Cryogenic air separation is currently the most widely used but energy-intensive technology for producing large quantities of oxygen and nitrogen, where cryogenic distillation consumes about 75% of the whole air separation field; however, its thermodynamic efficiency is very low. A novel structure of a full tower ideal internal thermally coupled air separation column (ITCASC) is therefore first proposed in this paper. A rigorous mathematic model and parameter analysis are then presented. Research results show that the proposed ITCASC process can yield high-purity products of both oxygen and nitrogen simultaneously and especially has a strong driving force of heat transfer, which reveals the larger energy-saving potential in the ITCASC process. Furthermore, an optimization model of the operation parameters is presented, where both the actual energysaving potential and the ideal energy-saving potential of ITCASC are investigated. Comparative studies against the conventional cryogenic air separation column (CASC) are carried out in detail. Research results show that the proposed ITCASC process has a larger extraction rate and better energy efficiency, where the nitrogen extraction rate increases 177.94% and the unit energy consumption decreases 40% compared to the CASC process with the same product purity requirements, revealing the advantages and promising application prospect of the proposed ITCASC process.

Raman spectra usually suffer from baseline drift caused by fluorescence or other reasons. Therefore, baseline correction is a necessary and crucial step that must be performed before subsequent processing and analysis of Raman spectra. An automated baseline correction method based on iterative morphological operations is proposed in this work. The method can adaptively determine the structuring element first and then gradually remove the spectral peaks during iteration to get an estimated baseline. Experiments on simulated data and real-world Raman data show that the proposed method is accurate, fast, and flexible for handling different kinds of baselines in various practical situations. The comparison of the proposed method with some state-of-the-art baseline correction methods demonstrates its advantages over the existing methods in terms of accuracy, adaptability, and flexibility. Although only Raman spectra are investigated in this paper, the proposed method is hopefully to be used for the baseline correction of other analytical instrumental signals, such as IR spectra and chromatograms.

We present a high throughput crop physiology condition monitoring system and corresponding monitoring method. The monitoring system can perform large-area chlorophyll fluorescence imaging and multispectral imaging. The monitoring method can determine the crop current condition continuously and non-destructively. We choose chlorophyll fluorescence parameters and relative reflectance of multispectral as the indicators of crop physiological status. Using tomato as experiment subject, the typical crop physiological stress, such as drought, nutrition deficiency and plant disease can be distinguished by the monitoring method. Furthermore, we have studied the correlation between the physiological indicators and the degree of stress. Besides realizing the continuous monitoring of crop physiology, the monitoring system and method provide the possibility of machine automatic diagnosis of the plant physiology.Highlights: A newly designed high throughput crop physiology monitoring system and the corresponding monitoring method are described in this study. Different types of stress can induce distinct fluorescence and spectral characteristics, which can be used to evaluate the physiological status of plants.

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.

No abstract