γ射线测量过程控制及其测量数据处理研究
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摘要
文中主要研究γ射线测量过程控制及其数据处理方面的问题。首先，言简意赅的叙述γ射线测量的基础理论和相关知识。其次，叙述了统计学基础理论及误差理论与数据处理部分内容，同时把统计学在放射性测量中的应用做了相应的分析。研究中发现理论在实际运用中的局限，提出了γ射线测量及其测量数据处理中存在的问题。最后，针对存在的问题，引入过程控制理论和最新的误差理论与数据处理理论对存在的问题进行解决，并列举大量实测数据进行验证分析。
介绍了数据质量定义及其纬度，在此基础上引入统计过程控制工具——控制图和过程能力指数。大量γ测量数据发现传统的统计过程控制工具不能够满足实际的运用，结合加权标准差方法的基本思想，提出了有偏总体的联合均值极差控制图。根据过程能力指数的定义，构造出适合放射性γ测量的测量能力指数。经过实际测量数据的检验，有偏总体的联合均值极差控制图和放射性测量能力指数能够很好的对放射性稳定核素的测量过程进行控制。放射性测量能力指数更加真实的衡量了仪器在测量过程中的长期稳定性。并理论上推导出适合短寿核素测量过程控制的控制图。
发现现有放射性测量不确定度评价存在的局限，利用灰色系统理论对样本分布的不要求和小样本等特点，由大量实测数据计算出放射性灰度常数，通过实际数据的验证，灰度系统理论计算结果大样本情况下优于基于泊松分布前提的计算结果，小样本情况下更是优于Bessel公式法和泊松分布前提的计算结果。
初步回归计算出美国ORTEC公司的高纯锗γ能谱仪对测量不确定度评定时采用的数学模型。
Firstly, simple description the foundation theories of theγradiation measurementand its related knowledges. The nine instruments index of theγradiation detector isemphasized in order to correspond the new instrument stability index that argue inchapter 5.Secondly, described the statistic basal theories and the error margintheorieses and data processing. Through analyse the statistics that used in radiationmeasurement,we find some problems are exist in theγradiation measurement and itsdata processing.Finally, aim at the existent problem, introduce the latest error margintheories and data processing theories to carry on resolve to the existent problem.
This aiticle detailed discussed the data quantity definition and its degree oflatitudes. Analyzing the main aspect of the radiation measurement data requested sothat to introduce the statistics process control tools—Control chart and Process abilityindex number. According to the datas that measured theγradiation in daily,wediscover the traditional statistics process control tools can't satisfy the real practiceenough. Combine the basic thought of add the power Sigma method, we put forwardthe new (?)-R control chart base on the sample data probability distributions andcompute the constants of the new (?)-R control chart. According to the definition of the process ability index number, we construct the new radiation measurement abilityindex number to suit the real practice. Through actual datas test the new (?)-Rcontrol chart base on the sample data probability distributions and the radiationmeasurement ability index number can do well than the its before, the new (?)-Rcontrol chart base on the sample data probability distributions can advance to appearand send out the early-warning information about the unqualified data, effectivelyavoided the mistakes—fail to report and wrong deliver. The radiation measurementability index number measured the instrument more truely at the long-term stability inthe process when it is used in daily.
Discover the existing problems of the experimental uncertainty in radiationmeasurement,we introduce the Gray system theories because of its characteristics ofno request to the sample data probability distributions and small sample datas. Fromthe great quantities numbers that measure in daily to compute a constant of the Graysystem theories. Passing the verification of the actual data,we find the Gray systemtheories constant do well not only in the large sample datas but also in the smallsample datas. Contrast the results that calculate in the Gray system theories, we caneasily draw the conclusion that the Gray system theories results is more effective thanthe results based on the poisson probability distribution.
Primary compute the mathematics model that used in an American company'sγradiation measurement instrument by the regression model and give an estimatedregression equation.
