小反射波导元件高频状态下驻波比的测量

介绍了一种测量小反射波导元件高频状态下驻波比的方法 ,可解决通常方法解决不了的问题。该方法具有使用设备简单 ,操作方便直观的特点。还介绍了在波导元件加工生产过程中利用此方法调整波导元件 。

浅层小反射资料处理方法及其应用

在复杂地区的地震数据处理中，因地形起伏剧烈、低降速带厚度或速度变化较大等因素，会产生较严重的静校正问题，因此确定近地表结构尤为重要。浅层小折射和微测井方法是确定近地表结构的有效方法，但它们也有局限性。基于反射波勘探的浅层小反射勘探，通过对表层反射界面进行观测来建立近地表模型，是解决近地表结构最有效的方法之一。主要介绍了浅层小反射资料处理方法及在实际测线生上产的应用。

微波测量线测量误差的自动校正

分析了微波测量线误差校正的方法 ,提出了仅用小反射滑动负载即可确定测量线误差网络参数的新方法 ,给出了测量线误差网络参数的最小二乘法显式解 ,并实现了测量线误差网络参数的CAT(ComputerAidedTest) .利用误差网络参数 ,对被测网络的输入反射系数进行误差的自动校正 。

复合函数渐变传输线研究

在已有渐变线类型的基础上,讨论了一种新型的、基于复合函数的渐变传输线,这种复合函数渐变线具有阻抗可调、低反射系数的特点,上述特点正是工业设计应用中所需要的。文章首先给出基于小反射理论的渐变阻抗函数的反射系数响应,然后推导出复合函数的阻抗响应,最后通过实例的方式,仿真出复合函数的阻抗特性和反射系数特性,并与指数渐变函数和三角渐变函数的阻抗特性和反射系数特性进行了比较,发现复合函数具有比指数渐变函数更低的反射系数,阻抗比三角渐变函数更具可调的灵活性。

微波加热装置打火问题的电磁仿真

以某型号微波加热装置为代表,根据传输线多重反射原理和小反射原理,提出了一种改善微波加热装置打火问题的新方法:首先对微波传播路径上的波导管结构进行优化,研究微波加热装置波导管结构参数对每一阶段反射系数的影响,找到影响每一阶段反射系数的最优参数,组成一个反射最小的波导管结构,再利用凸包对微波加热装置的整体阻抗进行匹配,从而达到改善微波加热装置打火问题的目的。进一步的测试研究证实了该方法对微波加热装置打火问题改善的有效性。

Relationship of 2 100-2 300 nm Spectral Characteristics of Wheat Canopy to Leaf Area Index and Leaf N as Affected by Leaf Water Content

The effects of leaf water status in a wheat canopy on the accuracy of estimating leaf area index (LAI) and N were determined in this study using extracted spectral characteristics in the 2 000-2 300 nm region of the short wave infrared (SWI) band. A newly defined spectral index, relative adsorptive index in the 2000-2300 nm region (RAI2000-2300), which can be calculated by RAI2000-2300 = (R2224 - R2054) (R2224 + R2054)-1 with R being the reflectance at 2224 or 2054 nm, was utilized. This spectral index, RAI2000-2300, was significantly correlated (P < 0.01) with green LAI and leaf N concentration and proved to be potentially valuable for monitoring plant green LAI and leaf N at the field canopy scale. Moreover, plant LAI could be monitored more easily and more successfully than plant leaf N. The study also showed that leaf water had a strong masking effect on the 2 000-2 300 nm spectral characteristics and both the coefficient between RAI2000-2300 and green LAI and that between RAI2000-2300 and leaf N content decreased as leaf water content increased.

