To detect radioactive substances with low activity levels,an anticoincidence detector and a high-purity germanium(HPGe)detector are typically used simultaneously to suppress Compton scattering background,thereby resul...To detect radioactive substances with low activity levels,an anticoincidence detector and a high-purity germanium(HPGe)detector are typically used simultaneously to suppress Compton scattering background,thereby resulting in an extremely low detection limit and improving the measurement accuracy.However,the complex and expensive hardware required does not facilitate the application or promotion of this method.Thus,a method is proposed in this study to discriminate the digital waveform of pulse signals output using an HPGe detector,whereby Compton scattering background is suppressed and a low minimum detectable activity(MDA)is achieved without using an expensive and complex anticoincidence detector and device.The electric-field-strength and energy-deposition distributions of the detector are simulated to determine the relationship between pulse shape and energy-deposition location,as well as the characteristics of energy-deposition distributions for fulland partial-energy deposition events.This relationship is used to develop a pulse-shape-discrimination algorithm based on an artificial neural network for pulse-feature identification.To accurately determine the relationship between the deposited energy of gamma(γ)rays in the detector and the deposition location,we extract four shape parameters from the pulse signals output by the detector.Machine learning is used to input the four shape parameters into the detector.Subsequently,the pulse signals are identified and classified to discriminate between partial-and full-energy deposition events.Some partial-energy deposition events are removed to suppress Compton scattering.The proposed method effectively decreases the MDA of an HPGeγ-energy dispersive spectrometer.Test results show that the Compton suppression factors for energy spectra obtained from measurements on ^(152)Eu,^(137)Cs,and ^(60)Co radioactive sources are 1.13(344 keV),1.11(662 keV),and 1.08(1332 keV),respectively,and that the corresponding MDAs are 1.4%,5.3%,and 21.6%lower,respectively.展开更多
A new neutron-gamma discriminator based on the support vector machine(SVM) method is proposed to improve the performance of the time-of-flight neutron spectrometer. The neutron detector is an EJ-299-33 plastic scintil...A new neutron-gamma discriminator based on the support vector machine(SVM) method is proposed to improve the performance of the time-of-flight neutron spectrometer. The neutron detector is an EJ-299-33 plastic scintillator with pulse-shape discrimination(PSD) property. The SVM algorithm is implemented in field programmable gate array(FPGA) to carry out the real-time sifting of neutrons in neutron-gamma mixed radiation fields. This study compares the ability of the pulse gradient analysis method and the SVM method. The results show that this SVM discriminator can provide a better discrimination accuracy of 99.1%. The accuracy and performance of the SVM discriminator based on FPGA have been evaluated in the experiments. It can get a figure of merit of 1.30.展开更多
This study proposes a ladder gradient method for neutron and gamma-ray discrimination.The proposed method exhibited state-of-the-art performance with low time consumption,which incorporates two parts:information extra...This study proposes a ladder gradient method for neutron and gamma-ray discrimination.The proposed method exhibited state-of-the-art performance with low time consumption,which incorporates two parts:information extraction and discrimination factor calculation.A quasi-continuous spiking cortical model was proposed to extract information from the radiation pulse signals,thus generating an ignition map corresponding to each pulse signal.The ignition map can be used to calculate the discrimination factor.A ladder gradient calculation was introduced to obtain a discrimination factor with low computational complexity.The proposed method was compared with five other discrimination methods to evaluate its robustness and efficacy.Furthermore,the filter adaptability of the pulse-coupled neural network and ladder gradient methods was investigated.Possible reasons for adapting the conditions with different discrimination methods and filters were analyzed.Experiments were conducted in 20 filtering situations with 11 types of filters to determine the most suitable filters for discrimination methods.The experimental results revealed that the three most adaptive filters of the pulse-coupled neural networks and ladder gradient methods are the wavelet,elliptic,and median filters and the elliptic,moving average,and wavelet filters,respectively.展开更多
