Characteristics of laser-induced breakdown spectroscopy of liquid slag

Rapid online analysis of liquid slag is essential for optimizing the quality and energy efficiency of steel production. To investigate the key factors that affect the online measurement of refined slag using laser-induced breakdown spectroscopy(LIBS), this study examined the effects of slag composition and temperature on the intensity and stability of the LIBS spectra. The experimental temperature was controlled at three levels: 1350℃, 1400℃, and 1450℃. The results showed that slag composition and temperature significantly affected the intensity and stability of the LIBS spectra. Increasing the Fe content and temperature in the slag reduces its viscosity, resulting in an enhanced intensity and stability of the LIBS spectra. Additionally, 42 refined slag samples were quantitatively analyzed for Fe, Si, Ca, Mg, Al, and Mn at 1350℃, 1400℃, and 1450℃.The normalized full spectrum combined with partial least squares(PLS) quantification modeling was used, using the Ca Ⅱ 317.91 nm spectral line as an internal standard. The results show that using the internal standard normalization method can significantly reduce the influence of spectral fluctuations. Meanwhile, a temperature of 1450℃ has been found to yield superior results compared to both 1350℃ and 1400℃, and it is advantageous to conduct a quantitative analysis of the slag when it is in a “water-like” state with low viscosity.

DELIBERATlON TO THE DEFINITION OF TOOTH THICKNESS FOR INVOLUTE HELICAL GEAR IN INTERNATIONAL STANDARD ISO1122／1

The definitions of the normal chordal tooth thichness and the constant chord in interna-tional standard ISO 1122/1-1983(E) are analyzed according to the basic principle of involute cy-lindrical gear geometry. It is pointed out that in the case of spur gears, the two definitions arerespectively identical with generally recognized traditional formulas, but in the case of helical gears,they are respectively contradictory with their traditional formulas. The general principle of themethod of the two-point measuring for the tooth thickness of gears is analysized, and the calcula-tion formulas of the two-point measuring for the tooth thickness of the involute helical gear ispresented. It is proved theoretically that a constant chord can be measured with the method of thetwo-point measuring (with the tooth thickness caliper) while normal chordal tooth thickness cannot be measured with the tooth thickness caliper (the method of the two-point measuring). The is-sues of the two definitions of the tooth thickness in the international standard are analysed outagain in measurng.

Abnormal Behavior Detection and Recognition Method Based on Improved ResNet Model

The core technology in an intelligent video surveillance system is that detecting and recognizing abnormal behaviors timely and accurately.The key breakthrough point in recognizing abnormal behaviors is how to obtain the effective features of the picture,so as to solve the problem of recognizing them.In response to this difficulty,this paper introduces an adjustable jump link coefficients model based on the residual network.The effective coefficients for each layer of the network can be set after using this model to further improving the recognition accuracy of abnormal behavior.A convolution kernel of 1×1 size is added to reduce the number of parameters for the purpose of improving the speed of the model in this paper.In order to reduce the noise of the data edge,and at the same time,improve the accuracy of the data and speed up the training,a BN(Batch Normalization)layer is added before the activation function in this network.This paper trains this network model on the public ImageNet dataset,and then uses the transfer learning method to recognize these abnormal behaviors of human in the UTI behavior dataset processed by the YOLO_v3 target detection network.Under the same experimental conditions,compared with the original ResNet-50 model,the improved model in this paper has a 2.8%higher accuracy in recognition of abnormal behaviors on the public UTI dataset.

Analysis of Turbulence Characteristics over the Northern Tibetan Plateau Area

Based on CAMP/Tibet [Coordinated Enhanced Observing Period （CEOP） Asia-Australia Monsoon Project （CAMP） on the Tibetan Plateau] turbulent data collected at the Bujiao （B J） site of the Nagqu area, the turbulent structure and transportation characteristics in the near surface layer during summer are analyzed. The main results show that the relationship between the normalized standard deviation of 3D wind speed and stability satisfies the similarity law under both unstable and stable stratifications. The relations of normalized standard deviation of temperature and specific humidity to stability only obey the ＂-1/3 power law＂ under unstable conditions. In the case of stable stratifications, their relations to stability are dispersing. The sensible heat dominates in the dry period, while in the wet period, the latent heat is larger than the sensible heat.

