基于高光谱技术的厌氧发酵液固形物含量检测的研究

实时监测发酵液中固形物含量的变化,对控制厌氧发酵过程的稳定性具有重要作用。研究中采用近红外高光谱技术结合化学计量学方法,对水葫芦和稻草秸秆混合厌氧发酵过程中的固形物含量进行定量检测研究。与传统2540G(APHA,1990)标准方法相比,近红外高光谱技术具有无损、快速的优点。实验过程中,首先获取发酵液样本的高光谱信息,应用移动平均平滑法(MAS)进行光谱预处理,并采用竞争自适应重加权采样算法(CARS)、连续投影算法(SPA)和Random frog算法提取光谱特征信息,然后基于全谱和所选特征波长下的光谱信息分别建立总固形物含量(TS)和挥发性固形物含量(VS)的校正模型,建模方法包括偏最小二乘回归(PLSR)和最小二乘-支持向量机(LS-SVM)。研究表明,SPA-LS-SVM模型的预测结果最好,其中TS的预测均方根误差(RMSEP)及相关系数(R_p)分别为0.005 8和0.841;而VS的RMSEP和R_p分别为0.004 1和0.874。结果表明,利用近红外高光谱结合化学计量学方法可以实现厌氧发酵液中的固形物含量的检测,为布置光谱传感器以便定量检测厌氧发酵过程中的固形物含量奠定了理论依据。

Application of Hyperspectral Technology for the Determination of the Solid Concentration of the Anaerobic Digestion

Timely monitoring variations of the solid concentration plays a significant role in the stability control of the anaerobic digestion process .In this study ,infrared hyperspectral technology coupled with chemometrics methods is applied to detect the amount of solid concentration in which process water hyacinth and rice straw are co-digested .Compared to the traditional way (2540G APHA ,1990) ,it is faster and non-destructive .Firstly ,the hyperspectral information of fermentation broth is obtained by application of infrared hyperspectral and the spectroscopy data is pretreated by utilizing moving average smoothing (MAS) , and then adaptive weighted sampling competition (CARS) ,random frog (RF) and successive projections algorithm (SPA) are applied to extract characteristic wavelengths .Finally the calibration models of total solid (TS) and volatile solid (VS) are estab-lished based on the extracted characteristic wavelengths ,partial least square (PLS) and least square-support vector machine (LS-SVM) ,Which are taken to predict the solid concentration of fermentation broth .The study indicates that SPA-LS-SVM model achieves optimal result ,among which the root mean square error prediction (RMSEP) and correlation efficient (R) of the total solid concentration are respectively 0.0058 and 0.841 ;the root mean square error prediction and correlation efficient of the vola-tile solid concentration are respectively 0.0041 and 0.874 .The study shows that it is feasible to utilize infrared hyperspectral combined with chemometrics methods for prediction of the solid concentration of the fermentation broth ,and it can provide a the-oretic and practical basis for setting up a spectral sensor to detect the solid concentration of anaerobic digestion process .