浅谈恒温槽技术性能的测试方法

恒温槽作为热工类计量器具检定工作中不可缺少的主要配套设备,为了保证其技术性能的可靠性,需定期对恒温槽的技术性能进行测试.恒温槽技术性能的重要指标包括温度波动度和温场均匀性,它们会直接影响到检定结果的准确性.本文就是以制冷恒温槽为具体实例,介绍以二等铂电阻温度计为测试标准器,在0℃的时候,制冷恒温槽的温度波动度和温场均匀性,来叙述恒温槽技术性能的测试方法.     

基于等效瞬时电感判别变压器励磁涌流的新算法

基于变压器铁心磁导率在励磁涌流与内部故障时变化情况的不同,应用瞬时励磁电感和等效瞬时电感的概念,可有效判别变压器励磁涌流.但是,现有的等效瞬时电感计算方法存在较大的误差,对准确判别变压器励磁涌流构成了威胁.为此,提出了改进型的等效瞬时电感计算方法,有效考虑了等效电阻的影响,极大地改善了计算精度.以此为基础,给出了2种判别励磁涌流方案,即时域法和频域法.通过动模实验,对改进型算法和现有的近似算法进行了对比研究.结果表明,应用改进型算法求取的等效瞬时电感更为准确,使时域法和频域法的判别精度得到了极大的改善,有力证实了文中所提出的新算法正确、可行、有效.     

一种基于傅里叶描述子的轴心轨迹自动识别方法

傅里叶描述子是分析和识别物体形状的重要方法之一。文中详细讨论了傅里叶描述子的原理、不变性和实际应用方法;运用人工神经网络分析方法,以傅里叶描述子作为特征向量,对汽轮发电机组轴心轨迹的自动识别进行了探讨;并对3类典型的轴心轨迹的自动识别进行了仿真试验,结果表明该方法是有效、可行的。     

超宽带通信技术及其在军事通信方面的应用

本文给出了超宽带(Ultra-wide Bandwidth:UWB)系统的信号表示形式,分析了其具体含义、信号特点及UWB通信系统的性能,结合当前军事通信的特点及发展趋势,介绍了超宽带脉冲通信在军事通信领域的应用现状及前景。     

A novel image segmentation model with an edge weighting function

A variational model for image segmentation consists of a data term and a regularization term. Usually, the data term is chosen as squared $\text{ L }_{2}$ norm, and the regularization term is determined by the prior assumption. In this paper, we present a novel model in the framework of MAP (maximum a posteriori). A new iteratively reweighted $\text{ L }_{2}$ norm is used in the data term, which shares the advantages of $\text{ L }_{2}$ and mixed $\text{ L }_{21}$ norm. An edge weighting function is addressed in the regularization term, which enforces the ability to reduce the outlier effects and preserve edges. An improved region-based graph cuts algorithm is proposed to solve this model efficiently. Numerical experiments show our method can get better segmentation results, especially in terms of removing outliers and preserving edges.     

Reversible data hiding based on hybrid prediction and interleaving histogram modification with single seed pixel recovery

This paper proposes a reversible data hiding scheme for natural images. A hybrid prediction mechanism is utilized in order to produce prediction errors as many as possible. The cover image excluding a seed pixel is partitioned into four non-overlapping segments, and four predictors are tailored for each of them. As a result, most prediction errors concentrate around zero in prediction error histogram. Besides, an interleaving histogram modification mechanism is presented such that the capacity is enhanced and easier to be finely tuned in contrast to some previous approaches. Third, a single seed pixel recovery strategy is introduced. Experimental results show the effectiveness of the proposed method.     

High-power Mode Converter of Overmoded Bent Circular Waveguide

Based on the mode coupling theory, a TE₀₁—TM₁₁ mode converter was designed and optimal results were obtained. In this paper, bandwidth of mode converter with axis exponential structure is the largest, and mode converter with axis sinusoidal structure is the most compact in the case of the center frequency is 28GHz and the waveguide radius is 16mm. If the bending angle between input port and output port of mode converter was demanded for 90°, mode converter with axis parabola structure had the characteristics of compact structure, higher mode purity and larger relative bandwidth. Meanwhile, we found that the converter could be also used as TE₁₁ mode transition with transmission efficiency above 99%. But due to bending angle of this structure was restricted, its center frequency and waveguide radius had the obvious corresponding relation.     

A code-pattern-driven digital background calibration technique for SAR ADCs

The article presents the buck converter for the application on headlights of vehicle with chip-level design. The LED components are used as for lighting source, which near/far lights are controlled with high-current switching circuit in the chip. The level-shift circuit and its current driver is proposed to control the input of high-voltage power MOS. The bypass method is presented to reduce the transient time as load current changes suddenly. The input voltage widely ranges from 8 to 21 V while keeping a stable output voltage with 6 V. The chip current can output from 20 to 1500 mA with excellent regulation. This chip had been implemented with TSMC0.25 µm HV- process, and the size of the circuit layout is about 8.6 mm², where includes power switch and far/near lighting switches. Measurements show that peak efficiency can achieve 86.3%. The power regulation is excellent, where the load regulation is only 0.3%, and the line regulation is only 0.5%.

     

Enhanced Thermal Stability and Efficiency of Polymer Bulk‐Heterojunction Solar Cells by Low‐Temperature Drying of the Active Layer

This study addresses two key issues, stability and efficiency, of polymer solar cells based on blended poly(3‐hexylthiophene) (P3HT) and [6,6]‐phenyl‐C61‐butyric acid methyl ester (PCBM) by demonstrating a film‐forming process that involves low‐temperature drying (?5 °C) and subsequent annealing of the active layer. The low‐temperature process achieves 4.70% power conversion efficiency (PCE) and ～1250 h storage half‐life at 65 °C, which are significant improvements over the 3.39% PCE and ～143 h half‐life of the regular room‐temperature process. The improvements are attributed to the enhanced nucleation of P3HT crystallites as well as the minimized separation of the P3HT and PCBM phases at the low drying temperature, which upon post‐drying annealing results in a morphology consisting of small PCBM‐rich domains interspersed within a densely interconnected P3HT crystal network. This morphology provides ample bulk‐heterojunction area for charge generation while allowing for facile charge transport; moreover, the P3HT crystal network serves as an immobile frame at heating temperatures less than the melting point (T_m) of P3HT, thus preventing PCBM/P3HT phase separation and the corresponding device degradation.     

Asymmetric Semi‐Supervised Boosting Scheme for Interactive Image Retrieval

Support vector machine (SVM) active learning plays a key role in the interactive content‐based image retrieval (CBIR) community. However, the regular SVM active learning is challenged by what we call “the small example problem” and “the asymmetric distribution problem.” This paper attempts to integrate the merits of semi‐supervised learning, ensemble learning, and active learning into the interactive CBIR. Concretely, unlabeled images are exploited to facilitate boosting by helping augment the diversity among base SVM classifiers, and then the learned ensemble model is used to identify the most informative images for active learning. In particular, a bias‐weighting mechanism is developed to guide the ensemble model to pay more attention on positive images than negative images. Experiments on 5000 Corel images show that the proposed method yields better retrieval performance by an amount of 0.16 in mean average precision compared to regular SVM active learning, which is more effective than some existing improved variants of SVM active learning.