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Eddy current sensor with online non-contact measurement, no coupling medium and high sensitivity etc, is widely used in engineering. In this paper, based on the eddy current testing principle, the eddy current sensor is modeled in ANSYS software to complete the optimization design. The article research on the method of flaw recognition after extracting the detection signal features and analysis the impact of the flaw size on the detection signal, so as to provide a theoretical method of qualitative detection in the practical application.

Inverse dynamics problem of large-displacement motion simulator is solved by Roberson-Wittenburg method. Simulation graphs plotted by matlab prove the validity of solution. This paper can be used in control studies of motion simulator.

In order to study the elastic motion stability of flexible manipulator arm , to compute the maximum dynamic allowable payload , the partial differential equation of elastic motion of the flexible manipulator arm is solved using the method of Laplace transformation , the dynamic model of flexible manipulator arm carried addition mass on its end position is established ,simplified and truncated using Lagrange equation . the state space expression is established with the state variable and control input and output variable designated , the elastic motion stability rule is built upon and simplified using Lyapunov stability theory . The influence of the end position addition mass and articulation rotational inertia of flexible manipulator arm on its elastic motion stability is analyzed using the stability rule , and the dynamic maximum allowable payload of flexible manipulator arm on its end position is computed in order to guarantee its elastic motion stability . this study is important to the design of robot mechanical manipulator and corresponding drive control system .

Different cloud services need different resources, how to use the resources efficiently has become one of the hot research topics about cloud computing. In order to improve the utilization of resources in cloud, this paper proposes an automatic cloud service classification method, which uses an artificial neural network to predict the type of service resource requirements, and classifies services based on the predicting result. In this paper, we do classification experiments on three groups of Web services on Web service site. The experiment results show that, the method is effective and can predict the type of resource requirements for Web services automatically.