基于神经网络的废物桶活度测量方法研究  

A neural network-based method for measuring the activity of waste drum

作　　者：舒旻翔 单陈瑜 顾卫国[3] 王德忠[3] SHU Minxiang;SHAN Chenyu;GU Weiguo;WANG Dezhong(College of Smart Energy,Shanghai Jiao Tong University,Shanghai 200240,China;China Nuclear Power Technology Research Institute,Shenzhen 518031,China;Machinery and Power Engineering College,Shanghai Jiao Tong University,Shanghai 200240,China)

机构地区：[1]上海交通大学国家电投智慧能源创新学院,上海200240 [2]中广核研究院有限公司,深圳518031 [3]上海交通大学机械与动力工程学院,上海200240

出　　处：《核技术》2023年第12期72-82,共11页Nuclear Techniques

摘　　要：针对废物桶活度传统分段γ扫描(Segmented Gamma Scanning,SGS)测量精度低、层析γ扫描(Tomographic Gamma Scanning,TGS)测量时间长的问题,提出了基于神经网络的新型活度测量方法(New Gamma Scanning,NGS)。在该方法中,对介质均匀分布的废物桶进行测量时,将三个不同位置的探测器的计数率输入神经网络,可以直接输出等效环源半径,最终实现废物桶内核素总活度的准确重建。对400 L均匀水泥废物桶进行了多组模拟测量,利用不同方法分别进行了活度重建。结果表明:对于单个源,新方法的平均相对误差为4.26%,远小于SGS的误差(68.15%),与60网格的TGS的误差接近(3.97%);对于多个源,新方法的平均相对误差为24.27%,而SGS为48.02%,TGS为28.61%。新方法的精度高于SGS,达到了TGS的水平,而测量时间缩短到了TGS的1/20。新方法在保证了高精度的前提下大大缩短了测量时间,为低、中水平放射性固体废物的测量提供了技术支撑。[Background]During the operation of nuclear power plants,a large amount of low and intermediate level waste(LILW)is generated,which is usually prepared into 200-L and 400-L waste drums.To ensure the safe disposal of these waste drums,they must be analyzed to determine the type and activity of the nuclides contained within them.Non-destructive assay(NDA)has been widely used in the detection of waste drums in nuclear power plants,along with segmented gamma scanning(SGS)and tomographic gamma scanning(TGS).However,the low measurement accuracy of SGS and the long measurement time of TGS limit the practical application of these methods.[Purpose]This sudy aims to shorten the measurement time while maintaining high measurement accuracy by proposing a new neural network-based method for measuring the activity of waste drum.[Methods]When the waste drum was filled with a uniform distribution of medium and rotated at a constant speed during measurement,the point source was equivalent to a ring source.The equivalent ring source in the waste drum possessed an activity equal to the total activity of all sources.The neural network model is established,the count rate of the detector at different positions is used as input,and the radius of the equivalent ring source is used as output.Finally,the total activity of the waste drum is calculated.The simulated measurement is carried out in a 400-L waste drum,the medium is concrete,the radioactive source is Co-60,and 50 groups of single-source and 10 groups of multi-source are generated randomly.Different methods are used to reconstruct the activity of the waste drum.[Results]When there is only one radioactive source in the waste drum,the mean relative error(MRE)of activity reconstruction by the new method is 4.26%,which is much lower than that of SGS(68.15%)and close to that of TGS with 60 grids(3.97%).When there are multiple radioactive sources in the waste drum,the MRE of activity reconstruction by the new method is 24.27%,which is lower than that of SGS(48.02%)and close to that of

关 键 词：低中放固废 无损测量 活度重建 神经网络 等效环源 

分 类 号：TL81[核科学技术—核技术及应用]