基于迭代算法A的海水盐度能力验证结果分析

Analysis of seawater salinity proficiency testing results based on iterative algorithm A

为评价海洋检验检测机构海水盐度检测能力,国家海洋标准计量中心设计并实施了2020年度海水盐度能力验证计划,制备能力验证样品并开展均匀性检验。本次能力验证采用双样品以随机组合形式发放,利用迭代算法A对62家实验室提交的能力验证数据进行统计分析处理,合理确定指定值及其不确定度,将能力验证数据转化为能力统计量,根据Z比分数评定各参加实验室能力验证结果。结果显示,双样品全部“满意”的实验室有52家,占85.5%,有3家实验室能力验证结果“不满意”,6家实验室能力验证结果“有问题”。“不满意”和“有问题”的实验室共占14.5%。本次能力验证数据的频率分布接近正态分布,通过开展双样品联合置信概率分析和仪器类型统计分析,与往年能力验证结果“满意率”进行比较,绝大多数实验室海水盐度检测能力良好,个别实验室仍需加强海水盐度检测能力建设和内部质量控制。

In order to evaluate the seawater salinity detection ability of marine inspection and testing institutions,National Center of Ocean Standards and Metrology(NCOSM)implemented the seawater salinity proficiency testing and prepared the test samples and carried out the uniformity test in 2020.The proficiency testing was conducted in the form of double sample random combination.The data submitted by 62 laboratories were statistically analyzed by using iterative algorithm A,the specified value and uncertainty were reasonably determined.The proficiency testing data were transformed into ability statistics,and the results of each participating laboratory were evaluated according to Z-score.The results showed that 52 laboratories(85.5%)were satisfied with the double samples,3 laboratories were dissatisfied with the results of proficiency testing,and 6 laboratories with problems,laboratories of dissatisfaction and problems accounted for 14.5%.The frequency distribution of the data in this proficiency testing was close to the normal distribution.Through the joint confidence probability analysis of two samples and statistical analysis of instrument types,the rate of satisfaction was compared to the ones in previous years.Most of the laboratories have good seawater salinity detection capabilities,but some laboratories still need to strengthen the construction of seawater salinity detection capacity and internal quality control.