Rapid Identification for Drought Resistance of Wheat Using Near-infrared Diffuse Reflectance Spectroscopy

[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drought resistance were selected and were classified according to their drought resistance grades determined by the Technical Specification of Identification and Evaluation for Drought Resistance in Wheat （GB/T 21127-2007）. In addition, the harvested wheat seed samples were spectrally analyzed with FOSS NIRSystems5000 near-infrared spectrum analyzer for grain quality （full spectrum analyzer） and then the forecasted regression equations were established. [Result] After the establishment of a database and validation, dis- criminated functions were obtained. The determination coefficient （RSQ） and coeffi- cients of determination for cross validation （1-VR） in the discriminant function built with seed samples from water stress area were 0.846 0 and 0.781 8, respectively, which indicated that the consistency between drought resistance and spectral charac- teristics in wheat varieties was good, and there was high correlation between the near-infrared diffuse reflectance spectra of seeds and the drought resistance in wheat. [Conclusiou] Under water stress condition, it is feasible to establish a conve- nient, rapid and no-damage identification system for the drought resistance in wheat by using the near-infrared diffuse reflectance spectrum technique to scan wheat seeds.

The Study of Using Near-infrared Diffuse Reflectance Spectroscopy Rapid Identify Wheat Drought Resistance-Ⅱ

[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were chosen and drought-tolerance degrees of wheat were graded and identified according to Winter-wheat Drought Tol- erance Evaluation Technical Standards （GB/T 21127-2007）, and harvest wheat grains underwent spectrum collection, with a full-spectrum analyzer, to establish a database. [Result] Based on qualitative analysis and full-spectrum correlation research, the coef- ficient of determination （RSQ） and cross-validation coefficient of determination （1-VR） were concluded at 0.697 5 and 0.600 2, showing near-infrared diffuse reflectance spectroscopy is of significant differences among wheat varieties and of significant or extremely significant correlation with drought-tolerance indices. [Conclusion] The re- search indicates that to evaluate drought-tolerance of wheat with near-infrared diffuse reflectance spectroscopy is a rapid and feasible way, which is simple, convenient without damages on grains, and of practical values for construction wheat drought-tol- erance evaluation index system and identification of breeding materials.

Influence of inaccurate wavelet phase estimation on seismic inversion

On the assumption that the seismic wavelet amplitude spectrum is estimated accurately, a group of wavelets with different phase spectra, regarded as estimated wavelets, are used to implement linear least-squares inversion. During inversion, except for the wavelet phase, all other factors affecting inversion results are not taken into account. The inversion results of a sparse reflectivity model （or blocky impedance model） show that： （1） although the synthetic data using inversion results matches well with the original seismic data, the inverted reflectivity and acoustic impedance are different from that of the real model. （2） the inversion result reliability is dependent on the estimated wavelet Z transform root distribution. When the estimated wavelet Z transform roots only differ from that of the real wavelet near the unit circle, the inverted reflectivity and impedance are usually consistent with the real model; （3） although the synthetic data matches well with the original data and the Cauchy norm （or modified Cauchy norm） with a constant damping parameter has been optimized, the inverted results are still greatly different from the real model. Finally, we suggest using the L1 norm, Kurtosis, variation, Cauchy norm with adaptive damping parameter or/and modified Cauchy norm with adaptive damping parameter as evaluation criteria to reduce the bad influence of inaccurate wavelet phase estimation and obtain good results in theory.

Estimation of As and Cu Contamination in Agricultural Soils Around a Mining Area by Reflectance Spectroscopy:A Case Study

Concentrations of Iron (Fe), As, and Cu in soil samples from the fields near the Baoshan Mine in Hunan Province, China, were analyzed and soil spectral reflectance was measured with an ASD FieldSpec FR spectroradiometer (Analytical Spectral Devices, Inc., USA) under laboratory condition. Partial least square regression (PLSR) models were constructed for predicting soil metal concentrations. The data pre-processing methods, first and second derivatives (FD and SD), baseline correction (BC), standard normal variate (SNV), multiplicative scatter correction (MSC), and continuum removal (CR), were used for the spectral reflectance data pretreatments. Then, the prediction results were evaluated by relative root mean square error (RRMSE) and coefficients of determination (R 2 ). According to the criteria of minimal RRMSE and maximal R 2 , the PLSR models with the FD pretreatment (RRMSE = 0.24, R 2 = 0.61), SNV pretreatment (RRMSE = 0.08, R 2 = 0.78), and BC-pretreatment (RRMSE = 0.20, R 2 = 0.41) were considered as the final models for predicting As, Fe, and Cu, respectively. Wavebands at around 460, 1 400, 1 900, and 2 200 nm were selected as important spectral variables to construct final models. In conclusion, concentrations of heavy metals in contaminated soils could be indirectly assessed by soil spectra according to the correlation between the spectrally featureless components and Fe; therefore, spectral reflectance would be an alternative tool for monitoring soil heavy metals contamination.

