基于QFD电动汽车技术特性重要度的确定方法研究

技术重要度是开展电动汽车综合设计优化的目标函数,提出了一种基于QFD的电动汽车关键技术重要度的综合确定方法。方法分析了电动汽车顾客需求和电动汽车技术指标,基于质量屋建立顾客需求重要度与技术特性重要度耦合模型,应用粗糙数进行顾客需求重要度排序,根据电动汽车市场竞争性评估对其进行修正;应用灰色关联法确定顾客需求与技术特性之间的相关关系,分析电动汽车技术特性自相关关系建立相应的修正决策系统。基于该方法,以本研究院研究车型与市场同类车型进行实例分析,证明了方法的有效性和可行性。     

一种基于Arnold变换和RSA的图像加密算法

提出一种Arnold变换和RSA相结合的图像加密算法。利用Arnold变换对图像的像素位置进行链式迭代置乱。在对置乱后的图像像素值进行替代和扩散的过程中,采用基于大素数分解的RSA算法,构造一个位置置乱和灰度变换相结合的加密算法。实验仿真结果表明该算法支持变长密钥,具有敏感性强、去相关能力强及抵御统计和已知明文攻击等优点,能够取得很好的加密效果。     

引入零视差缓冲的DIBR改良方法

针对图像部分像素深度值失真,导致图像变形后物体边缘失真的问题,提出了一种引入“零视差缓冲”的方法。首先选取四幅具有不同复杂程度场景的图像,引入零视差缓冲对图像进行变形,其次采用传统图像质量评价体系（结构相似度SSIM和模糊系数K）对得到的图像进行质量评价,最后对比传统DIBR方法和引入零视差缓冲方法得到的视点图中物体边缘的表现。实验结果表明,该方法对于变形图像的SSIM平均提高了4.66%, K平均下降了1.73%。提高了视点图中物体边缘的质量,提高了3D图像的整体质量。     

基于田口试验的高Nb-TiAl合金小孔电火花加工试验研究

采用D703F高速电火花小孔加工机床在高Nb-TiAl合金(Ti-44Al-8.5Nb-0.2Mo-0.2B)板材上加工直径为1mm小孔,运用田口试验法研究电火花加工参数(电流、脉宽和冲液压力)对加工速度和加工质量的影响,并对试验结果进行方差分析和灰关联度分析。结果表明:电流为10 A、脉宽为32μs、冲液压力为3 MPa时加工速度和孔径精度较高,对实现高Nb-TiAl合金的高效率、精密加工具有一定的实用价值。     

一种应用于图像去噪的广义回归神经网络模型设计研究

为了更好地去除图像中的椒盐噪声、保留图像细节信息,提出了一种广义回归神经网络模型,适用于图像去噪。首先,对传统广义回归神经网络的原理进行了分析,并对采用的广义回归神经网络进行具体设计。然后对广义回归神经网络中的唯一可调参数（平滑因子）进行了优化。采用归一化均方误差和峰值信噪比指标进行具体算法性能分析。仿真试验结果显示：相比径向基神经网络和传统广义回归神经网络,提出算法的去噪能力更强,具有较高的峰值信噪比和较低的归一化均方误差,验证了提出算法的有效性和先进性。     

A Novel Ni/YSZ Anode Image Segmentation Method for Solid Oxide Fuel Cell Electrodes Microstructure

For the three‐phase identification of solid oxide cuel cell (SOFC) electrode, this paper presents a novel segmentation method based on gaussian mixture model (GMM) for YSZ/Ni anode optical microscopy (OM) images. A coarseness‐entropy adaptive factor is defined to incorporate the spatial information based on markov random field (MRF) into GMM. Furthermore, the proposed method can obtain the trade‐off between robustness to noise and effectiveness of preserving the details. Experimental results show that the proposed method outperforms the compared method on three‐phase microstructure identification. It can provide reliable foundation for the quantification of SOFC microstructure parameters.     

基于RPCA的SAR图像纹理特征去噪

合成孔径雷达(SAR)图像具有丰富的纹理信息,这些纹理信息能反映地物空间结构关系。当前纹理特征被广泛应用于SAR图像分类和SAR图像分割中。受成像因素影响,直接采用从SAR图像中提取的纹理特征效果不够好。为避免传统先滤波再提取纹理特征的方法对纹理、边缘信息造成损失,提出了一种先提取SAR图像纹理特征,再利用Robust PCA方法对纹理特征去噪的新方法,最后采用Kmeans聚类方法检验RPCA处理后的纹理特征表达效果。实验结果表明该方法能将聚类正确率从82%提高到84%。     

Multichannel image contrast enhancement based on linguistic rule-based intensificators

This study follows the direct approach to image contrast enhancement, which changes the image contrast at each its pixel and is more effective than the indirect approach that deals with image histograms. However, there are only few studies following the direct approach because, by its nature, it is very complex. Additionally, it is difficult to develop an effective method since it is required to keep a balance in maintaining local and global image features while changing the contrast at each individual pixel. Moreover, raw images obtained from many sources randomly influenced by many external factors can be considered as fuzzy uncertain data. In this context, we propose a novel method to apply and immediately handle expert fuzzy linguistic knowledge of image contrast enhancement to simulate human capability in using natural language. The formalism developed in the study is based on hedge algebras considered as a theory, which can immediately handle linguistic words of variables. This allows the proposed method to produce an image contrast intensificator from a given expert linguistic rule base. A technique to preserve global as well as local image features is proposed based on a fuzzy clustering method, which is applied for the first time in this field to reveal region image features of raw images. The projections of the obtained clusters on each channel are suitably aggregated to produce a new channel image considered as input of the pixelwise defined operators proposed in this study. Many experiments are performed to demonstrate the effect of the proposed method versus the counterparts considered.     

Controllable Image‐Based Transfer of Flow Phenomena

Modelling flow phenomena and their related weathering effects is often cumbersome due their dependence on the environment, materials and geometric properties of objects in the scene. Example‐based modelling provides many advantages for reproducing real textures, but little effort has been devoted to reproducing and transferring complex phenomena. In order to produce realistic flow effects, it is possible to take advantage of the widespread availability of flow images on the Internet, which can be used to gather key information about the flow. In this paper, we present a technique that allows the transfer of flow phenomena between photographs, adapting the flow to the target image and giving the user flexibility and control through specifically tailored parameters. This is done through two types of control curves: a fitted theoretical curve to control the mass of deposited material, and an extended colour map for properly adapting to the target appearance. In addition, our method filters and warps the input flow in order to account for the geometric details of the target surface. This leads to a fast and intuitive approach to easily transfer phenomena between images, providing a set of simple and intuitive parameters to control the process.