micro-particles. According to the evolution of the microstructure, surface-cleaning is mainly ascribed to the effect of electro-thermal focusing. The process of surface-cleaning is achieved through rearrangement of grains, formation of vacancy, migration of vacancy and enhancement of electro-thermal focusing

A new densification mechanism of copper powder sintered under an electrical field

A new sintering mechanism is revealed for copper powder sintered under the influence of an electrical field and a force field during the formation of microcomponents. Analysis of the microstructure and grain boundary evolution of the sintered samples showed that the disappearance of the interface at contact areas between particles is a continuous process which involves new grain formation and grain refinement during this innovative microsintering process. The densification process is therefore different from what is known in a conventional powder sintering process

A new hierarchical ranking aggregation method

International audienceThe purpose of ranking aggregation (or fusion) is to combine multiple rankings to a consensus one. In the ranking aggregation, some of the items’ preference orders are easy to distinguish, however, some others’ are not. To specifically compare the ambiguous items, i.e., the items whose aggregated preference orders are difficult to distinguish, is helpful for ranking aggregation. In this paper, a new hierarchical ranking aggregation method is proposed. The items whose preference orders are easy to distinguish are first divided into different ranking levels (i.e., the ordered items subsets), and the ambiguous items are put into the same ranking level. The items in high ranking levels are ranked higher than the items in low ranking levels in the aggregated ranking. Then the items in the same ranking level are further compared and divided into multiple ranking sub-levels. The aggregated ranking is generated hierarchically by dividing the same ranking levels’ (or sub-levels’) items into sub-levels until each sub-level only includes one item. Furthermore, we discuss the way of using the insertion sort method for merging the adjacent levels’ rankings to improve the quality of the aggregated ranking. The experiments and simulations show that our new hierarchical methods perform well in ranking aggregation

Effects of sintering temperature on the densification of WC-6Co cemented carbides sintered by coupled multi-physical-fields activated technology

Sample parts with WC-6Co cemented carbides were manufactured successfully with a novel method called coupled multi-physical-fields (electric field, temperature field and force field) activated sintering technology, using a Gleeble-1500D thermal simulation machine. Effects of sintering temperature on the densification, microstructures and hardness of samples were investigated. It was found that densification of the samples was enhanced with the increase of the sintering temperature and a relative density of as high as 98.76% achieved when a sintering temperature of 1200 °C was used. The particle size of the WC in sintered samples increased from 1.837 μm to 2.897 μm when the temperature was increased from 1000 °C to 1200 °C, resulting in the decrease of the hardness from HRC 63.5 to HRC 61.7. The presented work shows that, potentially, coupled multi-physical-fields activated technology is able to produce hard alloys to meet the engineering applications

Spatial-temporal traffic modeling with a fusion graph reconstructed by tensor decomposition

Accurate spatial-temporal traffic flow forecasting is essential for helping traffic managers to take control measures and drivers to choose the optimal travel routes. Recently, graph convolutional networks (GCNs) have been widely used in traffic flow prediction owing to their powerful ability to capture spatial-temporal dependencies. The design of the spatial-temporal graph adjacency matrix is a key to the success of GCNs, and it is still an open question. This paper proposes reconstructing the binary adjacency matrix via tensor decomposition, and a traffic flow forecasting method is proposed. First, we reformulate the spatial-temporal fusion graph adjacency matrix into a three-way adjacency tensor. Then, we reconstructed the adjacency tensor via Tucker decomposition, wherein more informative and global spatial-temporal dependencies are encoded. Finally, a Spatial-temporal Synchronous Graph Convolutional module for localized spatial-temporal correlations learning and a Dilated Convolution module for global correlations learning are assembled to aggregate and learn the comprehensive spatial-temporal dependencies of the road network. Experimental results on four open-access datasets demonstrate that the proposed model outperforms state-of-the-art approaches in terms of the prediction performance and computational cost.Comment: 11 pages, 8 figure

Kinematic Design, Analysis and Simulation of a Hybrid Robot with Terrain and Aerial Locomotion Capability

Having only one type of locomotion mechanism limits the stability and locomotion capability of a mobile robot on irregular terrain surfaces. One of the possible solution to this is combining more than one locomotion mechanisms in the robot. In this paper, robotic platform composed of a quadruped module for terrain locomotion and quadrotor module for aerial locomotion is introduced. This design is inspired by the way which birds are using their wings and legs for stability in slopped and uneven surfaces. The main idea is to combine the two systems in such a way that the strengths of both subsystems are used, and the weakness of the either systems are covered. The ability of the robot to reach the target position quickly and to avoid large terrestrial obstacles by flying expands its application in various areas of search and rescue. The same platform can be used for detailed 3D mapping and aerial mapping which are very helpful in rescue operations. In particular, this paper presents kinematic design, analysis and simulation of such a robotic system. Simulation and verification of results are done using MATLAB