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Using artificial intelligence to aid measurement accuracy and reliability in coriolis gas flow meters

机译：使用人工智能帮助科里奥利气体流量计的测量准确性和可靠性

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摘要

Coriolis is one of the fastest growing technologies in the oil and gas flow measurement. Flow sensitivity, pressure drop, temperature changes and increased noise level affects the accuracy and reliability of these types of transmitters. However in most situations those parameters are not constant and not a mathematical model exist to include in the logic for the actual gas flow calculation. AGA Report Number 11 specifically concentrates on the measurement of natural gas and the impact of expanded compositional ranges on the flow calculation. Using Artificial intelligence enables performance characteristics that are much better than traditional metering technologies. Compressibility factors for natural gas and other Hydrocarbon gases are some of the factors that will be considered in artificial intelligence model for gas flow measurement. In this paper uncertain input parameters will be identified as fuzzy variables and will be integrated into fuzzy calculation of the gas flow measurement. It can be argued that Coriolis technology integrated with artificial intelligence greatly increases the accuracy and robustness of flow calculation. Uses of artificial intelligence in these types of Coriolis flow meters can minimize error and extend sensor life. This paper will discuss the appropriate implementation of such expert system with Coriolis flow measurement technology.
机译：科里奥利（Coriolis）是油气流量测量中发展最快的技术之一。流量灵敏度，压降，温度变化和噪声水平升高会影响这些类型的变送器的准确性和可靠性。但是，在大多数情况下，这些参数不是恒定的，并且不存在数学模型包含在实际气体流量计算的逻辑中。 AGA第11号报告专门关注天然气的测量以及扩大的成分范围对流量计算的影响。使用人工智能可以实现比传统计量技术更好的性能特征。天然气和其他烃类气体的可压缩性因素是人工智能模型中用于气体流量测量的一些因素。在本文中，不确定的输入参数将被识别为模糊变量，并将被集成到气体流量测量的模糊计算中。可以说科里奥利技术与人工智能相集成大大提高了流量计算的准确性和鲁棒性。在这些类型的科里奥利流量计中使用人工智能可以最大程度地减少误差并延长传感器寿命。本文将讨论采用科里奥利流量测量技术的此类专家系统的适当实现。

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