一种具有快速瞬态响应、小交调影响和纹波的基于次级纹波控制的单电感多输出电路

提出了一种主回路采用峰值电流型控制、次回路采用纹波控制的新型单电感多输出降压型开关电源的设计。这种设计,使单电感多输出的控制回路变得简单,同时也使瞬态响应速度变快,交调影响和纹波变小。其开关频率为2 MHz,两路输出分别为1.8 V和1.2 V,两路负载范围为0～200 mA,实现了全负载可以正常工作。在考虑了各种寄生参数的后仿真条件下,一路负载为200 mA,一路负载从50 mA变化到200 mA,瞬态响应速度小于3μs,交调影响小于0.05 mV/mA,纹波小于30 mV,峰值效率可以达到91%。该芯片已经在CHART 0.18-μm CMOS工艺上设计实现,正在流片验证。

一种高效率LC谐振式移相全桥行波管高压电源的设计

设计了一种高效率LC谐振式移相全桥高压电源,从变换器拓扑、控制模式、功率器件、开关频率等多个方面进行分析,最终设计了一种高稳定度(≤0.5‰)、高电压(10kV)、小纹波(≤0.2‰)、高效率(不计输入整流滤波损耗满载效率达96.1%)、小型化(高压电源模块尺寸为200mm×200mm×50mm)、中等功率量级(满载输出450 W)的高压电源。

基于UC3844的24V/200W开关电源

为了解决矿下大功率用电设备的持续供电问题,并且提高其工作稳定性和安全可靠性,将双管正激拓扑结构的开关电源应用到实际设备中。开展了相关可行性分析,指出了线性稳压电源和传统开关电源的不足,提出了基于UC3844的200W双管正激开关电源设计方法;对电路基本工作原理进行了分析验证,并增加了过流保护、过压保护等功能;对电路各功能进行了恶劣条件下的反复试验,对相关数据、波形进行了多次分析比较。研究结果表明,该电源安全可靠、稳定性好、纹波小、效率高,且满足国家标准,达到了设计要求。

新型三开关(SEPIC)[1]电路的分析与设计

介绍了运用于开关电源芯片中的SEPIC拓扑结构。详细分析了传统SEPIC功率管在开态和关态情况下的工作原理。运用小纹波近似、电感的伏-秒数平衡和电容的电荷平衡等方法,计算了正常工作情况下输入输出电压关系,输出电流与两电感的关系。最后在理论分析的基础上介绍了改良型的SEPIC拓扑结构。在相同条件下仿真得出,改良型SEPIC比传统SEPIC效率要高。使用TSMC 0.50 UM CMOS工艺库进行了仿真。

基于电动汽车交错并联双向DC/DC变换器设计的研究

该文分析了交错并联双向DC/DC变换器在不同工作模式下的工作原理,并阐述了为电动汽车供电电源设置双向DC/DC变换器的必要性。从小纹波角度推导了双向DC/DC变换器的主要参数,采用电流控制的方法对选择的参数进行修正。试验结果表明,采用该文所提出的计算方法得出的参数可以有效地对电动汽车双向DC/DC变换器进行控制,具有很好的实用价值。

Performance evaluation of wavelet scattering network in image texture classification in various color spaces

The optimized color space is searched by using the wavelet scattering network in the KTH_TIPS_COL color image database for image texture classification. The effect of choosing the color space on the classification accuracy is investigated by converting red green blue （RGB） color space to various other color spaces. The results show that the classification performance generally changes to a large degree when performing color texture classification in various color spaces, and the opponent RGB-based wavelet scattering network outperforms other color spaces-based wavelet scattering networks. Considering that color spaces can be changed into each other, therefore, when dealing with the problem of color texture classification, converting other color spaces to the opponent RGB color space is recommended before performing the wavelet scattering network.

