The present paper proposes an automated Laser-Induced Breakdown Spectroscopy （LIBS） analytical test system, which consists of a LIBS measurement and control platform based on a modular design concept, and a LIBS qua...The present paper proposes an automated Laser-Induced Breakdown Spectroscopy （LIBS） analytical test system, which consists of a LIBS measurement and control platform based on a modular design concept, and a LIBS qualitative spectrum analysis software and is developed in C#. The platform provides flexible interfacing and automated control; it is compatible with different manufacturer component models and is constructed in modularized form for easy ex- pandability. During peak identification, a more robust peak identification method with improved stability in peak identification has been achieved by applying additional smoothing on the slope obtained by calculation before peak identification. For the purpose of element identification, an improved main lines analysis method, which detects all elements on the spectral peak to avoid omission of certain elements without strong spectral lines, is applied to element identification in the tested LIBS samples. This method also increases the identification speed. In this paper, actual applications have been carried out. According to tests, the analytical test system is compatible with components of various models made by different manufacturers. It can automatically control components to get experimental data and conduct filtering, peak identification and qualitative analysis, etc. on spectral data.展开更多
Unlike the traditional traction power supply system which enables the electrified railway traction sub- station to be connected to power grid in a way of phase rotation, a new generation traction power supply system w...Unlike the traditional traction power supply system which enables the electrified railway traction sub- station to be connected to power grid in a way of phase rotation, a new generation traction power supply system without phase splits is proposed in this paper. Three key techniques used in this system have been discussed. First, a combined co-phase traction power supply system is applied at traction substations for compensating negative sequence current and eliminating phase splits at exits of substations; design method and procedure for this system are presented. Second, a new bilateral traction power supply technology is proposed to eliminate the phase split at section post and reduce the influence of equalizing current on the power grid. Meanwhile, power factor should be adjusted to ensure a proper voltage level of the traction network. Third, a seg- mental power supply technology of traction network is used to divide the power supply arms into several segments, and the synchronous measurement and control technology is applied to diagnose faults and their locations quickly and accurately. Thus, the fault impact can be limited to a min- imum degree. In addition, the economy and reliability of the new generation traction power supply system are analyzed.展开更多
This study presents a radio frequency(RF)fingerprint identification method combining a convolutional neural network(CNN)and gated recurrent unit(GRU)network to identify measurement and control signals.The proposed alg...This study presents a radio frequency(RF)fingerprint identification method combining a convolutional neural network(CNN)and gated recurrent unit(GRU)network to identify measurement and control signals.The proposed algorithm(CNN-GRU)uses a convolutional layer to extract the IQ-related learning timing features.A GRU network extracts timing features at a deeper level before outputting the final identification results.The number of parameters and the algorithm’s complexity are reduced by optimizing the convolutional layer structure and replacing multiple fully-connected layers with gated cyclic units.Simulation experiments show that the algorithm achieves an average identification accuracy of 84.74% at a -10 dB to 20 dB signal-to-noise ratio(SNR)with fewer parameters and less computation than a network model with the same identification rate in a software radio dataset containing multiple USRP X310s from the same manufacturer,with fewer parameters and less computation than a network model with the same identification rate.The algorithm is used to identify measurement and control signals and ensure the security of the measurement and control link with theoretical and engineering applications.展开更多
基金supported by the National Major Scientific Instruments and Equipment Development Special Funds of China(No.2011YQ030113)
文摘The present paper proposes an automated Laser-Induced Breakdown Spectroscopy （LIBS） analytical test system, which consists of a LIBS measurement and control platform based on a modular design concept, and a LIBS qualitative spectrum analysis software and is developed in C#. The platform provides flexible interfacing and automated control; it is compatible with different manufacturer component models and is constructed in modularized form for easy ex- pandability. During peak identification, a more robust peak identification method with improved stability in peak identification has been achieved by applying additional smoothing on the slope obtained by calculation before peak identification. For the purpose of element identification, an improved main lines analysis method, which detects all elements on the spectral peak to avoid omission of certain elements without strong spectral lines, is applied to element identification in the tested LIBS samples. This method also increases the identification speed. In this paper, actual applications have been carried out. According to tests, the analytical test system is compatible with components of various models made by different manufacturers. It can automatically control components to get experimental data and conduct filtering, peak identification and qualitative analysis, etc. on spectral data.
基金supported by the National Natural Science Funds of China (Nos. 51307143 and 51307142)Technology Research and Development Program of China Railway Corporation (No. 2014J009-B)
文摘Unlike the traditional traction power supply system which enables the electrified railway traction sub- station to be connected to power grid in a way of phase rotation, a new generation traction power supply system without phase splits is proposed in this paper. Three key techniques used in this system have been discussed. First, a combined co-phase traction power supply system is applied at traction substations for compensating negative sequence current and eliminating phase splits at exits of substations; design method and procedure for this system are presented. Second, a new bilateral traction power supply technology is proposed to eliminate the phase split at section post and reduce the influence of equalizing current on the power grid. Meanwhile, power factor should be adjusted to ensure a proper voltage level of the traction network. Third, a seg- mental power supply technology of traction network is used to divide the power supply arms into several segments, and the synchronous measurement and control technology is applied to diagnose faults and their locations quickly and accurately. Thus, the fault impact can be limited to a min- imum degree. In addition, the economy and reliability of the new generation traction power supply system are analyzed.
基金supported by the National Natural Science Foundation of China(No.62027801).
文摘This study presents a radio frequency(RF)fingerprint identification method combining a convolutional neural network(CNN)and gated recurrent unit(GRU)network to identify measurement and control signals.The proposed algorithm(CNN-GRU)uses a convolutional layer to extract the IQ-related learning timing features.A GRU network extracts timing features at a deeper level before outputting the final identification results.The number of parameters and the algorithm’s complexity are reduced by optimizing the convolutional layer structure and replacing multiple fully-connected layers with gated cyclic units.Simulation experiments show that the algorithm achieves an average identification accuracy of 84.74% at a -10 dB to 20 dB signal-to-noise ratio(SNR)with fewer parameters and less computation than a network model with the same identification rate in a software radio dataset containing multiple USRP X310s from the same manufacturer,with fewer parameters and less computation than a network model with the same identification rate.The algorithm is used to identify measurement and control signals and ensure the security of the measurement and control link with theoretical and engineering applications.