介绍了数据质量定义及其纬度，在此基础上引入统计过程控制工具——控制图和过程能力指数。大量γ测量数据发现传统的统计过程控制工具不能够满足实际的运用，结合加权标准差方法的基本思想，提出了有偏总体的联合均值极差控制图。根据过程能力指数的定义，构造出适合放射性γ测量的测量能力指数。经过实际测量数据的检验，有偏总体的联合均值极差控制图和放射性测量能力指数能够很好的对放射性稳定核素的测量过程进行控制。放射性测量能力指数更加真实的衡量了仪器在测量过程中的长期稳定性。并理论上推导出适合短寿核素测量过程控制的控制图。
发现现有放射性测量不确定度评价存在的局限，利用灰色系统理论对样本分布的不要求和小样本等特点，由大量实测数据计算出放射性灰度常数，通过实际数据的验证，灰度系统理论计算结果大样本情况下优于基于泊松分布前提的计算结果，小样本情况下更是优于Bessel公式法和泊松分布前提的计算结果。
初步回归计算出美国ORTEC公司的高纯锗γ能谱仪对测量不确定度评定时采用的数学模型。
Firstly, simple description the foundation theories of theγradiation measurementand its related knowledges. The nine instruments index of theγradiation detector isemphasized in order to correspond the new instrument stability index that argue inchapter 5.Secondly, described the statistic basal theories and the error margintheorieses and data processing. Through analyse the statistics that used in radiationmeasurement,we find some problems are exist in theγradiation measurement and itsdata processing.Finally, aim at the existent problem, introduce the latest error margintheories and data processing theories to carry on resolve to the existent problem.
This aiticle detailed discussed the data quantity definition and its degree oflatitudes. Analyzing the main aspect of the radiation measurement data requested sothat to introduce the statistics process control tools—Control chart and Process abilityindex number. According to the datas that measured theγradiation in daily,wediscover the traditional statistics process control tools can't satisfy the real practiceenough. Combine the basic thought of add the power Sigma method, we put forwardthe new (?)-R control chart base on the sample data probability distributions andcompute the constants of the new (?)-R control chart. According to the definition of the process ability index number, we construct the new radiation measurement abilityindex number to suit the real practice. Through actual datas test the new (?)-Rcontrol chart base on the sample data probability distributions and the radiationmeasurement ability index number can do well than the its before, the new (?)-Rcontrol chart base on the sample data probability distributions can advance to appearand send out the early-warning information about the unqualified data, effectivelyavoided the mistakes—fail to report and wrong deliver. The radiation measurementability index number measured the instrument more truely at the long-term stability inthe process when it is used in daily.
Discover the existing problems of the experimental uncertainty in radiationmeasurement,we introduce the Gray system theories because of its characteristics ofno request to the sample data probability distributions and small sample datas. Fromthe great quantities numbers that measure in daily to compute a constant of the Graysystem theories. Passing the verification of the actual data,we find the Gray systemtheories constant do well not only in the large sample datas but also in the smallsample datas. Contrast the results that calculate in the Gray system theories, we caneasily draw the conclusion that the Gray system theories results is more effective thanthe results based on the poisson probability distribution.
Primary compute the mathematics model that used in an American company'sγradiation measurement instrument by the regression model and give an estimatedregression equation.