There are numerous goals in next-generation cellular networks(5G),which is expected to be available soon.They want to increase data rates,reduce end-to-end latencies,and improve end-user service quality.Modern network...There are numerous goals in next-generation cellular networks(5G),which is expected to be available soon.They want to increase data rates,reduce end-to-end latencies,and improve end-user service quality.Modern networks need to change because there has been a significant rise in the number of base stations required to meet these needs and put the operators’low-cost constraints to the test.Because it can withstand interference from other wireless networks,and Adaptive Complex Multicarrier Modulation(ACMM)system is being looked at as a possible choice for the 5th Generation(5G)of wireless networks.Many arithmetic units need to be used on the hardware side of multicarrier systems to do the pulse-shaping filters and inverse FFT.The main goal of this study is to adapt complex multicarrier modulation(ACMM)for baseband transmission with low complexity and the ability to change it.We found that this is the first recon-figurable architecture that lets you choose how many subcarriers a subband has while still having the same amount of hardware resources as before.Also,under the new design with a single selection line,it selects from a set of filters.The baseband modulating signal is evaluated and tested using a Field-Programmable Gate Array(FPGA)device.This device is available from a commercial source.New technology outperforms current technology in terms of computational com-plexity,simple design,and ease of implementation.Additionally,it has a higher power spectrum density,spectral efficiency,a lower bit error rate,and a higher peak to average power ratio than existing technology.展开更多
The photoneutron source （PNS, phase 1）, an electron linear accelerator （linac）-based pulsed neutron facility that uses the time-of-flight （TOF） technique, was constructed for the acquisition of nuclear data from...The photoneutron source （PNS, phase 1）, an electron linear accelerator （linac）-based pulsed neutron facility that uses the time-of-flight （TOF） technique, was constructed for the acquisition of nuclear data from the Thorium Molten Salt Reactor （TMSR） at the Shanghai Institute of Applied Physics （SINAP）. The neutron detector signal used for TOF calculation, with information on the pulse arrival time, pulse shape, and pulse height, was recorded by using a waveform digitizer （WFD）. By using the pulse height and pulse-shape discrimination （PSD） analysis to identify neutrons and ＂y-rays, the neutron TOF spectrum was obtained by employing a simple electronic design, and a new WFD-based DAQ system was developed and tested in this commissioning experiment. The DAQ system developed is characterized by a very high efficiency with respect to millisecond neutron TOF spectroscopy.展开更多
基金This work was supported by the National Key R&D Program of China(Nos.2022YFF0709503,2022YFB1902700,2017YFC0602101)the Key Research and Development Program of Sichuan province(No.2023YFG0347)the Key Research and Development Program of Sichuan province(No.2020ZDZX0007).
文摘To detect radioactive substances with low activity levels,an anticoincidence detector and a high-purity germanium(HPGe)detector are typically used simultaneously to suppress Compton scattering background,thereby resulting in an extremely low detection limit and improving the measurement accuracy.However,the complex and expensive hardware required does not facilitate the application or promotion of this method.Thus,a method is proposed in this study to discriminate the digital waveform of pulse signals output using an HPGe detector,whereby Compton scattering background is suppressed and a low minimum detectable activity(MDA)is achieved without using an expensive and complex anticoincidence detector and device.The electric-field-strength and energy-deposition distributions of the detector are simulated to determine the relationship between pulse shape and energy-deposition location,as well as the characteristics of energy-deposition distributions for fulland partial-energy deposition events.This relationship is used to develop a pulse-shape-discrimination algorithm based on an artificial neural network for pulse-feature identification.To accurately determine the relationship between the deposited energy of gamma(γ)rays in the detector and the deposition location,we extract four shape parameters from the pulse signals output by the detector.Machine learning is used to input the four shape parameters into the detector.Subsequently,the pulse signals are identified and classified to discriminate between partial-and full-energy deposition events.Some partial-energy deposition events are removed to suppress Compton scattering.The proposed method effectively decreases the MDA of an HPGeγ-energy dispersive spectrometer.Test results show that the Compton suppression factors for energy spectra obtained from measurements on ^(152)Eu,^(137)Cs,and ^(60)Co radioactive sources are 1.13(344 keV),1.11(662 keV),and 1.08(1332 keV),respectively,and that the corresponding MDAs are 1.4%,5.3%,and 21.6%lower,respectively.
