Analysis on influencing factors of detecting chemical oxygen demand in water by ultraviolet absorption spectroscopy

Taking the standard solution and actual water samples as the research object, this paper studies the influence of various environmental factors (temperature, alkalinity (pH), inorganic salt ions and salinity) on the detection of chemical oxygen demand (COD) in water by ultra-violet (UV) spectrometry, analyzes the influence mechanism, and draws relevant conclusions. The results show that the UV absorbance of the COD standard solution and the actual river water samples varies very little with temperature. The value of pH has certain impact on both the standard solution and the actual water samples, but the pH values of the affected experimental samples are in different ranges. The effects of nitrogen salt ions (NO2- and NO3-) on the UV absorption spectra can be eliminated by intercepting the UV spectrum interval less affected for modeling. The influence of salinity values below 35‰ on the UV absorption spectrum of water is mainly concentrated in the spectral band of 200—250 nm, and the influence above 250 nm is very little. This paper provides a preliminary analysis and discussion on the influence mechanism and laws of various environmental factors in the detection of water quality parameters by UV spectrometry, which provides an experimental basis for selecting the optimal test conditions when establishing the COD prediction model.     

Detection of chemical oxygen demand in water based on UV absorption spectroscopy and PSO-LSSVM algorithm

A method of detecting chemical oxygen demand (COD) of water based on ultraviolet (UV) absorption spectra is proposed. The modeling and analysis of the standard samples and the actual water samples are carried out respectively. For the standard solution samples, the univariate linear models based on single wavelengths and the partial least square (PLS) model based on synergy interval partial least square (SiPLS) and moving window partial least square (MWPLS) are established. For the actual water samples, different pre-processing methods are used. SiPLS and MWPLS are used to select the characteristic bands. The least squares support vector machine algorithm optimized by particle swarm optimization (PSO-LSSVM) algorithm is used to establish the prediction model, and the prediction results of various models are compared. The results show that the optimal model is PSO-LSSVM which uses SiPLS to select the characteristic bands of the first derivative spectra (preprocessing method). The determination coefficient of the prediction set is 0.963 1, and the root mean square error of prediction (RMSEP) is 2.225 4 mg/L. PSO-LSSVM algorithm has good prediction performance for the analysis of COD in actual water samples by UV spectra. This paper provides a new design idea for the research and development of water quality detection optical sensor.     

Analysis on influencing factors of detecting chemical oxygen demand in water by three-dimensional spectroscopy

This paper focuses on the standard chemical oxygen demand(COD) liquid and studies the impact of pH, nitrite nitrogen, nitrate nitrogen, heavy metals, salinity, and other factors on fluorescence intensity and fluorescence peak positions during the detection of COD in water using fluorescence spectrometry. The influence mechanisms of different environmental factors on fluorescence spectra are also analyzed. Results indicate that pH value affects the fluorescence emission wavelength(Em), resulting ...     

无线桥接使信号覆盖范围更远

为了增加无线网络的覆盖范围,需要用到无线路由器的桥接或WDS功能,在具备WDS功能的无线路由器间进行正确桥接,即可延伸信号覆盖范围。     

阿拉善盟沙尘暴统计特征

通过对阿拉善盟2002—2009年常规气象资料的统计分析,结果表明,阿拉善盟沙尘暴天气以拐子湖为高发中心,以阿拉善左旗为低发中心;沙尘暴多发生在春、夏两季,冬季次之,秋季最少;阿拉善盟大风从西北偏北、东北偏北和东南偏东3个风方位来时,发生沙尘暴的概率最高;降水对沙尘暴具有一定的抑制作用,大风在春季时对沙尘暴影响最大.