Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.How...Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.However,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale accelerators.By leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and security.Given the criticality of personal safety for stranded individuals,search and security processes must be sufficiently reliable.To ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring range.The YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the cameras.Furthermore,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive unit.This strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall rate.Specifically,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,respectively.Although there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software design.Experimental tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.展开更多
To verify the performance of the neutron total cross-sectional spectrometer, the neutron total cross section of carbon is initially measured in the energy range of 1 eV to 20 MeV using the time-of-flight method. The m...To verify the performance of the neutron total cross-sectional spectrometer, the neutron total cross section of carbon is initially measured in the energy range of 1 eV to 20 MeV using the time-of-flight method. The measurement is performed at the Back-n white neutron source with a 76-m time-of-flight path using the China Spallation Neutron Source. A multilayer fast fission chamber with 235U and 238U is employed as the neutron detector. The diameter and thickness of the natural graphite sample are 70 mm and 40 mm, respectively. Signal waveforms are collected using a data acquisition system. Off-line data processing was used to obtain the neutron time-of-flight spectra and transmissions. The uncertainty of the counting statistics is generally approximately 3% for each bin in the energy range of 1–20 MeV. It is determined that the results for the neutron total cross section of carbon obtained using ^235U cells are in good agreement with the results obtained using 238U cells within limits of statistical uncertainty. Moreover, the measured total cross sections show good agreement with the broadening evaluated data.展开更多
文摘Prompt radiation emitted during accelerator operation poses a significant health risk,necessitating a thorough search and securing of hazardous areas prior to initiation.Currently,manual sweep methods are employed.However,the limitations of manual sweeps have become increasingly evident with the implementation of large-scale accelerators.By leveraging advancements in machine vision technology,the automatic identification of stranded personnel in controlled areas through camera imagery presents a viable solution for efficient search and security.Given the criticality of personal safety for stranded individuals,search and security processes must be sufficiently reliable.To ensure comprehensive coverage,180°camera groups were strategically positioned on both sides of the accelerator tunnel to eliminate blind spots within the monitoring range.The YOLOV8 network model was modified to enable the detection of small targets,such as hands and feet,as well as larger targets formed by individuals near the cameras.Furthermore,the system incorporates a pedestrian recognition model that detects human body parts,and an information fusion strategy is used to integrate the detected head,hands,and feet with the identified pedestrians as a cohesive unit.This strategy enhanced the capability of the model to identify pedestrians obstructed by equipment,resulting in a notable improvement in the recall rate.Specifically,recall rates of 0.915 and 0.82were obtained for Datasets 1 and 2,respectively.Although there was a slight decrease in accuracy,it aligned with the intended purpose of the search-and-secure software design.Experimental tests conducted within an accelerator tunnel demonstrated the effectiveness of this approach in achieving reliable recognition outcomes.
基金supported by the National Key Research and Development Plan(No.2016YFA0401603)the National Natural Science Foundation of China(No.11675155)
文摘To verify the performance of the neutron total cross-sectional spectrometer, the neutron total cross section of carbon is initially measured in the energy range of 1 eV to 20 MeV using the time-of-flight method. The measurement is performed at the Back-n white neutron source with a 76-m time-of-flight path using the China Spallation Neutron Source. A multilayer fast fission chamber with 235U and 238U is employed as the neutron detector. The diameter and thickness of the natural graphite sample are 70 mm and 40 mm, respectively. Signal waveforms are collected using a data acquisition system. Off-line data processing was used to obtain the neutron time-of-flight spectra and transmissions. The uncertainty of the counting statistics is generally approximately 3% for each bin in the energy range of 1–20 MeV. It is determined that the results for the neutron total cross section of carbon obtained using ^235U cells are in good agreement with the results obtained using 238U cells within limits of statistical uncertainty. Moreover, the measured total cross sections show good agreement with the broadening evaluated data.
