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Xu H.,Shenyang University of Technology | Ren J.,Shenyang University of Technology | Li B.-Y.,SIASUN Robot and Automation Co.
Sensors and Transducers | Year: 2014

In terms of parameters selection and detection in measurement of Ultra Wide Bandwidth stepped frequency bioradar model, stepped frequency interval of emission signal, frequency bandwidth of the intermediate filter (IFBW) and sampling integration time of echo signal are discussed in this paper. These factors impact imaging and human respiratory detection. A novel calculation method of parameters is proposed based on both theoretical and experimental results, which are Fourier transformation analysis method and empirical data, respectively. The stepped frequency interval of emission signal is 14.15 MHz, IFBW<3 kHz and the sampling integration time of echo signal is 15 s which has been shown that reasonable parameter settings can improve image resolution and the echo signal to noise ratio significantly. © 2014 IFSA Publishing, S. L. Source


Sun J.,Shenyang Jianzhu University | Li J.,Shenyang Jianzhu University | Song J.,Shenyang Jianzhu University | Feng W.-T.,SIASUN Robot and Automation Co.
Advanced Materials Research | Year: 2010

In order to improve the horizontal moving acceleration of stackers, the paper proposes a horizontal moving mechanism called "side-wheel operating simultaneously" and presents the calculating method of its main parameters. The FEM model of improved stacker's rail system is established by using software ANSYS and the analyzing results show that the design meets the requirement of high-speed & high-acceleration for stackers. © (2010) Trans Tech Publications. Source


Wang K.,Zhejiang University | Wang K.,Eaton Corporate Research and Technology China | Yao W.,Zhejiang University | Chen B.,Zhejiang University | And 3 more authors.
IEEE Transactions on Industrial Electronics | Year: 2015

It is necessary to obtain accurate knowledge about the magnetizing curve of an induction machine so that the magnetizing inductance can be updated according to different flux references for either efficiency optimization or field weakening control. This paper proposes a computational saving method to obtain a one-to-one correspondence magnetizing curve without the need for conventional curve-fitting strategies, which require the assumption of explicit analytical curve functions. A detailed comparison between the proposed method and the conventional curve-fitting method has been done. It shows great accuracy improvements of this proposed method. The identification is easy to implement with high precision while maintaining the motor at standstill. No additional sensor devices are needed except the sensors carried by the drive itself. This proposed method is verified by simulation. Further experimental results of this method are utilized in a real control strategy with a 2.2-kW 50-Hz 4-pole induction motor to confirm its validity and feasibility. © 1982-2012 IEEE. Source


Zhang Y.,Northeastern University China | Zhang Y.,SIASUN Robot and Automation Co. | Xiang S.,Northeastern University China | Fu W.,Northeastern University China | Wei D.,Northeastern University China
International Journal of Distributed Sensor Networks | Year: 2014

In recent years, collinearity theory is widely used in large-scale sensor network. When the anchor nodes are located at almost a straight line, the collinearity phenomenon will happen and usually cause negative influence on positioning accuracy. From detailed analysis of the relation between DV-Hop localization error and the collinearity, we proposed to select the anchor nodes which can meet the condition of hop count threshold and collinearity to participate in the localization procedure. Since there is uncertain situation that the anchor node's region is hard to be decided for the sensor nodes in one hop area, Voronoi diagram is adopted to divide the sensor network into several regions. Then, we can get the anchor node information in each Voronoi polygon. With this information and the collinearity condition, we can estimate the unknown node's position with relatively higher accuracy. Compared with the traditional DV-Hop and collinearity algorithm, our proposed algorithm can get better positioning accuracy in both homogeneous network and anisotropic network. © 2014 Yunzhou Zhang et al. Source


Ren J.,Shenyang University of Technology | Xu H.,Shenyang University of Technology | Li B.,Shenyang University of Technology | Li B.,SIASUN Robot and Automation Co. | Zhou C.,Shenyang University of Technology
Gaojishu Tongxin/Chinese High Technology Letters | Year: 2014

The relationship between the key parameter sparsity and the sampling rate in the compressive sensing (CS) theory was studied for the determination of the CS sampling rate. The minimum number of sampling times in a CS sampling process was carried out and proved theoretically and experimentally. In the two-dimensional image recovery process, the number of sampling times, called M, was scanned, and the parameters including peak signal to noise ratio (PSNR), mean square error (MSE) and the similarity, were used to test the effect of image recovery evaluation to achieve the low sampling rate. Two images were used in the restoration experiment, and the results show that the theoretical derivation is correct and practical, and it is of significance for future application of compressive sensing in signal sampling. Source

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