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Focusing on the defects in the lighting color of LED lamps and the chip heat exists in the traditional LED package which caused phosphor performance degradation, color temperature drift and the uneven light, the remote phosphor package which is emerging in recent years is used in this paper. With yellow-green YGG phosphor and nitrogen red phosphors mixing with silica gel, the remote phosphor is made and then encapsulated as the LED lamps. A lot of experiments were made to determine the best ratio of yellow green phosphor, red phosphor and silica gel, LED lamps with different color temperature was prepared. The lamps were also tested and analyzed with some parameters such as e color coordinates, luminous efficiency, color rendering index (CRI), R9, color quality scale (CQS), color temperature, and the gamut area index (GAI), which provide a more objective and comprehensive evaluation to the high quality LED lighting. Experimental results show that the optimum ratio of red and yellow-green phosphor is 1∶7.6, and total phosphor with silica gel is 1∶5，at this time the white LED lighting color temperature is 4 113 K, the color coordinate (x, y) is (0.375 4, 0.373 1), luminous efficiency is 52.33 lm·w-1, color gamut is 0.981, color rendering index is up to 96, R9 is 97, color quality scale Qa is up to 93, and the gamut area index is 79. Compared with the traditional packaging，the surface temperature ofthe remote phosphor encapsulated fluorescent plate is much lower than that of adhesive dispensing encapsulation, which can effectively avoid the harmful effect caused by high temperature on the LED.

In order to realize rapid identification of dried red jujubes, this paper proposes a method based on near-infrared hyperspectral imaging technology. The near-infrared hyperspectral images (1 000～1 600 nm) of 240 samples in total from 4 cultivars of dried red jujubes will be acquired. The samples are to be divided into the calibration set and the prediction set in the ratio of 2∶1. 7, 8, 10 effective wavelengths are to be selected by principal component analysis(PCA), x-loading weight(x-LW)and successive projection algorithm(SPA) respectively. The dimensionality of original hyperspectral images will be reduced with PCA, and texture features of the first principal component image are to be extracted with gray-level co-occurrence matrix(GLCM).The partial least squares-discriminant analysis(PLS-DA), back propagation neural network(BPNN)and least square support vector machine(LS-SVM) are to be applied to build identification models with the selected effective wavelengths, texture features and fusion of the former two features. The identification rates of the models based on fusion features will be higher than those of models based on the spectral features or texture features respectively. The BPNN models based on the fusion features will obtain the best results, whose identification rates of prediction set are to be 100%. The results in this paper indicate that the near-infrared hyperspectral imaging technology has great potential to identify the dried red jujubes rapidly.

The water inrush should been rapidly and accurately identified during preventing coalmine water inrush. The laser induced fluorescent (LIF) spectrum technology provides a new method to identify water inrush with the characteristics of high sensitivity, quick and accurate monitoring. In order to identify water inrush, this paper introduces the spectrum technology of LIF to obtain water inrush fluorescence spectra data. The spectral preprocessing methods of Savitzky-Golay(SG) and Multiplicative Scatter Correction (MSC) have been used to eliminate noise spectra in collecting process. Principal component analysis (PCA) extracts feature information, for SG reprocessing data, when the number of principal component is 3, the cumulative contribution rate can reach 99.76 percent. This method has largely retained the information of original data. This paper chooses the classification model with 3 layers BP neural network, constructing by different training and testing sets. The classification model with SG preprocessing has achieved accurate identification, however, appeared few false identification for MSC and original data. The result shows that SG preprocessing is better than MSC. Research results show that the classification model with PCA and BP neural network can effectively identify coalmine water inrush, and have the strong self-organizing, self-learning ability.

In terms of water quality monitoring based on the ultraviolet-visible spectroscopy, different optical path lengths of spectrometer probe need to be set to maintain higher signal-to-noise ratio of the spectra when the water body measured is complex and changeable. However, large numbers of experiments always have to be undertaken to get the appropriate optical path length, which is difficult to meet the demand of real-time, accurate, sensitive and stable online monitoring system. In this paper, an optimized spectra fusion algorithm was developed to improve the signal-to-noise ratio of fused spectra from two independent spectra that were acquired using two different optical path lengths. In the fusion algorithm, the sliding-pane method was applied to obtain the distribution of noise variance of the spectra, so the region of strong noise in the spectra could be determined. Due to different signal intensity of spectra with long and short optical path length, genetic algorithm was used to calculate the optimal gain matching rate of fusion. Finally, according to the distribution of noise variance, piecewise weighted method is applied to achieve a fusion spectrum with higher signal-to-noise ratio. The experimental results showed that the fusion algorithm could effectively enhance the signal-to-noise ratio of the fused spectra for each sample without altering the optical path length; the noise within 200~250 nm was suppressed and the low-noise and high-sensitivity spectra in the visible band were preserved; Zero interference was moved to the left of 220 nm of the spectrum. This means the fusion algorithm not only shows improvements in both signal-to-noise ratio and the detailed characteristics of the spectrum, but also reduces the excessive number of experiments in order to optimize optical path length and minimize noise in spectra. It has important practical significance to broaden the application range of the ultraviolet-visible spectroscopy based water quality monitoring system.