Research on ultra-small textured surface of multicrystalline silicon solar cell

The ultra-small textured surface of multicrystalline silicon solar cell,prepared by electroless chemical-etching method,shows an excellent anti-reflection property over a wide spectral bandwidth.A novel back surface protection method and front surface passivation method have been used in the multicrystalline solar cells with ultra-small textured surfaces.With these improvements,the back surface remains intact after the etch process and the efficient minority lifetime is apparently increased.The test result shows that the solar cell with ultra-small textured surface can obtain better electrical performances by these improvements.

Model-Based Integrated Methods for Quantitative Estimation of Soil Salinity from Hyperspectral Remote Sensing Data:A Case Study of Selected South African Soils

Soil salinization is a land degradation process that leads to reduced agricultural yields. This study investigated the method that can best predict electrical conductivity (EC) in dry soils using individual bands, a normalized difference salinity index (NDSI), partial least squares regression (PLSR), and bagging PLSR. Soil spectral reflectance of dried, ground, and sieved soil samples containing varying amounts of EC was measured using an ASD FieldSpec spectrometer in a darkroom. Predictive models were computed using a training dataset. An independent validation dataset was used to validate the models. The results showed that good predictions could be made based on bagging PLSR using first derivative reflectance (validation R2 = 0.85), PLSR using untransformed reflectance (validation R2 = 0.70), NDSI (validation R2 = 0.65), and the untransformed individual band at 2257 nm (validation R2 = 0.60) predictive models. These suggested the potential of mapping soil salinity using airborne and/or satellite hyperspectral data during dry seasons.

Estimation of Organic Matter Content in Coastal Soil Using Reflectance Spectroscopy

Rapid determination of soil organic matter(SOM) using regression models based on soil reflectance spectral data serves an important function in precision agriculture. "Deviation of arch"(DOA)-based regression and partial least squares regression(PLSR)are two modeling approaches to predict SOM.However,few studies have explored the accuracy of the DOA-based regression and PLSR models.Therefore,the DOA-based regression and PLSR were applied to the visible near-infrared(VNIR) spectra to estimate SOM content in the case of various dataset divisions.A two-fold cross-validation scheme was adopted and repeated 10 000 times for rigorous evaluation of the DOA-based models in comparison with the widely used PLSR model.Soil samples were collected for SOM analysis in the coastal area of northern Jiangsu Province,China.The results indicated that both modelling methods provided reasonable estimation of SOM,with PLSR outperforming DOA-based regression in general.However,the performance of PLSR for the validation dataset decreased more noticeably.Among the four DOA-based regression models,a linear model provided the best estimation of SOM and a cutoff of SOM content(19.76 g kg^(-1)),and the performance for calibration and validation datasets was consistent.As the SOM content exceeded 19.76 g kg^(-1),SOM became more effective in masking the spectral features of other soil properties to a certain extent.This work confirmed that reflectance spectroscopy combined with PLSR could serve as a non-destructive and cost-efficient way for rapid determination of SOM when hyperspectral data were available.The DOA-based model,which requires only 3 bands in the visible spectra,also provided SOM estimation with acceptable accuracy.

