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In order to obtain an orientation error of planar feature accurate, a method to evaluate it using convex hull is proposed. Firstly, a convex hull is established based on a set of measured points on the planar datum feature by the ...
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In order to obtain an orientation error of planar feature accurate, a method to evaluate it using convex hull is proposed. Firstly, a convex hull is established based on a set of measured points on the planar datum feature by the coordinate measurement machine (CMM). Then, the datum simulator is determined by the vertices of the convex hull with taking maximum material requirements (MMC) into consideration. Afterwards, allowable variation range of the locating features is derived with relative to the datum simulator. Finally, orientation error is evaluated based on convex hull constructed by measuring points of the location feature.
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摘要 :
In order to obtain an orientation error of planar feature accurate, a method to evaluate it using convex hull is proposed. Firstly, a convex hull is established based on a set of measured points on the planar datum feature by the ...
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In order to obtain an orientation error of planar feature accurate, a method to evaluate it using convex hull is proposed. Firstly, a convex hull is established based on a set of measured points on the planar datum feature by the coordinate measurement machine (CMM). Then, the datum simulator is determined by the vertices of the convex hull with taking maximum material requirements (MMC) into consideration. Afterwards, allowable variation range of the locating features is derived with relative to the datum simulator. Finally, orientation error is evaluated based on convex hull constructed by measuring points of the location feature.
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摘要 :
The extraction of a radio holography signal (RHS) is the precondition of shadow inverse synthetic aperture radar (SISAR) imaging. However, the target return usually has a relatively high carrier and narrow bandwidth when detecting...
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The extraction of a radio holography signal (RHS) is the precondition of shadow inverse synthetic aperture radar (SISAR) imaging. However, the target return usually has a relatively high carrier and narrow bandwidth when detecting ground moving targets, which makes it difficult to achieve the baseband signal with synchronous demodulation in a conventional Forward Scatter Radar (FSR) system. Thus a new method for RHS reconstruction is put forward in this paper. The method consists of envelope detection, segmental Hilbert transform and amplitude compensation. With these steps the target RHS can be accurately reconstructed and target profiles can be extracted via the SISAR algorithm. The effectiveness of this method is verified with both simulation and experimental data processing results.
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Smart primary equipment as typical components and structure basis of intelligent substation. Intelligent components which is the core component of smart primary equipment, will be the access platform of various smart unit, and sma...
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Smart primary equipment as typical components and structure basis of intelligent substation. Intelligent components which is the core component of smart primary equipment, will be the access platform of various smart unit, and smart unit will be the applied terminal of specific intelligence technology. This paper designed a general intelligent component platform, the module structure and configuration program of the intelligence components are given. Meanwhile, the use of The real-time operating systems was used to manage the cooperative work of intelligence unit, so as to meet the various requirements of the general intelligent equipment. Finally, the real-time validation of the smart component platform was carried out by the GOOSE message. The results meet the requirements of IEC61850 standard and provide a reference for the further research and development of intelligent components.
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摘要 :
Smart primary equipment as typical components and structure basis of intelligent substation. Intelligent components which is the core component of smart primary equipment, will be the access platform of various smart unit, and sma...
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Smart primary equipment as typical components and structure basis of intelligent substation. Intelligent components which is the core component of smart primary equipment, will be the access platform of various smart unit, and smart unit will be the applied terminal of specific intelligence technology. This paper designed a general intelligent component platform, the module structure and configuration program of the intelligence components are given. Meanwhile, the use of The real-time operating systems was used to manage the cooperative work of intelligence unit, so as to meet the various requirements of the general intelligent equipment. Finally, the real-time validation of the smart component platform was carried out by the GOOSE message. The results meet the requirements of IEC61850 standard and provide a reference for the further research and development of intelligent components.
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Aiming at the special request of neural network for safety assessment of coal mines, in this paper, the improvement is made for the mathematics model of training and studying function combining with analyses of studying process of...
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Aiming at the special request of neural network for safety assessment of coal mines, in this paper, the improvement is made for the mathematics model of training and studying function combining with analyses of studying process of the neural network, by which the assessment network can get a simulation output more steadily when the input-sample data for training of the neural network is limited, and the stability and practicability of the neural network are advanced greatly in the safety assessment for the coal mines.
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摘要 :
Aiming at the special request of neural network for safety assessment of coal mines, in this paper, the improvement is made for the mathematics model of training and studying function combining with analyses of studying process of...
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Aiming at the special request of neural network for safety assessment of coal mines, in this paper, the improvement is made for the mathematics model of training and studying function combining with analyses of studying process of the neural network, by which the assessment network can get a simulation output more steadily when the input-sample data for training of the neural network is limited, and the stability and practicability of the neural network are advanced greatly in the safety assessment for the coal mines.
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摘要 :
With the development of unmanned aerial vehicle, the spectrum resources for communication become increasingly scarce. Spectrum sharing can alleviate this problem effectively, and spectrum prediction is the key step. The previous s...
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With the development of unmanned aerial vehicle, the spectrum resources for communication become increasingly scarce. Spectrum sharing can alleviate this problem effectively, and spectrum prediction is the key step. The previous spectrum prediction models only consider the time domain variation and ignore the time-frequency correlation. In order to change this defect, we propose a new spectrum prediction model, which extends the traditional one-dimensional HMM model to the two dimensions of time-frequency. In addition, homotopy method is introduced to solve the strict dependence on historical spectrum data during UAV flight. Through simulation experiments, we verify that the new two-dimensional model has better prediction effect than the one-dimensional model, and has a good performance in the absence of sufficient prior information.
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With the number of antennas and users increases significantly, and the complexity of channel estimation and pilot overhead increase continuously in Massive MIMO systems. To solve this problem, in this paper, a doubly selective cha...
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With the number of antennas and users increases significantly, and the complexity of channel estimation and pilot overhead increase continuously in Massive MIMO systems. To solve this problem, in this paper, a doubly selective channel estimation method based on distributed compressed sensing (DCS) is proposed for large-scale MIMO system. Firstly, the problem of doubly selective channel estimation is formulated under the framework of DCS. Then the joint sparsity of doubly selective channel is theoretically proved by showing that the channel coefficients in transformed domain have the spatial correlation between the adjacent antennas. By exploiting the joint sparsity of transformed domain coefficients corresponding to the channel between different transmit and receive antennas, the channel coefficients is reconstructed by distributed compressed reconstruction algorithm. The simulation results show that the proposed approach can reconstruct the original channel coefficient effectively with significantly reduced pilot overhead.
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摘要 :
With the number of antennas and users increases significantly, and the complexity of channel estimation and pilot overhead increase continuously in Massive MIMO systems. To solve this problem, in this paper, a doubly selective cha...
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With the number of antennas and users increases significantly, and the complexity of channel estimation and pilot overhead increase continuously in Massive MIMO systems. To solve this problem, in this paper, a doubly selective channel estimation method based on distributed compressed sensing (DCS) is proposed for large-scale MIMO system. Firstly, the problem of doubly selective channel estimation is formulated under the framework of DCS. Then the joint sparsity of doubly selective channel is theoretically proved by showing that the channel coefficients in transformed domain have the spatial correlation between the adjacent antennas. By exploiting the joint sparsity of transformed domain coefficients corresponding to the channel between different transmit and receive antennas, the channel coefficients is reconstructed by distributed compressed reconstruction algorithm. The simulation results show that the proposed approach can reconstruct the original channel coefficient effectively with significantly reduced pilot overhead.
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