基金partially supported by the National Science and Technology Major Project of Ministry of Science and Technology of China (Grant Nos. 2014GB109003 and 2015GB111002)National Natural Science Foundation of China (Grant Nos. 11375195, 11575184, 11375004 and 11775068)
文摘A new neutron-gamma discriminator based on the support vector machine(SVM) method is proposed to improve the performance of the time-of-flight neutron spectrometer. The neutron detector is an EJ-299-33 plastic scintillator with pulse-shape discrimination(PSD) property. The SVM algorithm is implemented in field programmable gate array(FPGA) to carry out the real-time sifting of neutrons in neutron-gamma mixed radiation fields. This study compares the ability of the pulse gradient analysis method and the SVM method. The results show that this SVM discriminator can provide a better discrimination accuracy of 99.1%. The accuracy and performance of the SVM discriminator based on FPGA have been evaluated in the experiments. It can get a figure of merit of 1.30.
基金supported by the National Natural Science Foundation of China(Nos.U19A2086,41874121,12205078).
文摘This study proposes a ladder gradient method for neutron and gamma-ray discrimination.The proposed method exhibited state-of-the-art performance with low time consumption,which incorporates two parts:information extraction and discrimination factor calculation.A quasi-continuous spiking cortical model was proposed to extract information from the radiation pulse signals,thus generating an ignition map corresponding to each pulse signal.The ignition map can be used to calculate the discrimination factor.A ladder gradient calculation was introduced to obtain a discrimination factor with low computational complexity.The proposed method was compared with five other discrimination methods to evaluate its robustness and efficacy.Furthermore,the filter adaptability of the pulse-coupled neural network and ladder gradient methods was investigated.Possible reasons for adapting the conditions with different discrimination methods and filters were analyzed.Experiments were conducted in 20 filtering situations with 11 types of filters to determine the most suitable filters for discrimination methods.The experimental results revealed that the three most adaptive filters of the pulse-coupled neural networks and ladder gradient methods are the wavelet,elliptic,and median filters and the elliptic,moving average,and wavelet filters,respectively.
文摘There are numerous goals in next-generation cellular networks(5G),which is expected to be available soon.They want to increase data rates,reduce end-to-end latencies,and improve end-user service quality.Modern networks need to change because there has been a significant rise in the number of base stations required to meet these needs and put the operators’low-cost constraints to the test.Because it can withstand interference from other wireless networks,and Adaptive Complex Multicarrier Modulation(ACMM)system is being looked at as a possible choice for the 5th Generation(5G)of wireless networks.Many arithmetic units need to be used on the hardware side of multicarrier systems to do the pulse-shaping filters and inverse FFT.The main goal of this study is to adapt complex multicarrier modulation(ACMM)for baseband transmission with low complexity and the ability to change it.We found that this is the first recon-figurable architecture that lets you choose how many subcarriers a subband has while still having the same amount of hardware resources as before.Also,under the new design with a single selection line,it selects from a set of filters.The baseband modulating signal is evaluated and tested using a Field-Programmable Gate Array(FPGA)device.This device is available from a commercial source.New technology outperforms current technology in terms of computational com-plexity,simple design,and ease of implementation.Additionally,it has a higher power spectrum density,spectral efficiency,a lower bit error rate,and a higher peak to average power ratio than existing technology.
基金Supported by Strategic Priority Research Program of the Chinese Academy of Science(TMSR)(XDA02010100)National Natural Science Foundation of China(NSFC)(11475245,No.11305239)Shanghai Key Laboratory of Particle Physics and Cosmology(11DZ2260700)
文摘The photoneutron source （PNS, phase 1）, an electron linear accelerator （linac）-based pulsed neutron facility that uses the time-of-flight （TOF） technique, was constructed for the acquisition of nuclear data from the Thorium Molten Salt Reactor （TMSR） at the Shanghai Institute of Applied Physics （SINAP）. The neutron detector signal used for TOF calculation, with information on the pulse arrival time, pulse shape, and pulse height, was recorded by using a waveform digitizer （WFD）. By using the pulse height and pulse-shape discrimination （PSD） analysis to identify neutrons and ＂y-rays, the neutron TOF spectrum was obtained by employing a simple electronic design, and a new WFD-based DAQ system was developed and tested in this commissioning experiment. The DAQ system developed is characterized by a very high efficiency with respect to millisecond neutron TOF spectroscopy.