Diagnostic absorption features can indicate the existence of specific materials, which is the foundation of mineral analysis with optical remote sensing data. In hyperspectral data processing, the most commonly used method to extract absorption feature, is Continuum Removal (CR). As for multispectral data, Principle Component Analysis and other indirect methods were used to extract absorption information, and little research has been done on full-band absorption feature extraction. Classification of similar minerals is one of the major difficulties in mineral spectral analysis, while there is no valid index for spectral difference between similar mineral groups. Absorption feature extraction may improve the classification accuracy, but there is no research to investigate the impact of absorption feature extraction on spectral difference between similar minerals. This paper summarized the principle of mineral spectral difference, and proposed the concept of Class Separability Ratio (CSR), which was verified to be a valid index for spectral difference between similar mineral categories. Through comparison experiments on alunite and kaolinite spectra, including USGS spectral library spectra and resampled spectra in accordance with the band settings of HYPERION, ASTER and OLI, the impact of absorption feature extraction on spectral difference between similar minerals were investigated. Experimental results show that valid absorption feature extraction can greatly enhance the spectral difference between similar minerals, and the spectral difference is positively correlated with spectral resolution. Besides, the results of CR can be severely affected by spectral resolution and band center positions, and the absorption feature spectra extraction results for multispectral datasets need to be improved. This research laid the foundation of precise identification between similar mineral categories, and provided valuable reference for the band settings of future geology remote sensing sensors.

Based on the advantage of spectroscopy method and the significant effect of ·OH and ·O in advanced oxidation degradation system, the change of relative emission spectra intensities of the ·OH and the ·O in a pulsed discharge plasma (PDP) system bubbled with oxygen were tested by using the spectrum detecting technique in this research. The PDP system with needle-to-net electrode was set up in the paper to remediate the polluted soil. The relative emission spectra intensities of the ·OH and the ·O formed in the PDP system with oxygen (O2) bubbling were detected with the spectrograph to illustrate the critical effect of the ·OH and the ·O on the organic compound degradation in the PDP system. The changes of the relative emission spectra intensities of the ·OH and the ·O under the conditions of without soil addition, with the original soil addition, with the organic compound polluted soil addition and with the organic compound-heavy metal polluted soil addition were firstly investigated in the paper. The effect of peak pulse voltage, electrode gap and O2 flow rate on the relative emission spectra intensities of the ·OH and the ·O were also studied to explain the changing rule of the active species in the PDP system. The obtained results show that the addition of soil are beneficial to the formation of the ·OH and the ·O in PDP system for the soil remediation. The relative emission spectra intensities of the ·OH and the ·O in the PDP system with organic compounds polluted soil addition were lower than those in the PDP system with the original soil addition, which proved the oxidation of the ·OH and the ·O on the organic compounds degradation in the remediation system, and the addition of heavy metal ions were favorable to the degradation of the organic compounds in the PDP system. Furthermore, the increase of the peak pulse voltage as well as theO2 flow rate was in favor of the formation of the ·OH and the ·O, while the relative emission spectra intensities of the ·OH and the ·O were lower under the condition of the higher electrode gap, which demonstrated that the higher electrode gap were not in favor of the active species formation. In the study, based on the description of the pivotal role of ·OH and the ·O in the PDP system for the polluted soil remediation, the influence rule of the main factors during the process of polluted soil remediation in the PDP system on the content of ·OH and the ·O were analyzed. This research will provide some basic experimental evidence for the application of PDP technology on the polluted soil remediation.

High value-added utilization of solid wastes is one of the important ways of sustainable development. A novel pore size-controlled alkali-activated steel slag-based cementitious material (PASSCM) was synthesized by adjusting the content of pore forming agent of acrylic resin emulsion. Meanwhiel, a new type of porous steel slag-based catalyst loaded CeO2 was prepared via incipient wetness impregnation method in the paper. The composition, structure and optical properties of photocatalysts were characterized with XRF, XRD, BET and UV-Vis DRS. Meanwhile, the photocatalytic performance of hydrogen production from water was evaluated. The results showed that adding pore-forming agent changed the pore structure and the mesoporous volume increased by 70.27% of alkali-activated steel slag-based cementitious material. The mesoporous volume increased by 144.14% in photocatalyst loaded 8 Wt% CeO2. In the simulated solar source irradiation for 6 h, the photocatalyst loaded 8wt%CeO2 exhibiting the highest photocatalytic hydrogen production activity (7 653 μmol·g-1) and hydrogen generation rate [1 275.5 μmol·(g·h)-1], which were attributed to mesoporous volume increases the mass transfer rate of the water molecules, and in the formation of the coupled semiconductors, the high dispersion of the CeO2 active component and the FeO in the carrier promoted the high efficiency separation of the photogenerated electron-hole pairs.

