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Visible/ NIR on-line sensor for marine engine oil condition monitoring applying chemometric methods

机译:可见/ NIR在线传感器用于船用发动机油状况监测应用化学计量方法

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Marine engine oils are used for years without an oil change. During this long period of time the oil gets contaminated,not only by water and fuel but also by solid contaminants due to oxidation of the base oil, overreacted additives soot and other products of Heavy Fuel Oil combustion.This paper shows the design, development and assembly of a visible-near infrared (400-1100 nm) sensor that monitors several characteristics corresponding to in-use marine engine oil condition. Also, chemometric techniques (PLS) are applied for determining TBN, %insoluble in pentane, soot and water from visible-near infrared spectra, having in mind the low resolution capability of the extracted on-line sensor signal. Different prediction models for each oil parameter were obtained. These prediction models were developed by partial least squares regression from the VIS/NIR spectra.Finally, the sensor has been tested at low-speed crosshead engine (two stroke engine). So that, reference values for TBN,%insoluble in pentane, soot and water were obtained in the laboratory for every sample. During the validation test, the models showed: a) a correlation higher than or equal to 0.85; b) the slope for the regression model tends to one; c) low bias; and d) the root mean square error of prediction (RMSEP) and the standard error of performance (SEP) were similar and close to the laboratory's estimated error.
机译:船用发动机油在没有换油的情况下使用。在这种长时间内,油被污染,不仅通过水和燃料而且由于氧化基础油的氧化,也通过氧化剂,过度添加剂和其他重质燃料油燃烧产品。本文显示了设计,开发和组装可见近红外(400-1100nm)传感器,监测对应于使用的船用发动机油状况的几种特性。此外,化学测量技术(PLS)用于确定来自可见近红外光谱的TBN,%不溶于戊烷,烟灰和水中,考虑到提取的在线传感器信号的低分辨率能力。获得每个油参数的不同预测模型。这些预测模型由来自VIS / NIR光谱的部分最小二乘回归开发。最后,在低速十字头发动机(两个行程发动机)下测试传感器。因此,在实验室中获得每个样品的实验室中获得TBN,戊烷和水中的TBN的参考值,戊烷,烟灰和水。在验证测试期间,模型显示:a)相关性高于或等于0.85; b)回归模型的斜率趋于一个; c)低偏见;而d)预测的根均线误差(RMSEP)和性能标准误差(SEP)类似,接近实验室的估计误差。

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