引文
[1] W．B．MANN，A．RYTZ，A．SPERNOL著，卞祖和等译．放射性测量——原理与实践[M]．北京：中国科学技术出版社，1992．
[2] 格伦．F．诺尔著，李旭等译．辐射探测与测量[M]．北京：原子能出版社，1988．
[3] 瓦冈诺夫，周蓉生．核方法原理及运用[M]．北京：地质出版社，1993．
[4] 谭金波，李彦禄．高纯锗Y谱仪活度测量标准装置[J]．计量学报．2000，21(3)：232～238．
[5] 贾文懿，方方等．核地球物理仪器[M]．北京：原子能出版社，1998．8．
[6] 徐春长．全国γ谱仪在环境和建材中放射性活度测量研讨会资料．P2～P3．
[7] 古当长．放射性核素活度测量的方法和技术[M]．北京：科学技术出版社，1994．
[8] 方方．野外地面伽玛射线全谱测量研究[D]．成都理工大学博士论文．2001．5．
[9] 陆继根．高纯锗γ谱仪对环境样品的探测效率刻度[J]．甘肃环境研究与监测．1997，10(3)：25～27．
[10] 核辐射测量方法讲义，成都理工大学．
[11] 贾俊平．统计学(第二版)[M]．北京：清华大学出版社，2006．7．
[12] 茆诗松．统计手册[M]．北京：科学出版社，2003．
[13] 茆诗松，王静龙，濮晓龙．高等数理统计[M]．北京：高等教育出版社，1998．
[14] 官生平．SPC统计制程管制[M]．厦门：厦门大学出版社，2004．
[15] 杨跃进．统计过程控制技术[M]．北京：航空工业出版社，2003．
[16] 王毓芳．统计过程控制的策划与实施[M]．北京：中国经济出版社，2005．
[17] GB／T 4091-2001《常规控制图》．
[18] 周纪芗，茆诗松．质量管理统计方法[M]．北京：中国统计出版社，1999．
[19] Bissell AF. How Reliableis Your Capability Index[J]. Applied Statistics. 1999: 331-340.
[20] 费业泰．现代误差理论及其基本问题[J]．宇航计测技术，1996，16(4，5)：2-5．
[21] 王亦兵．统计学初步知识及在放射性测量中的应用[J]．辐射防护，1977，Z2．
[22] Chang YS, Bai DS.Control charts for positively-skewed populations with weighted standard deviations [J].Quality and Reliability Engineering International.2001:17:397-406.
[23] Chang YS, Choi IS, Bai DS. Process Capability Indices for Skewed Populations [J].Quality Reliability Engineering International. 2002:18:383-393.
[24] Chen KS, Pearn WL, Lin PC. Capability Measures for Processes with Multiple Characteristics[J]. Quality and Reliability Engineering International.2003:19:101一110.
[25] Pipino, L. L., Lee, Y. W. &Wang, R. Y. Data quality assessment [J]. Communications of the ACM, 2002, 45(4): 211-218.
[26] Liu Zhimin.Uncertainty and Reliability Analysis [J].Proceedings of Quality Standardization Metrology, 1995.
[27] Wang Zhongyu, Qin Ping, Gao Yongsheng.Grey Evaluation of Measurement Uncertainty[J].The Journal of Grey system,1999,11(4):347-352.
[28] 邓聚龙．灰色系统理论教程[M]．武汉：华中理工大学出版社，1992．
[29] GB18871-2002《电离辐射防护与辐射源安全基本标准》．
[30] HJ／T61-2001《辐射环境监测技术规范》．
[31] GB12379—90《环境核辐射监测规定》．
[32] 韩奎初，丁声耀．实用电离辐射计量学[M]．北京：原子能出版社，1996．
[33] 贾文懿．利用天然放射性找地下水[M]．北京：原子能出版社，1986．
[34] 孙山泽．抽样调查[M]．北京：北京大学出版社，2004．
[35] 王中宇，夏新涛，朱坚民．非统计原理及其工程应用[M]．北京：科学出版社，2005．
[36] 美国能源部．关国能源部设施环境放则性监督学则[A]．潘白强，罗圆祯等．国外辐则防护规程汇编5[C]．北京：国务院环境保护委员会办公室，1981．
[37] 高玉堂．环境监测常用统计方法[M]．北京：原了能出版社．1981．
