Abstract Molecular management has become an important trend in petroleum refining, which relies on the information of petroleum composition. In this contribution, a simple and effective analytical approach is proposed for the rapid prediction of the more detailed molecular composition of naphtha samples based on raw near infrared (NIR) spectroscopy for the first time. The 101 samples of reformed naphtha were collected and determined, and Tchebichef curve moments (TCMs) were calculated directly from the raw NIR spectra and employed to establish linear models for the quantitative analysis of 26 hydrocarbons (PIONA) with different carbon numbers and components. For the obtained models, the average of RMSE of prediction is 0.10. According to the ratio of performance to deviation (SD/RMSEp), the 23 obtained TCM models achieved “excellent” predictive quality. By means of the conventional PLS method with spectral pretreatment, there were only 15 models with “excellent” predictive quality, which indicated that TCM method without any spectral preprocessing could provide more simple, accurate and reliable analytical results, and meet the requirements of fast assessment. This work suggests the feasibility of the proposed method for the rapid and non-destructive analysis of molecular composition in naphtha, which is significant in the determination of refinery operating conditions.

中文翻译：

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基于原始近红外光谱预测石脑油分子组成的有效且快速的方法

摘要 依赖于石油成分信息的分子管理已成为石油炼制的一个重要趋势。在这一贡献中，首次提出了一种简单有效的分析方法，用于基于原始近红外 (NIR) 光谱快速预测石脑油样品的更详细的分子组成。收集并测定了 101 个重整石脑油样品，直接从原始 NIR 光谱计算 Tchebichef 曲线矩 (TCM)，并用于建立线性模型，用于定量分析 26 种不同碳数和组分的碳氢化合物 (PIONA)。对于获得的模型，预测的均方根误差平均值为 0.10。根据性能偏差比（SD/RMSEp），获得的23个中医模型达到了“优秀”的预测质量。传统的PLS方法加上光谱预处理，只有15个模型具有“优秀”的预测质量，这表明没有任何光谱预处理的TCM方法可以提供更简单、准确和可靠的分析结果，满足快速评估的要求. 这项工作表明所提出的方法可用于石脑油中分子组成的快速无损分析，这对确定炼油厂操作条件具有重要意义。分析结果准确可靠，满足快速评估的要求。这项工作表明所提出的方法可用于石脑油中分子组成的快速无损分析，这对确定炼油厂操作条件具有重要意义。分析结果准确可靠，满足快速评估要求。这项工作表明所提出的方法可用于石脑油中分子组成的快速无损分析，这对确定炼油厂操作条件具有重要意义。