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As the core technology of deep learning, convolutional neural networks have been widely applied in a variety of computer vision tasks and have achieved state-of-the-art performance. However, it’s difficult and inefficient for them to deal with high dimensional image signals due to the dramatic increase of training parameters. In this paper, we present a lightweight and efficient MS-Net for the multi-dimensional(MD) image processing, which provides a promising way to handle MD images, especially for devices with limited computational capacity. It takes advantage of a series of one dimensional convolution kernels and introduces a separable structure in the ConvNet throughout the learning process to handle MD image signals. Meanwhile, multiple group convolutions with kernel size 1 × 1 are used to extract channel information. Then the information of each dimension and channel is fused by a fusion module to extract the complete image features. Thus the proposed MS-Net significantly reduces the training complexity, parameters and memory cost. The proposed MS-Net is evaluated on both 2D and 3D benchmarks CIFAR-10, CIFAR-100 and KTH. Extensive experimental results show that the MS-Net achieves competitive performance with greatly reduced computational and memory cost compared with the state-of-the-art ConvNet models.

The optimal design of the magnetorheological (MR) dampers is important to meet the engineering applications and obtain better performance compared with the conventional design methods. In this chapter, a multiobjective optimization method, based on Parallel-plate Model and genetic algorithms, is proposed to obtain the optimal structural parameters for the MR damper. The algorithm indicates that the most important influential factors of the damping force and its adjustable ratio are the gap between the cylinder and piston and the effective length of the piston. The results demonstrate the effectiveness and feasibility of the proposed optimization approach.

Magnetorheological (MR) damper is a kind of superiorly semi-active control device whose response time directly affects its vibration reduction. This paper analyzed the mechanism of response time through magnetorheological fluid, control electric circuit and magnetic circuit, and the flexibility of mechanism. Based on above analysis, response time of MR damper was tested using the Material Testing System (MTS) 810 when electric current, excited frequency and excited amplitude were changing. And the experimental data were analyzed with the mathematical statistical method and the variation tendencies of the response time following the changing of electric current and velocity were shown, which could provide a reference for the improvement of MR dampers and the design of vibration control algorithm.