基于拉曼光谱荧光背景的痕量原油泄漏检测方法

炼化企业在原油和常压蒸馏塔侧线轻质油换热过程中存在原油泄漏问题，进而对安全生产和后续加工环节质量控制造成不利影响。利用拉曼光谱荧光背景对原油敏感的特点，可以实现轻质油中痕量原油的检测。扫描90个含有痕量原油的常压蒸馏塔塔顶石脑油样本拉曼光谱作为试验数据，采用偏最小二乘回归法结合遗传算法、随机蛙跳算法以及竞争自适应重加权采样算法建模。其中检测效果最好的是竞争自适应重加权采样算法与偏最小二乘法结合的方法，预测均方根误差为1.5674 μg/g。该研究表明使用拉曼光谱荧光背景进行轻质油痕量原油检测，在算法优化后可以精确检测到质量分数1~100 μg/g的痕量原油，满足炼化企业生产要求。

DETECTION METHOD OF TRACE AMOUNTS OF CRUDE OIL LEAKAGE BASED ON RAMAN FLUORESCENCE BACKGROUND

In the process of heat exchange between crude oil and light oil on the side line of atmospheric distillation column, there is the problem of crude oil leakage in refining and chemical enterprises, which has an adverse effect on the safety production and subsequent processing. Based on the sensitivity of Raman fluorescence background to crude oil, the detection of trace amounts of crude oil in light oil was introduced. Raman spectra of 90 naphtha samples containing trace amounts of crude oil were scanned as experimental data, and the model was established using partial least squares regression (PLSR) combined with genetic algorithm (GA), random frog algorithm (RF) and competitive adaptive reweighting sampling algorithm (CARS). The best model is the combination of CARS and PLSR, in which RMSEP is 1.567 4 μg/g. The results show that the detection method using Raman spectral fluorescence background can be used to accurately detect trace crude oil of 1-100 μg/g after algorithm optimization, which can fully meet the requirements of refining and chemical enterprises.