张先勇,唐其环,张燕.漠河低温工作极值及其统计方法探讨[J].装备环境工程,2021,18(9):125-131. ZHANG Xian-yong,TANG Qi-huan,ZHANG Yan.Discussion on Operational Extreme Value and Statistical Method of Mohe Low Temperature[J].Equipment Environmental Engineering,2021,18(9):125-131.
漠河低温工作极值及其统计方法探讨
Discussion on Operational Extreme Value and Statistical Method of Mohe Low Temperature
投稿时间:2021-04-09  修订日期:2021-05-31
DOI:10.7643/issn.1672-9242.2021.09.019
中文关键词:  漠河  低温  工作极值  严酷月  时间风险率  基准条件  环境适应性
英文关键词:Mohe  low-temperature  operational extreme values  harsh month  time risk rate  base condition  environmental adaptability
基金项目:
作者单位
张先勇 西南技术工程研究所,重庆 400039;漠河大气环境材料腐蚀国家野外科学观测研究站,黑龙江 漠河 165399 
唐其环 西南技术工程研究所,重庆 400039 
张燕 西南技术工程研究所,重庆 400039 
AuthorInstitution
ZHANG Xian-yong Southwest Institute of Technology and Engineering, Chongqing 400039, China;Mohe National Field Scientific Observation & Research Station on Materials Corrosion in Atmospheric Environment, Mohe 165399, China 
TANG Qi-huan Southwest Institute of Technology and Engineering, Chongqing 400039, China 
ZHANG Yan Southwest Institute of Technology and Engineering, Chongqing 400039, China 
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中文摘要:
      为提高漠河试验站低温工作极值统计的准确性,推进低温工作极值在装备低温环境适应性评估中的应用。以最低温度、平均温度、小于–35 ℃的天数为基准条件,分别统计了漠河不同年份的低温工作极值,研究了基准条件、统计年份、数据缺失情况对严酷月确定和工作极值的影响。基准条件、统计年份、数据缺失都会影响严酷月的确定和低温工作极值的统计,统计年份的影响比基准条件大,数据缺失影响的严重性需要看数据缺失的多少和时间段。工作极值结果至少包括数据年限、基准条件、严酷月、时间风险率、与时间风险率对应的工作极值等内容。1991—2005年,时间风险率为1%、5%、10%、20%、30%的最低温度工作极值分别为:–44.0、–40.7、–38.1、–35.6、–33.6 ℃。
英文摘要:
      This paper aims to improve the accuracy of low temperature operational extreme value statistics in Mohe test station and promote the application of low temperature operational extreme value in equipment low temperature environmental adaptability assessment. Based on the lowest temperature, average temperature and days below –35 ℃, the low temperature operational extreme values of Mohe in different years are counted respectively, and the effects of base conditions, statistical years and data missing on the determination of harsh months and operational extreme values are studied. Base conditions, statistical years, data missing will affect the determination of harsh months and the statistics of low temperature operational extreme values. The influence of statistical year is greater than that of base condition. The severity of the influence caused by data missing depends on the amount and time period of data missing. The results of operational extreme values include at least data years, base conditions, harsh months, time risk rates, operational extreme values corresponding to time risk rates, etc. From 1991 to 2005, the lowest temperature operational extreme values with the time risk rates of 1%, 5%, 10%, 20% and 30% were –44.0, –40.7, –38.1, –35.6 and –33.6 ℃ respectively.
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