矿物油的使用是造成雾霾等空气污染问题的重要原因。 矿物油荧光光谱检测系统光谱消噪处理的有效性和快速性是在线实时监测系统的热点问题。 研究应用提升算法小波变换(LWT)矿物油荧光光谱去噪的方法。 与传统的离散小波变换(DWT)相比, 提升小波变换将现有的小波滤波器分解成基本的构造模块, 分步骤完成变换, 结构简单, 运算速度快。 在矿物油荧光光谱去噪过程中具有运算量低、 原位运算和便于实现的特点, 有效解决了传统小波变换在这方面的不足。 提升算法的小波变换、 传统离散小波变换和经验模态变换(EMD)分别运用到0#柴油、 97#汽油、 煤油三种矿物油的荧光光谱去噪中, 评价去噪效果指标的信噪比(SNR)、 重构均方根误差(RMSE)和波形相似度(NCC)证明了提升方法小波变换用于矿物油荧光光谱去噪的有效性。 同时, 提升算法变换能提高构造的灵活性和运算的简单性使消噪时间降低62%, 证明了提升算法的小波变换运用到矿物油荧光光谱去噪中的快速性, 适于矿物油实时消噪处理系统。

The use of the mineral oil is an important cause of air pollution such as fog. The effectiveness and rapidity of the de-noising processing in mineral oil fluorescence spectroscopy detection system is a hot issue of the online real-time monitoring system. The de-noising method of the lifting wavelet transform (LWT) in the application of mineral oil fluorescence spectrum is proposed. Compared with traditional discrete wavelet transform (DWT), this wavelet transform method decomposes the existing wavelet filter module into the basic construction modules and steps to complete the transform with simplicity and a fast speed. There are characteristics of low computational complexity, in situ operation and the easy implement in the denoising process of mineral oil fluorescence spectra. The LWT can effectively solve the problems in these respects. The three methods of LWT, DWT and EMD are applied to the fluorescence spectra of 0# diesel oil, 97# gasoline and kerosene. The indicators evaluating de-noising effect such as the Signal-to-Noise Ratio (SNR), Mean Squared Error (MSE) and Normalied Correlation Coefficient (NCC) of the three kinds of mineral oil in the fluorescence spectra denoising prove the effectiveness of the lifting scheme wavelet transform in the application of mineral oil fluorescence spectrum. Meanwhile, the lifting scheme transform can improve the flexibility of structure and operation simplicity that makes the de-noising time reduced by 62%, validating the speediness of the de-noising method of the LWT in the application of mineral oil fluorescence spectrum and it is suitable for mineral oil fast de-noising processing system in real time.