High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Effect of sintering temperature on solidification and migration of non-volatile and volatile heavy metals in glass-ceramic

Using tailings as material to prepare glass-ceramic is an excellent way to achieve the resource utilization of solid waste. However, at present, researches on the solidification and migration of heavy metals are limited. Therefore, in this study, ten groups of samples were prepared by controlling sintering temperatures. The solidification, migration, and leaching behavior of non-volatile and volatile heavy metals were studied. The research showed that, with the increase of temperature, the properties of the samples were improved. Fe participated in the phase transformation and evolved into insoluble iron pyroxenes solid solution, while Pb was homogeneously distributed in the glass matrix of glass-ceramics. The leaching concentrations of Fe and Pb in the glass-ceramics were 0.055 mg/L ～0.087 mg/L and 0.074 mg/L ～0.140 mg/L, which were far below the threshold value. The results showed that heavy metals can be effectively solidified in glass-ceramics and have good environmental benefits.     

基于ABAQUS的显式动力学分析方法研究

显式动力学(The Explicit Dynamic)是针对隐式求解器的一个补充,其分析方法对于求解广泛、各类非线性结构力学问题是一个非常有效的工具,显式方法中的单个增量步取决于模型的最高固有频率,与持续时间、载荷类型无关。ABAQUS/Explicit主要用于碰撞、接触以及失效分析。探讨了ABAQUS显式动力学的基本理论、求解的问题,对显示动力学分析方法中的求解算法、稳定时间极限和能量平衡问题进行研究,给出了显示动力学分析的一般性分析方法。通过案例验证了该方法的可行性,应用该方法可有效解决实际工业生产中的碰撞问题、复杂的接触问题以及复杂的后屈曲问题,可为显式动力学分析方法应用于工程实践奠定理论与方法基础。     

Operational time-series data modeling via LSTM network integrating principal component analysis based on human experience

Today’s information technologies involve increasingly intelligent systems, which come at the cost of increasingly complex equipment. Modern monitoring systems collect multi-measuring-point and long-term data which make equipment health prediction a “big data” problem. It is difficult to extract information from such condition monitoring data to accurately estimate or predict health statuses. Deep learning is a powerful tool for big data processing that is widely utilized in image and speech recognition applications, and can also provide effective predictions in industrial processes. This paper proposes the Long Short-term Memory Integrating Principal Component Analysis based on Human Experience (HEPCA-LSTM), which uses operational time-series data for equipment health prognostics. Principal component analysis based on human experience is first conducted to extract condition parameters from the condition monitoring system. The long short-term memory (LSTM) framework is then constructed to predict the target status. Finally, a dynamic update of the prediction model with incoming data is performed at a certain interval to prevent any model misalignment caused by the drifting of relevant variables. The proposed model is validated on a practical case and found to outperform other prediction methods. It utilizes a powerful deep learning analysis method, the LSTM, to fully process big condition monitoring series data; it effectively extracts the features involved with human experience and takes dynamic updates into consideration.     

Decay Rate Kinetics of Ozone Gas in Rice Grains

The present study was carried out to evaluate the effects of ozone on rice grains for the following three conditions: saturation time, decay rate, and half-life of ozone. Experiments were performed in different bed thicknesses (5 and 10 cm) and moisture content (11.4 and 14.2% wb) at atmospheric conditions. The lowest saturation time of ozone was 119 min, with the concentration of 516 ppm for rice grains ozonated at 5-cm bed thickness with 11.4% (wb) moisture content. The decay rate kinetics of ozone obtained were consistent with a first-order model. Regarding the half-life of ozone, the lowest value obtained was 6.78 min for rice grains ozonated at 10-cm bed thickness with 14.2% (wb) moisture content.     

Estimation of power density in IMPATT using different materials

ABSTRACT

The RF output power dissipated per unit area is calculated using Runge-Kutta method for the high-moderate-moderate-high (n⁺-n-p-p⁺) doping profile of double drift region (DDR)-based impact avalanche transit time (IMPATT) diode by taking different substrate at Ka band. Those substrates are silicon, gallium arsenide, germanium, wurtzite gallium nitride, indium phosphide and 4H-silicon carbide. A comparative study regarding power dissipation ability by the IMPATT using different material is being presented thereby modelling the DDR IMPATT diode in a one-dimensional structure. The IMPATT based on 4H-SiC element has highest power density in the order of 10¹⁰ Wm^?2 and the Si-based counterpart has lowest power density of order 10⁶ Wm^?2 throughout the Ka band. So, 4H-SiC-based IMPATT should be preferable over others for the power density preference based application. This result will be helpful to estimate the power density of the IMPATT for any doping profile and to select the proper element for the optimum design of the IMPATT as far as power density is concerned in the Ka band. Also, we have focused on variation of power density with different junction temperatures and modelled the heat sink with analysis of thermal resistances.     

全球邮政、快递业应用RFID技术的研究

本文在掌握大量案例的基础上,分析了全球邮政、快递行业应用RFID技术的发展空间、应用现状,提出了我国邮政企业实施RFID在技术层面上的若干问题并提供了建议。     

Type inference in stack based languages

We consider a language of operations which pass parameters by means of a stack. An algebra over the set of type signatures is introduced, which allows the type signature of a program to be obtained from the type signatures of its constituent operations.Although the theories apply in principle to any stack based language, they have been evolved with particular regard to the proposed ANSI Standard Forth language, which is currently implemented in a type free manner. We hope this work will stimulate an interest in Forth amongst those applying algebraic techniques in software engineering, and we hope to lay the theoretical foundations for implementing practical type checkers to support Forth.     

Evaluation of Monkman-Grant parameters for type 316LN and modified 9Cr-Mo stainless steels

The Monkman-Grant (M-G) and its modified parameters were evaluated for type 316LN and modified 9Cr-Mo stainless steels prepared with minor element variations. Several sets of creep data for the two alloy systems were obtained by constant-load creep tests in 550-650°C temperature range. The M-G parameters,m, m’,C, andC’ were proposed and discussed for the two alloy systems. Them value of the M-G relation was 0.90 in type 316LN steel and 0.84 in modified 9Cr-Mo steel. Them’, value of the modified relation was 0.94 in type 316LN steel and 0.89 in 9Cr-Mo steel. Although creep fracture modes and creep properties between type 316LN and modified 9Cr-Mo steels showed a basic difference, the M-G and its modified relations demonstrated linearity quite well. Them’ of modified relation almost overlapped regardless of the creep testing conditions and chemical variations in the two alloy systems, and the parameterm’ was closer to unity than that of the M-G relation.     

双时基频率校准电路

提供精确的时间基准是精密仪器和高精度设备计时和工作的关键技术之一。文中采用两套晶振电路，通过分频产生高频和低频两个频率信号，采用编码的方法对两个频率信号在每一个时钟周期内进行动态校核，只有两个晶振的频率在允许的精度范围内，或同时增大（缩小）相同的倍数，校核后频率信号才是正确的，且能给系统提供精确的时间基准。该方法能有效防止系统的时钟周期因意外的原因伸长或缩短。整个电路可以作为精密仪器或高精度设备的一个模块电路。