共查询到16条相似文献,搜索用时 39 毫秒
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周江 《理化检验(物理分册)》1998,34(10):22-23
根据电力行业标准DL441-91《火力发电厂高温高压蒸汽管道蠕变监督导则》中关于蠕变标记测量方法的要求,通过推导得到了测量温度的差值与换算到0℃时周长差值的关系式,并列举了北仑电厂实测得到的一些数据来进一上说明温度测量的重要性。 相似文献
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本文提出一种动态测试中单次性信号测试数据的贝叶斯推断方法,其中单次性的被测信号和输出信号被认为是随机过程的现实。通常,在进行测试之前获得这些现实的一些知识是有用的。为了从单次性的动态测试中获取最多的信息,引入了贝叶斯方法使实验者根据测试结果提供的新的信息修改其先验置信度。 相似文献
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测试系统中动态非线性一直是测试界棘手的问题,国内外十分重视这方面的研究,直到现在非线性动态测试还没有形成象线性动态测试那样成熟的理论,模型化的测量是现代测试技术的发展方向。本文提出一种非线性动态测试系统的模型化测量原理,对于兵器动态测试有广阔的应用前景。 相似文献
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M. L. Malczewski 《Particulate Science and Technology》1992,10(3):183-199
This paper describes a methodology which estimates the average particulate concentration in a process gas of continuous rather than batch collected data. The method combines the statistical approach described by VanSlooten (1) and the use of a sliding average to the analysis of incoming continuous particle count data.
Standard deviation equations estimating the average particulate concentration in process gas streams as a function of the sample volume are derived, allowing calculation of the method's resolution for different sliding average window widths. The paper includes examples of the method applied to synthetic data, and discusses the effect of counter background, counter sampling rates, and window widths on the sliding average. In addition, continuous data from several facilities are analyzed by this method and the results are discussed. 相似文献
Standard deviation equations estimating the average particulate concentration in process gas streams as a function of the sample volume are derived, allowing calculation of the method's resolution for different sliding average window widths. The paper includes examples of the method applied to synthetic data, and discusses the effect of counter background, counter sampling rates, and window widths on the sliding average. In addition, continuous data from several facilities are analyzed by this method and the results are discussed. 相似文献
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M. L. MALCZEWSKI 《Particulate Science and Technology》2013,31(3-4):183-199
This paper describes a methodology which estimates the average particulate concentration in a process gas of continuous rather than batch collected data. The method combines the statistical approach described by VanSlooten (1) and the use of a sliding average to the analysis of incoming continuous particle count data. Standard deviation equations estimating the average particulate concentration in process gas streams as a function of the sample volume are derived, allowing calculation of the method's resolution for different sliding average window widths. The paper includes examples of the method applied to synthetic data, and discusses the effect of counter background, counter sampling rates, and window widths on the sliding average. In addition, continuous data from several facilities are analyzed by this method and the results are discussed. 相似文献