Dissolution rate determination of alumina in molten cryolite-based aluminum electrolyte

Determination of dissolution rate of alumina is one of the classical problems in aluminum electrolysis. A novel method which can measure the dissolution rate of alumina was presented. Effect of factors on dissolution rate of alumina was studied intuitively and roundly using transparent quartz electrobath and image analysis techniques. Images about dissolution process of alumina were taken at an interval of fixed time from transparent quartz electrobath of double rooms. Gabor wavelet transforms were used for extracting and describing the texture features of each image. After subsampling several times, the dissolution rate of alumina was computed using these texture features in local neighborhood of samples. Regression equation of the dissolution rate of alumina was obtained using these dissolution rates. Experiments show that the regression equation of the dissolution rate of alumina is y=-0.000 5x^3＋0.024 0x^2-0.287 3x＋ 1.276 7 for Na3AIF6-AIF3-Al2O3-CaF2-LiF- MgF2 system at 920 ℃.

Multiwavelets domain singular value features for image texture classification

A new approach based on multiwavelets transformation and singular value decomposition (SVD) is proposed for the classification of image textures. Lower singular values are truncated based on its energy distribution to classify the textures in the presence of additive white Gaussian noise (AWGN). The proposed approach extracts features such as energy, entropy, local homogeneity and max-min ratio from the selected singular values of multiwavelets transformation coefficients of image textures. The classification was carried out using probabilistic neural network (PNN). Performance of the proposed approach was compared with conventional wavelet domain gray level co-occurrence matrix (GLCM) based features, discrete multiwavelets transformation energy based approach, and HMM based approach. Experimental results showed the superiority of the proposed algorithms when compared with existing algorithms.

Edge detection of magnetic tile cracks,based on wavelet

In order to extract the defect edge information on the magnetic tile surface with low contrast and textured background,an edge detection algorithm based on image weighted information entropy and wavelet modulus maxima is proposed.At first,a new Butterworth high pass filter(BHPF) with adaptive cutoff frequency is produced,because the clarity and complexity of the textured background are described by the weighted information entropy of the image gradient variance quantitatively,and the filter can change its parameters through matching the non-linear relationship between the information entropy and the cutoff frequency.And then,the best decomposition scale is obtained by the level determination function to prevent edge information from missing.At last,edge points are got by double threshold after obtaining the wavelet modulus maxima,and then the edge image is linked by the edge points to ensure the edge continuity and veracity.Experiment results indicate that the proposed algorithm outperforms the conventional Canny and Sobel algorithm,and the edge detection algorithm can also detect other defects,and lays the foundation for defecting auto- recognition.

Steam turbine rotor crack detection using sifting process of EMD and B-spline wavelet on the interval element model

A high-precision identification method for steam turbine rotor crack is presented. By providing me nrst three measured natural frequencies, contours for the specified natural frequency are plotted in the same coordi- nate, and the intersection of the three curves predicts the crack location and size. The cracked rotor system is mod- eled using B-spline wavelet on the interval （BSWI） finite element method, and a method based on empirical mode decomposition （EMD） and Laplace wavelet is implemented to improve the identification precision of the first three measured natural frequencies. Compared with the classical nondestructive testing, the presented method shows its effectiveness and reliability. It is feasible to apply this method to the online health monitoring for rotor structure.

AN ADAPTIVE DIGITAL IMAGE WATERMARK ALGORITHM BASED ON GRAY-SCALE MORPHOLOGY

An adaptive digital image watermark algorithm with strong robustness based on gray-scale morphology is proposed in this paper.The embedded strategies include:The algorithm seeks and extracts adaptively the image strong texture regions.The algorithm maps the image strong texture region to the wavelet tree structures, and embeds adaptively watermark into the wavelet coefficients corresponding to the image's strong texture regions.According to the visual masking features, the algorithm adjusts adaptively the watermark-embedding intensity.Experimental results show the algorithm is robust to compression, filtering, noise as well as strong shear attacks.The algorithm is blind watermark scheme.The image strong texture region extraction method based on morphology in this algorithm is simple and effective and adaptive to various images.