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Data Acquisition Uncertainty

机译:数据采集​​不确定性

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With the advent of modern parallel computing systems, larger and more accurate simulation models have been developed to simulate real-world hardware. These models require verification and validation (V&V), the latter using data acquired from representative hardware to ascertain the uncertainty of the model. An understanding of the errors introduced by the measurement system into the validation assessment allows for the model assessor to attribute errors to the measurement system as opposed to the model or experimental setup. Once the model(s) have been through the validation process, decision makers can better understand the risk associated with using these models. This paper describes one possible procedure to quantify the uncertainty of the data acquisition (DAQ) system. This DAQ uncertainty procedure includes; developing a test system in hardware, employing it in a laboratory environment, developing a test procedure to cover expected signal ranges, and developing an analysis scheme. The successful implementation of this system will provide a reasonable measurement uncertainty associated with the DAQ equipment, in the chosen environment. This uncertainty can then be used to determine the trustworthiness of the results acquired.
机译:随着现代平行计算系统的出现,已经开发出更大和更准确的仿真模型来模拟现实世界的硬件。这些模型需要验证和验证(V&V),后者使用从代表性硬件获取的数据来确定模型的不确定性。对测量系统引入的错误到验证评估的理解允许模型评估员对测量系统的错误属性,而不是模型或实验设置。一旦模型通过验证过程,决策者可以更好地了解与使用这些模型相关的风险。本文介绍了一种可能的过程来量化数据采集(DAQ)系统的不确定性。此DAQ不确定性程序包括;在硬件中开发测试系统,在实验室环境中使用它,开发测试程序以覆盖预期信号范围,并开发分析方案。在所选环境中,该系统的成功实施将提供与DAQ设备相关的合理测量不确定性。然后可以使用这种不确定性来确定所获得的结果的可信度。

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