As photoelectrically detected ^(252)Cf-source-driven neutron signals always contain noise, a denoising algorithm is proposed based on compressive sensing for the noised neutron signal. In the algorithm, Empirical Mode...As photoelectrically detected ^(252)Cf-source-driven neutron signals always contain noise, a denoising algorithm is proposed based on compressive sensing for the noised neutron signal. In the algorithm, Empirical Mode Decomposition(EMD) is applied to decompose the noised neutron signal and then find out the noised Intrinsic Mode Function(IMF) automatically. Thus, we only need to use the basis pursuit denoising(BPDN) algorithm to denoise these IMFs. For this reason, the proposed algorithm can be called EMDCSDN(Empirical Mode Decomposition Compressive Sensing Denoising). In addition, five indicators are employed to evaluate the denoising effect. The results show that the EMDCSDN algorithm is more effective than the other denoising algorithms including BPDN. This study provides a new approach for signal denoising at the front-end.展开更多
The neutron flux monitor(NFM)system is an important diagnostic subsystem introduced by large nuclear fusion devices such as international thermonuclear experimental reactor(ITER),Japan torus-60,tokamak fusion test rea...The neutron flux monitor(NFM)system is an important diagnostic subsystem introduced by large nuclear fusion devices such as international thermonuclear experimental reactor(ITER),Japan torus-60,tokamak fusion test reactor,and HL-2 A.Neutron fluxes can provide real-time parameters for nuclear fusion,including neutron source intensity and fusion power.Corresponding to different nuclear reaction periods,neutron fluxes span over seven decades,thereby requiring electronic devices to operate in counting and Campbelling modes simultaneously.Therefore,it is crucial to design a real-time NFM system to encompass such a wide dynamic range.In this study,a high-precision NFM system with a wide measurement range of neutron flux is implemented using realtime multipoint linear calibration.It can automatically switch between counting and Campbelling modes with variations in the neutron flux.We established a testing platform to verify the feasibility of the NFM system,which can output the simulated neutron signal using an arbitrary waveform generator.Meanwhile,the accurate calibration interval of the Campbelling mode is defined well.Based on the above-mentioned design,the system satisfies the requirements,offering a dynamic range of 10~8 cps,temporal resolution of 1 ms,and maximal relative error of 4%measured at the signal-to-noise ratio of 15.8 dB.Additionally,the NFM system is verified in a field experiment involving HL-2 A,and the measured neutron flux is consistent with the results.展开更多
Experiments were performed on a high-speed online random neutron analyzing system (HORNA system) with a 252Cf neutron source (up to 1 GHz sampling rate and 3 input data channel),to obtain timeand frequency dependent s...Experiments were performed on a high-speed online random neutron analyzing system (HORNA system) with a 252Cf neutron source (up to 1 GHz sampling rate and 3 input data channel),to obtain timeand frequency dependent signatures which are sensitive to changes in the composition,fissile mass and configuration of the fissile assembly.The data were acquired by three high-speed synchronized acquisition cards at different detector angles,source-detector distances and block sizes.According to the relationship between 252Cf source and the ratio of power spectral density,Rpsd,all the signatures were calculated and analyzed using correlation and periodogram methods.Based on the results,the simulated autocorrelation functions were utilized for identifying different fissile mass with Elman neural network.The experimental results show that the Rpsd almost remains at constant amplitude in frequency range of 0-100 MHz,and is only related to the angle and source-detector distance.The trained Elman neural network is able to distinguish the characteristics of autocorrelation function and identify different fissile mass.The average identification rate reached 90% with high robustness.展开更多
基金Supported by the National Natural Science Foundation of China(Nos.61175005 and 61401049)
文摘As photoelectrically detected ^(252)Cf-source-driven neutron signals always contain noise, a denoising algorithm is proposed based on compressive sensing for the noised neutron signal. In the algorithm, Empirical Mode Decomposition(EMD) is applied to decompose the noised neutron signal and then find out the noised Intrinsic Mode Function(IMF) automatically. Thus, we only need to use the basis pursuit denoising(BPDN) algorithm to denoise these IMFs. For this reason, the proposed algorithm can be called EMDCSDN(Empirical Mode Decomposition Compressive Sensing Denoising). In addition, five indicators are employed to evaluate the denoising effect. The results show that the EMDCSDN algorithm is more effective than the other denoising algorithms including BPDN. This study provides a new approach for signal denoising at the front-end.
基金supported by the National Natural Science Foundation of China(Nos.11475131,11975307,and 11575184)the National Magnetic Confinement Fusion Energy Development Research(No.2013GB104003)。
文摘The neutron flux monitor(NFM)system is an important diagnostic subsystem introduced by large nuclear fusion devices such as international thermonuclear experimental reactor(ITER),Japan torus-60,tokamak fusion test reactor,and HL-2 A.Neutron fluxes can provide real-time parameters for nuclear fusion,including neutron source intensity and fusion power.Corresponding to different nuclear reaction periods,neutron fluxes span over seven decades,thereby requiring electronic devices to operate in counting and Campbelling modes simultaneously.Therefore,it is crucial to design a real-time NFM system to encompass such a wide dynamic range.In this study,a high-precision NFM system with a wide measurement range of neutron flux is implemented using realtime multipoint linear calibration.It can automatically switch between counting and Campbelling modes with variations in the neutron flux.We established a testing platform to verify the feasibility of the NFM system,which can output the simulated neutron signal using an arbitrary waveform generator.Meanwhile,the accurate calibration interval of the Campbelling mode is defined well.Based on the above-mentioned design,the system satisfies the requirements,offering a dynamic range of 10~8 cps,temporal resolution of 1 ms,and maximal relative error of 4%measured at the signal-to-noise ratio of 15.8 dB.Additionally,the NFM system is verified in a field experiment involving HL-2 A,and the measured neutron flux is consistent with the results.
基金Supported by Natural Science Foundation Project of CQ (CSTC2009BB2188)Fundamental Research Funds for Central Universities (No. CDJXS10120013)
文摘Experiments were performed on a high-speed online random neutron analyzing system (HORNA system) with a 252Cf neutron source (up to 1 GHz sampling rate and 3 input data channel),to obtain timeand frequency dependent signatures which are sensitive to changes in the composition,fissile mass and configuration of the fissile assembly.The data were acquired by three high-speed synchronized acquisition cards at different detector angles,source-detector distances and block sizes.According to the relationship between 252Cf source and the ratio of power spectral density,Rpsd,all the signatures were calculated and analyzed using correlation and periodogram methods.Based on the results,the simulated autocorrelation functions were utilized for identifying different fissile mass with Elman neural network.The experimental results show that the Rpsd almost remains at constant amplitude in frequency range of 0-100 MHz,and is only related to the angle and source-detector distance.The trained Elman neural network is able to distinguish the characteristics of autocorrelation function and identify different fissile mass.The average identification rate reached 90% with high robustness.
