A novel adaptive temporal-spatial information fusion model based on Dempster-Shafer evidence theory

In the field of target recognition based on the temporal-spatial information fusion,evidence the-ory has received extensive attention.To achieve accurate and efficient target recognition by the evi-dence theory,an adaptive temporal-spatial information fusion model is proposed.Firstly,an adaptive evaluation correction mechanism is constructed by the evidence distance and Deng entropy,which realizes the credibility discrimination and adaptive correction of the spatial evidence.Secondly,the credibility decay operator is introduced to obtain the dynamic credibility of temporal evidence.Finally,the sequential combination of temporal-spatial evidences is achieved by Shafer’s discount criterion and Dempster’s combination rule.The simulation results show that the proposed method not only considers the dynamic and sequential characteristics of the temporal-spatial evidences com-bination,but also has a strong conflict information processing capability,which provides a new refer-ence for the field of temporal-spatial information fusion.

Positioning method of a cylindrical cutter for ruled surface machining based on minimizing one-sided Hausdorff distance

Motivated by the definition of the machining errors induced by tool path planning methods, a mapping curve of the tool axis of a cylindrical cutter is constructed on the tool surface. The mapping curve is a typical one that can be used to express the closeness between the tool surface and the surface to be machined. A novel tool path planning method is proposed for flank or plunge milling ruled surfaces based on the minimization of the one-sided Hausdorff distance （HD） from the mapping curve to the surface to be machined. It is a nonlinear optimization problem in best uniform approximation （BUA） or Chebyshev sense. A mathematical programming model for computing the minimum one-sided HD is proposed. The linearization method of the programming model is provided and the final optimal solutions are obtained by simplex method. The effectiveness of the proposed BUA method is verified by two numerical examples and compared with the least squares （LS） and double point offset （DPO） methods. The variation in tool orientation induced by the optimization of the tool positions is also evaluated.

An empirical method for improving accuracy of human eye temperature measured by uncooled infrared thermal imager

In order to reduce the temperature measurement error with the uncooled infrared thermal imager, experiments were conducted to evaluate the effects of environment temperature and measurement distance on the measurement error of human eye temperature. First, the forehead temperature was used as an intermediate variable to obtain the actual temperature of human eyes. Then, the effects of environment temperature and measurement distance on the temperature measurement were separately analyzed. Finally, an empirical model was established to correlate actual eye temperature with the measured temperature, environment temperature, and measurement distance. To verify the formula, three different environment temperatures were tested at different distances. The measurement errors were substantially reduced using the empirical model for temperature correction. The results show that this method can effectively improve the accuracy of temperature measurement using the infrared thermal imager.