State Key Lab of Industrial Control Technology, Zhejiang University, Hangzhou, China 310027.
Appl Spectrosc. 2011 Nov;65(11):1300-6. doi: 10.1366/10-06169.
Raman spectral analysis integrated with multivariate calibration is a fast and effective solution to monitor chemical product properties. However, Raman instruments utilizing charge-coupled device (CCD) detectors suffer from occasional spikes caused by cosmic rays. Cosmic spikes can disturb or even destroy the meaningful chemical information expressed by normal Raman spectra. In online monitoring, some cosmic spikes have intensity and bandwidth similar to normal Raman peaks of chemical components when a low resolution and cost-effective Raman instrument is used. Moreover, the online Raman spectra always contain variations of strong Raman peaks and fluorescence. Current spike-removal methods seem to have difficulty detecting and recovering cosmic spikes in these online Raman spectra. Therefore, an improved algorithm is proposed. In this algorithm, a new scheme composed of intensity identification and local moving window correlation analysis is introduced for cosmic spike detection; intensity identification based on derivative spectra and local linear fitting approximation are used for the recovery of cosmic spikes. The algorithm is proved to be simple and effective and has been applied in an online Raman instrument installed at a continuous catalytic reforming unit in a refinery.
拉曼光谱分析与多元校准相结合是监测化学产品特性的一种快速有效的解决方案。然而，利用电荷耦合器件（CCD）探测器的拉曼仪器偶尔会受到宇宙射线的干扰而产生尖峰。宇宙尖峰会干扰甚至破坏正常拉曼光谱所表达的有意义的化学信息。在在线监测中，当使用低分辨率和具有成本效益的拉曼仪器时，一些宇宙尖峰的强度和带宽与化学组分的正常拉曼峰相似。此外，在线拉曼光谱总是包含强拉曼峰和荧光的变化。当前的去尖峰方法似乎难以检测和恢复这些在线拉曼光谱中的宇宙尖峰。因此，提出了一种改进的算法。在该算法中，引入了一种由强度识别和局部移动窗口相关分析组成的新方案，用于宇宙尖峰检测；基于导数光谱和局部线性拟合逼近的强度识别用于宇宙尖峰的恢复。该算法被证明简单有效，并已应用于安装在炼油厂连续催化重整装置中的在线拉曼仪器中。
