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Analysis and Modeling Methodologies for Heat Exchanges of Deep-Sea In Situ Spectroscopy Detection System Based on ROV

机译:基于ROV的原位光谱检测系统热交换器的分析与建模方法

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In recent years, cabled ocean observation technology has been increasingly used for deep sea in situ research. As sophisticated sensor or measurement system starts to be applied on a remotely operated vehicle (ROV), it presents the requirement to maintain a stable condition of measurement system cabin. In this paper, we introduce one kind of ROV-based Raman spectroscopy measurement system (DOCARS) and discuss the development characteristics of its cabin condition during profile measurement process. An available and straightforward modeling methodology is proposed to realize predictive control for this trend. This methodology is based on the Autoregressive Exogenous (ARX) model and is optimized through a series of sea-going test data. The fitting result demonstrates that during profile measurement processes this model can availably predict the development trends of DORCAS's cabin condition during the profile measurement process.
机译:近年来,有线海洋观测技术越来越多地用于深海原位研究。 由于复杂的传感器或测量系统开始应用于远程操作的车辆(ROV),因此它呈现了保持测量系统舱的稳定条件的要求。 在本文中,我们介绍了一种基于ROV的拉曼光谱测量系统(DOCARS),并在轮廓测量过程中讨论其舱室状况的开发特性。 提出了一种可用和简单的建模方法,以实现这种趋势的预测控制。 该方法基于自回归外源性(ARX)模型,并通过一系列海上测试数据进行了优化。 拟合结果表明,在轮廓测量过程期间,该模型可在轮廓测量过程中可用地预测Dorcas驾驶室条件的发展趋势。

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