For the determination of molybdenum in molybdenum concentrate，lead molybdate gravimetric method was considered as standard method. In order to ensure the lead ions to be washed thoroughly from the entrained precipitate, lead molybdate precipitate was washed, filtered repeatedly, then ashed and burned. This method cannot satisfy the rapid measurement demand of mineral processing and metallurgy scientific research due to its time consuming. In the present work, molybdenum was determined by atomic absorption spectrometry indirectly and a rapid analysis method for molybdenum in molybdenum concentrate was proposed. The sample was dissolved by nitric acid, potassium chlorate and sulfuric acid, pH was adjusted by acetic acid and ammonium acetate buffer solution to pH 5～7, then a certain amount and excess of lead standard was added. Based on lead molybdate was considered as undissolved electrolyte on room temperature, the solubility of lead molybdate was 1.16×10-5g, far less than 0.01 g, was considered as the undissolved electrolyte, the electrolyte insoluble at a certain temperature can complete precipitation, usually compared with the solubility production product Qc and the relative size of constant Ksp, when Qc>Ksp, solution was supersaturated, precipitation was precipitate completely, the content of molybdenum in molybdenum concentrate was 40%~60%, the amount of lead was 0.125 0~0.150 0 g, took the minimum calculated solution lead molybdate ion product, Qc＝[Pb2+][MoO2-4]=2.51×10-5，Ksp＝1.0×10-13，QcKsp，Therefore lead molybdate precipitate can be precipitated completely, after dry filtered, the excess of lead ions were determined by atomic absorption spectrometry, the content of molybdenum was calculated by subtraction method. In this paper, the amount of acetic acid-ammonium acetate buffer solution, the amount of lead standard, time of lead molybdate precipitation, heating time and maximum amount of coexisting ions such as W6+, Sn4+, Cu2+, etc were investigated. Compared with lead molybdate gravimetric method, repeatedly washing, ashing and burning with lead molybdate were eliminated by proposed method, which was simple, easy to master and was able to cut the analysis time in half. The control experiments were conducted by lead molybdate gravimetric method and proposed method. After the results were implemented by mathematical statistics, it can be concluded that it had good accuracy and precision for the proposed method, which can be applied to rapid analysis of molybdenum in molybdenum concentrate for mineral processing and metallurgy.

Polarization imaging contains rich target parameters including spectrum, radiant intensity, polarization state, space geometry, etc. Polarization imaging can improve the target detection and recognition ability. The infrared polarization imaging is a new infrared detect technology in recent years. Infrared polarization imaging mainly aims to detect and identify the target with the difference of infrared radiation polarization characteristic between target and scene. But the state of polarization is affected by transmission medium in the transmission process of infrared radiation polarization information while the common method is to analyze the infrared radiation polarization characteristics of target that is not able to describe effects of all interrelated parameters and is difficult to estimate influence factors in the process of transmission. The equation of infrared polarized radiation is established through bidirectional reflectance distribution function based on micro-facet theory. And the mathematical model of the relationship between infrared radiation polarization degree and emissivity is derived in this paper. Result shows that the influence of target surface emissivity on the infrared degree can be ignored. On the basis of theoretical analysis, the infrared spectrum polarization imaging tests are unfolded, and the analysis of test data is consistent with the theoretical analysis. It is concluded that the correlation between the polarization degree of infrared and the emissivity of target surface can be neglected. The research production of this paper is conductive to increase of target detect efficiency, and it will provide new ways and means for camouflage target detect and identify. Therefore, the research production can be applied to detect and identify the camouflage target that is accomplished camouflage through change emissivity of camouflage target surface.

Facing the problem of choosing different data source as compressing object results in different compression effect, several techniques are investigated to explore a better data source which can reduce the loss of image and spectral information while getting higher compression ratio in the compression work of the large aperture static imaging spectrometer. In this paper the optical path difference dimension data source of LASIS was proposed after analyzing the characteristic of LASIS and then compared with the LASIS and LAMIS data source in detail. The SWIR data collected with the principle prototype of LASIS were used in our experiment. Firstly, three forms of data sources were extracted after detailedly introducing their data characteristic and extracting methods. Secondly, the mature algorithms in engineering JPEG and JPEG2000 were employed to compress and reconstruct the three forms of data sources respectively. Finally, the compression effect was evaluated in the aspect of image content, interference dimension, spectral dimension and compression ratio respectively, and the original spectral curves of three materials choosing from the field of view and those after reconstruction were extracted next, then the loss of spectral information of these three materials were measured by using the SA (Spectral Angle) and RQE (Relative Quadratic Error) values of the spectral curves to evaluate the compression effect. It is demonstrated that using the optical path difference dimension data as compressing object shows obvious advantages compared with LASIS and LAMIS, which achieves a combination of higher compression ratio, lower mean square error, lower peak signal noise ratio and less information loss that is competitive with the best results from the literature. The results show that the proposed optical path difference dimension data source has good performance in preserving the spatial and spectral information during the compression of LASIS than the other two common forms data sources of LASIS.