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A novel magnetostrictive rotary motor using Terfenol-D (Tb 0.3 Dy 0.7 Fe 1.9 ) material as the driving element is developed. The motor is constructed of three giant magnetostrictive actuators connected to a stator frame and a rotor is placed in the center of the stator. The small movement of the magnetostrictive actuator is scaled to three times by using flexible flexure hinges and a specially designed mechanism is used to combine three such actuators to form a pure rotation movement and this movement is used to drive the rotor of the motor. A prototype of this research motor is made and a common three-phase alternating current is used to drive it. Preliminary experiments are also carried out in the laboratory of

In recent years, there has been widespread concern about the problems of stream data query both academic and industrial communities. The problems obtained some results. At the same time, big data stream brings great benefits for information society. Information query about stream data form has also brought crucial challenges. However, it is seldom about the research of big data stream query in network space. This paper analyzes the characteristics of stream data query in massive data, discusses the challenges and research issues of data stream for big data query. Finally the works for the data stream query are surveyed.

Abstract:In the target classification based on belief function theory, sensor reliability evaluation has two basic issues: reasonable dissimilarity measure among evidences, and adaptive combination of static and dynamic discounting. One solution to the two issues has been proposed here. Firstly, an improved dissimilarity measure based on dualistic exponential function has been designed. We assess the static reliability from a training set by the local decision of each sensor and the dissimilarity measure among evidences. The dynamic reliability factors are obtained from each test target using the dissimilarity measure between the output information of each sensor and the consensus. Secondly, an adaptive combination method of static and dynamic discounting has been introduced. We adopt Parzen-window to estimate the matching degree of current performance and static performance for the sensor. Through fuzzy theory, the fusion system can realize self-learning and self-adapting with the sensor performance changing. Experiments conducted on real databases demonstrate that our proposed scheme performs better in target classification under different target conditions compared with other methods.

Lubrication failures of axle box bearings can lead to accidents, such as bearing burnout and hot axle cutting. Presently, the modeling of the vehicle-track system dynamics rarely considers the nonlinear contact load of axle box bearings, and this leads to imperfection in the vehicle-track system dynamics calculation. And then, the load distribution and lubrication characteristics of axle box bearings are difficult to obtain. Therefore, in this paper, we fully consider the time-varying nonlinear contact load of bearings and track irregularity in establishing the bearing-wheel-rail system coupling-dynamics model. The dynamic response of axle box bearings is obtained by taking the vertical, strong impact-time-varying load on the carrying saddles as the external excitation. The load-balance equation of dynamic pressure lubrication is then obtained, according to the slicing method of bearing rollers. Finally, the elastohydrodynamic lubrication (EHL) model of axle box bearings is established considering thermal and scale effects. The results show that the central film thickness under thermal EHL was decreased by 13.61% compared with that under isothermal EHL. As the velocity of the contact pair increases, the thickness difference between thermal and isothermal EHL became larger. Thermal effects should be considered in the EHL model, in order to truly reflect the characteristics of EHL under a high speed.