Rapid screening of DON contamination in whole wheat meals by Vis/NIR spectroscopy and computer vision coupling technology

This work intends to develop an online experimental system for screening of deoxynivalenol (DON) contamination in whole wheat meals by visible/near-infrared (Vis/NIR) spectroscopy and computer vision coupling technology. Spectral and image information of samples with various DON levels was collected at speed of 0.15 m s⁻¹ on a conveyor belt. The two-type data were then integrated and subjected to chemometric analysis. Discriminant analysis showed that samples could be classified by setting 1000 μg kg⁻¹ as the cut-off value. The best correct classified rate obtained in prediction was 93.55% based on fusion of spectral and image features, with reduced prediction uncertainty as compared to single feature. However, quantification of DON by quantitative analysis was not successful due to poor model performance. These results indicate that, although not accurate enough to provide conclusive result, this coupling technology could be adopted for rapid screening of DON contamination in cereals and feeds during processing.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Fabrication of direct Z-scheme FeIn2S4/Bi2WO6 hierarchical heterostructures with enhanced photocatalytic activity for tetracycline hydrochloride photodagradation

A series of direct Z-scheme FeIn₂S₄/Bi₂WO₆ hierarchical heterostructures with intimate interface contacts were synthesized by in-situ growth route and characterized by systematical analyses. All as-prepared FeIn₂S₄/Bi₂WO₆ nanocomposites showed significantly enhanced photocatalytic activity towards photodegradation for the removal of tetracycline hydrochloride (TCH) in comparison with individual FeIn₂S₄ and Bi₂WO₆. Meanwhile, the highest photocatalytic degradation activity can be achieved by modulating adding amount of FeIn₂S₄ in FeIn₂S₄/Bi₂WO₆ nanocomposites and the optimized component ratio of FeIn₂S₄ to Bi₂WO₆ is determined to be 10 wt%. The enhanced photocatalytic activity could be ascribed to efficient separation between photogenerated holes and electrons based on the construction of direct Z-scheme system. The high photocatalytic stability of resultant 10 wt% FeIn₂S₄/Bi₂WO₆ nanocomposites was revealed through six successive recycling reactions. The main intermediate generated during TCH photodegradation was explored by HPLC-MS. Besides, the direct Z-scheme photocatalytic mechanism was confirmed by band position analysis, electron spin resonance (ESR) and active species capture experiment.     

Improved Input and State Estimation for Linear Stochastic Systems with Direct Feedthrough

This paper is concerned with the problem of joint input and state estimation for linear stochastic systems with direct feedthrough. Based on the fact that each unknown input between any two time steps is always bounded, a novel improved algorithm is proposed. Compared with existing results, this algorithm can effectively enhance estimation accuracy. Moreover, the stability of the algorithm is also discussed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.     

基于状态空间法的电动机故障诊断和识别

电动机的初期故障信号一般较弱,不易辨别,而状态空间法在小信号的处理中灵敏度很高。为达到对电动机故障的诊断和识别,试图把状态空间法应用到对电动机的故障诊断中,先通过推导,从数学理论层面分析了状态空间法对于电动机故障信号的可辨别性,再使用Matlab软件搭建状态空间的辨别模型,把实验台测试的三组数据导入到模型中进行测试。测试的结果有力地证明了此方法的可行性,并能克服快速傅里叶变换(FFT)中数据采集量较大、分辨率不高的缺点。     

A distributed energy system integrating SOFC-MGT with mid-and-low temperature solar thermochemical hydrogen fuel production

Solar thermochemical hydrogen production with energy level upgraded from solar thermal to chemical energy shows great potential. By integrating mid-and-low temperature solar thermochemistry and solid oxide fuel cells, in this paper, a new distributed energy system combining power, cooling, and heating is proposed and analyzed from thermodynamic, energy and exergy viewpoints. Different from the high temperature solar thermochemistry (above 1073.15 K), the mid-and-low temperature solar thermochemistry utilizes concentrated solar thermal (473.15–573.15 K) to drive methanol decomposition reaction, reducing irreversible heat collection loss. The produced hydrogen-rich fuel is converted into power through solid oxide fuel cells and micro gas turbines successively, realizing the cascaded utilization of fuel and solar energy. Numerical simulation is conducted to investigate the system thermodynamic performances under design and off-design conditions. Promising results reveal that solar-to-hydrogen and net solar-to-electricity efficiencies reach 66.26% and 40.93%, respectively. With the solar thermochemical conversion and hydrogen-rich fuel cascade utilization, the system exergy and overall energy efficiencies reach 59.76% and 80.74%, respectively. This research may provide a pathway for efficient hydrogen-rich fuel production and power generation.     

Structure, properties, and thermal stability of nanocrystallite Fe-Ti-N soft magnetic films

We deposited Fe-Ti-N magnetic films with a high sputtering power of 7 W/cm/sup 2/. When the composition of the films was in the range of Fe-Ti(3.9 at.%)-N(8.8 at.%) to Fe-Ti(3.3 at.%)-N(13.5 at.%), the films were composed of /spl alpha/' and Ti/sub 2/N precipitates. With the addition of nitrogen, 4/spl pi/M/sub s/ became higher than that of pure iron, reaching a maximum of 23.8 kG. At the same time, H/sub c/ was reduced to a minimum of 1.12 Oe. The best films can meet the needs of the recording head in dual-element giant magnetoresistive/inductive heads, yielding high storage density (10 Gb/in/sup 2/). The incorporation of N in /spl alpha/-Fe brought about the /spl alpha/' phase with its higher saturation magnetization. Ti additions inhibited the equilibrium decomposition /spl alpha/'/spl rarr//spl alpha/+/spl gamma/'. Because H/sub C//sup D//spl prop/D/sup 6/, where D is average grain diameter, grain size control is very important. The nitrogen induces severe distortion of the /spl alpha/' lattice, which can cause the grains to break into pieces and reduce the grain size. High sputtering power also led to the formation of fine grains, with diameter in the order of 14 nm. Probably Ti/sub 2/N is preferentially precipitated on the grain boundary, pinning the grain boundary and stabilizing the grain size during high-temperature heat treatment. The temperature limit for stability of the structure and its associated low coercivity was not less than 520/spl deg/C.