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Zhang Y.,Hebei University of Technology | Zhang Y.,Hebei Control Engineering Research Center | Zhang J.,Hebei University of Technology | Zhou Y.,Hebei University of Technology | And 2 more authors.
Beijing Gongye Daxue Xuebao/Journal of Beijing University of Technology | Year: 2016

The online detection of the particle size is of great significance to realize the optimizing control of the grinding process and to improve the grade of concentrated ore and metal recovery rate. However, the problem of the present instrument is that the particle size cannot meet the real-time detection due to the long measurement period. Based on the characteristics of the typical two stage grinding circuits, this paper puts forward the grinding particle size soft sensor modeling method based on Gaussian process (GP), and the adaptive natural gradient (ANG) is applied to the super Gaussian process parameter optimization of the process. Then, the model of grinding particle size soft sensor was built based on ANG-GP. Soft sensor simulation experiment was carried out comparative study with the BP neural network and support vector machine model, respectively. Results show that this method is superior to the other methods, this method has high prediction accuracy, and it is effective to online detection of grinding particle size, which shows the effectiveness of this method. © 2016, Editorial Department of Journal of Beijing University of Technology. All right reserved.


Xu X.-Q.,Hebei University of Technology | Xu X.-Q.,Hebei Control Engineering Research Center | Yang P.,Hebei University of Technology | Yang P.,Hebei Control Engineering Research Center | And 6 more authors.
Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) | Year: 2011

In order to enhance the searching performance of robot hearing system in three-dimensional space and increase the adaptability in actual noisy environment, a multi-source target positioning system based on time delay of arrival (TDOA) was presented. The localization of target was carried out through the regular tetrahedron microphone array architecture on multi-source. The whole system was divided into four parts including the signal acquisition and preprocessing, blind source separation, multi-source positioning and robot control. Experiments results show that the design can make the robot find the position of many sources and reach the target rapidly and accurately.

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