Visible and Near-Infrared Spectroscopic Discriminant Analysis Applied to Identification of Soy Sauce Adulteration

The identification of soy sauce adulteration can avoid fraud, and protect the rights and interests of producers and consumers. Based on two measurement models (1 mm, 10 mm), the visible and near-infrared (Vis-NIR) spectroscopy combined with standard normal variate-partial least squares-discriminant analysis (SNV-PLS-DA) was used to establish the discriminant analysis models for adulterated and brewed soy sauces. Chubang soy sauce was selected as an identification brand (negative, 70). The adulteration samples (positive, 72) were prepared by mixing Chubang soy sauce and blended soy sauce with different adulteration rates. Among them, the “blended soy sauce” sample was concocted of salt water (NaCl), monosodium glutamate (C5H10NNaO5) and caramel color (C6H8O3). The rigorous calibration-prediction-validation sample design was adopted. For the case of 1 mm, five waveband models (visible, short-NIR, long-NIR, whole NIR and whole scanning regions) were established respectively;in the case of 10 mm, three waveband models (visible, short-NIR and visible-short-NIR regions) for unsaturated absorption were also established respectively. In independent validation, the models of all wavebands in the cases of 1 mm and 10 mm have achieved good discrimination effects. For the case of 1 mm, the visible model achieved the optimal validation effect, the validation recognition-accuracy rate (RARV) was 99.6%;while in the case of 10 mm, both the visible and visible-short-NIR models achieved the optimal validation effect (RARV = 100%). The detection method does not require reagents and is fast and simple, which is easy to promote the application. The results can provide valuable reference for designing small dedicated spectrometers with different measurement modals and different spectral regions.

Spectroscopy-Based Soil Organic Matter Estimation in Brown Forest Soil Areas of the Shandong Peninsula, China

Soil organic matter (SOM) is important for plant growth and production. Conventional analyses of SOM are expensive and time consuming. Hyperspectral remote sensing is an alternative approach for SOM estimation. In this study, the diffuse reflectance spectra of soil samples from Qixia City, the Shandong Peninsula, China, were measured with an ASD FieldSpec 3 portable object spectrometer (Analytical Spectral Devices Inc., Boulder, USA). Raw spectral reflectance data were transformed using four methods: nine points weighted moving average (NWMA), NWMA with first derivative (NWMA + FD), NWMA with standard normal variate (NWMA + SNV), and NWMA with min-max standardization (NWMA + MS). These data were analyzed and correlated with SOM content. The evaluation model was established using support vector machine regression (SVM) with sensitive wavelengths. The results showed that NWMA + FD was the best of the four pretreatment methods. The sensitive wavelengths based on NWMA + FD were 917, 991, 1 007, 1 996, and 2 267 nm. The SVM model established with the above-mentioned five sensitive wavelengths was significant ( R 2 = 0.875, root mean square error (RMSE) = 0.107 g kg −1 for calibration set;R 2 = 0.853, RMSE = 0.097 g kg −1 for validation set). The results indicate that hyperspectral remote sensing can quickly and accurately predict SOM content in the brown forest soil areas of the Shandong Peninsula. This is a novel approach for rapid monitoring and accurate diagnosis of brown forest soil nutrients.

Derivative-Based Techniques for Geological Contact Mapping from Gravity Data

Gravity anomalies illuminate subsurface lithology and geological structure in three dimensions,which is vital for studies of concealed faults,sedimentary basins,basement lithology,and other geological targets.Although not all geological contacts correspond to lithological contacts,the contact mapping provides key information on structural regimes,deformation styles and trends.Many techniques for contact mapping have been developed.Here,we evaluate five methods applied to gridded data.The first two are the horizontal gradient magnitude of the gravity field （GFhgm）,and tilt （TIhgm）.The third and fourth rely on locating maxima of the analytic signal （AS） and the 3D local wavenumber （LW）.The fifth is normalized standard deviation （NSTD） method.In this article,we evaluate the use of these five methods for mapping contacts and compare the results.First,synthetic vertically-sided models are used to quantify the offsets of maxima from the true contact location due to the source effects of finite source thickness,central depth,and width.Second,the effects of contact dip are discussed.Finally,a real data set is used to evaluate the ability of each method to produce maps of coherent contact trends in the presence of noise and gridding artifacts.