Densely quaternized anion exchange membranes synthesized from Ullmann coupling extension of ionic segments for vanadium redox flow batteries

Membranes with high ion conductivity and selectivity are important for vanadium redox flow batteries.Herein, densely quaternized anion exchange membranes based on quaternary ammonium functionalized octa-benzylmethyl-containing poly(fluorenyl ether ketone)s(QA-OMPFEKs) were prepared from the(i) condensation polymerization of a newly developed octa-benzylmethyl-containing bisphenol monomer via Ullmann coupling,(ii) bromination at the benzylmethyl sites using N-bromosuccinimide, and(iii)quaternization of the bromomethyl groups using trimethylamine. The QA-OMPFEK-20 with an ion exchange capacity(IEC) of 1.66 mmolg^-1 exhibited a higher SO42-conductivity(9.62mScm^-1) than that of the QA-TMPFEK-40(4.82mScm^-1) at room temperature, which had a slightly higher IEC of 1.73 mmolg-1but much lower QA density.The enhanced SO42-conductivity of QA-OMPFEK-20 was attributed to the ion-segregated structure arising from the densely anchored QA groups, which was validated by SAXS observation. Furthermore, the QA-OMPFEK-20 showed much lower VO2+permeability(1.24×10^-14m^2s^-1) than QA-TMPFEK-40(5.40×10^-13m^2s^-1) and Nafion N212(5.36×10^-12m^2s^-1), leading to improved Coulombic and energy efficiencies in Vanadium redox flow batteries(VRFBs). Therefore, the Ullmann coupling extension is a valuable approach for the development of high performance anion exchange membranes for VRFBs.

Mapping of Total Carbon and Clay Contents in Glacial Till Soil Using On-the-Go Near-Infrared Reflectance Spectroscopy and Partial Least Squares Regression

Characterizing spatial variability of soil attributes, using traditional soil sampling and laboratory analysis, is cost prohibitive. The potential benefit of managing soils on a site-specific basis is well established. High variations in glacial till soil render detailed soil mapping difficult with limited number of soil samples. To overcome this problem, this paper demonstrates the feasibility of soil carbon and clay mapping using the newly developed on-the-go near-infrared reflectance spectroscopy (NIRS). Compared with the geostatistics method, the partial least squares regression (PLSR), with NIRS measurements, could yield a more detailed map for both soil carbon and clay. Further, by using independent validation dataset, the accuracy of predicting could be improved significantly for soil clay content and only slightly for soil carbon content. Owing to the complexity of field conditions, more work on data processing and calibration modeling might be necessary for using on-the-go NIRS measurements.

Determination of soluble solid content and acidity of loquats based on FT-NIR spectroscopy

The near infrared （NIR） spectroscopy technique has been applied in many fields because of its advantages of simple preparation, fast response, and non-destructiveness. We investigated the potential of NIR spectroscopy in diffuse reflectance mode for determining the soluble solid content （SSC） and acidity （pH） of intact loquats. Two cultivars of loquats （Dahongpao and Jiajiaozhong） harvested from two orchards （Tangxi and Chun＇an, Zhejiang, China） were used for the measurement of NIR spectra between 800 and 2500 nm. A total of 400 loquats （100 samples of each cultivar from each orchard） were used in this study. Relationships between NIR spectra and SSC and acidity of loquats were evaluated using partial least square （PLS） method. Spectra preprocessing options included the first and second derivatives, multiple scatter correction （MSC）, and the standard normal variate （SNV）. Three separate spectral windows identified as full NIR （800-2500 nm）, short NIR （800-1100 rim）, and long NIR （1100-2500 nm） were studied in factorial combination with the preprocessing options. The models gave relatively good predictions of the SSC of loquats, with root mean square error of prediction （RMSEP） values of 1.21, 1.00, 0.965, and 1.16 °Brix for Tangxi-Dahongpao, Tangxi-Jiajiaozhong, Chun＇an-Dahongpao, and Chun＇an-Jiajiaozhong, respectively. The acidity prediction was not satisfactory, with the RMSEP of 0.382, 0.194, 0.388, and 0.361 for the above four loquats, respectively. The results indicate that NIR diffuse reflectance spectroscopy can be used to predict the SSC and acidity of loquat fruit.