[38] 诸洪达，沙连茂．质量控制和数据处理[A]．张景源．中国食品放则性所致内剂量[C]．北京：中国环境科学出版社．
[2] 格伦．F．诺尔著，李旭等译．辐射探测与测量[M]．北京：原子能出版社，1988．
[3] 瓦冈诺夫，周蓉生．核方法原理及运用[M]．北京：地质出版社，1993．
[4] 谭金波，李彦禄．高纯锗Y谱仪活度测量标准装置[J]．计量学报．2000，21(3)：232～238．
[5] 贾文懿，方方等．核地球物理仪器[M]．北京：原子能出版社，1998．8．
[6] 徐春长．全国γ谱仪在环境和建材中放射性活度测量研讨会资料．P2～P3．
[7] 古当长．放射性核素活度测量的方法和技术[M]．北京：科学技术出版社，1994．
[8] 方方．野外地面伽玛射线全谱测量研究[D]．成都理工大学博士论文．2001．5．
[9] 陆继根．高纯锗γ谱仪对环境样品的探测效率刻度[J]．甘肃环境研究与监测．1997，10(3)：25～27．
[10] 核辐射测量方法讲义，成都理工大学．
[11] 贾俊平．统计学(第二版)[M]．北京：清华大学出版社，2006．7．
[12] 茆诗松．统计手册[M]．北京：科学出版社，2003．
[13] 茆诗松，王静龙，濮晓龙．高等数理统计[M]．北京：高等教育出版社，1998．
[14] 官生平．SPC统计制程管制[M]．厦门：厦门大学出版社，2004．
[15] 杨跃进．统计过程控制技术[M]．北京：航空工业出版社，2003．
[16] 王毓芳．统计过程控制的策划与实施[M]．北京：中国经济出版社，2005．
[17] GB／T 4091-2001《常规控制图》．
[18] 周纪芗，茆诗松．质量管理统计方法[M]．北京：中国统计出版社，1999．
[19] Bissell AF. How Reliableis Your Capability Index[J]. Applied Statistics. 1999: 331-340.
[20] 费业泰．现代误差理论及其基本问题[J]．宇航计测技术，1996，16(4，5)：2-5．
[21] 王亦兵．统计学初步知识及在放射性测量中的应用[J]．辐射防护，1977，Z2．
[22] Chang YS, Bai DS.Control charts for positively-skewed populations with weighted standard deviations [J].Quality and Reliability Engineering International.2001:17:397-406.
[23] Chang YS, Choi IS, Bai DS. Process Capability Indices for Skewed Populations [J].Quality Reliability Engineering International. 2002:18:383-393.
[24] Chen KS, Pearn WL, Lin PC. Capability Measures for Processes with Multiple Characteristics[J]. Quality and Reliability Engineering International.2003:19:101一110.
[25] Pipino, L. L., Lee, Y. W. &Wang, R. Y. Data quality assessment [J]. Communications of the ACM, 2002, 45(4): 211-218.
[26] Liu Zhimin.Uncertainty and Reliability Analysis [J].Proceedings of Quality Standardization Metrology, 1995.
[27] Wang Zhongyu, Qin Ping, Gao Yongsheng.Grey Evaluation of Measurement Uncertainty[J].The Journal of Grey system,1999,11(4):347-352.
[28] 邓聚龙．灰色系统理论教程[M]．武汉：华中理工大学出版社，1992．
[29] GB18871-2002《电离辐射防护与辐射源安全基本标准》．
[30] HJ／T61-2001《辐射环境监测技术规范》．
[31] GB12379—90《环境核辐射监测规定》．
[32] 韩奎初，丁声耀．实用电离辐射计量学[M]．北京：原子能出版社，1996．
[33] 贾文懿．利用天然放射性找地下水[M]．北京：原子能出版社，1986．
[34] 孙山泽．抽样调查[M]．北京：北京大学出版社，2004．
[35] 王中宇，夏新涛，朱坚民．非统计原理及其工程应用[M]．北京：科学出版社，2005．
[36] 美国能源部．关国能源部设施环境放则性监督学则[A]．潘白强，罗圆祯等．国外辐则防护规程汇编5[C]．北京：国务院环境保护委员会办公室，1981．
[37] 高玉堂．环境监测常用统计方法[M]．北京：原了能出版社．1981．
[38] 诸洪达，沙连茂．质量控制和数据处理[A]．张景源．中国食品放则性所致内剂量[C]．北京：中国环境科学出版社．