电力设备制造外包供方的评价与选择

利用过程方法对电力设备制造企业的外包运作过程和资源风险进行了分析．根据组织外包过程的绩效目标,在识别并分析外包供方运作资源的基础上,建立了电力设备制造外包供方评价指标体系．利用主成分分析法,构建了电力设备制造外包供方的评价模型．以河南省电力装备制造企业的外包过程为对象进行了实证研究,证明了本方法的有效性,为组织规避外包...     

Kernel PCA与BP神经网络相结合的变压器故障诊断*

为了提高变压器故障诊断的准确率和抗干扰能力,提出一种基于核特征量的BP神经网络故障诊断模型。通过核主成分分析将故障样本从低维的特征空间非线性地映射到高维的核空间,提高了样本的可分性,然后以核特征量作为BP神经网络的输入特征量,建立变压器故障诊断模型。实验对比了结构相似、输入量不同的BP神经网络,结果表明采用核特征量的诊断模型具有更好的诊断效果和抗干扰能力。     

Variational PCA fusion for resolution Pan-sharpening very high imagery

The Pan-sharpening approach based on principle component analysis （PCA） is affected by severe spectral distortion. To address this problem, a new pan-sharpening model based on PCA and variational technique is proposed to construct the substitute image of the first principal component （PC1）. The energy functional consists of three terms. The first term injects PC1 with the geometric structure of the panchromatic （Pan） image. The second term preserves the spectral pattern of the multi-spectral image in the merged result. And the third term guarantees the smoothness of the functional optimization solution. The fusion result is given by the minimum of the energy functional, which is computed with the gradient descend flow. The experiments on QuickBird and IKONOS datasets validate the effectiveness of the proposed model. Compared with the state- of-the-art pan-sharpening approaches, this model exhibits a better trade-off between improving spatial quality and preserving spectral signature of the MS image.     

基于溶液图像时序特征的元素组分含量动态监测系统

针对稀土萃取过程中组分含量难以实时监测以及现有组分含量检测方法耗时、耗内存的现状,设计了一种基于溶液图像时序特征的元素组分含量动态监测系统。首先使用图像采集装置获取萃取槽体溶液的时序图像,考虑萃取液颜色特性和单一颜色空间的不全面性,采用主成分分析（PCA）方法在HSI和YUV融合的颜色空间提取图像的时序特征,并结合生产指标构造基于鲸鱼优化算法（WOA）的最小二乘支持向量机（LSSVM）分类器来对工况状态进行判断。然后当工况处于非最佳状态时,在HSV颜色空间对图像提取颜色直方图和颜色矩特征,并开发以溶液图像间的混合特征差值的线性加权值为相似度度量的图像检索系统,从而获取组分含量值。最后进行镨/钕萃取槽体混合溶液测试,结果表明该系统能够实现元素组分含量的动态监测。     

Anti-disturbance dynamic surface control scheme for a class of uncertain nonlinear systems with asymmetric dead-zone nonlinearity

This study proposes anti-disturbance dynamic surface control scheme for nonlinear strict-feedback systems subjected simultaneously to unknown asymmetric dead-zone nonlinearity, unmatched external disturbance and uncertain nonlinear dynamics. Radial basis function-neural network (RBF-NN) is invoked to approximate the uncertain dynamics of the system, and the dead-zone nonlinearity is represented as a time-varying system with a bounded disturbance. The nonlinear disturbance observer (NDO) is proposed to estimate the unmatched external disturbance which further will be used to compensate the effect of the disturbance. Then, by integrating RBF-NN, NDO and dynamic surface control (DSC) approaches, the proposed anti-disturbance control scheme is designed. Stability analysis of the closed-loop system shows that all signals of the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error can be made arbitrarily small by proper selection of the design parameters. In comparison with the existing methods, the proposed scheme deals with the unmatched external disturbance, uncertain dynamics and unknown asymmetric dead-zone nonlinearity, simultaneously; it avoids the "explosion of complexity" problem and develops the simple control law without singularity concern. Furthermore, some imposed assumptions to the dead-zone input and disturbances are relaxed. Simulation and comparison results verify the effectiveness of the proposed approach.     

Mechanical analysis of roof stability under nonlinear compaction of solid backfill body

Based on the compaction characteristic test and the nonlinear compaction deformation characteristics of backfill material, this paper applies the theory of nonlinear elastic foundation of thin plate to establish a mechanical model of backfill body and roof in solid dense backfill coal mining. This study critically analyses the deflection equation of the roof by the energy method, derives the conditions of roof breakage and combined with concrete engineering practice analyses, determines roof movement regularity and stability in solid dense backfill mining. Analysis of the engineering practice of the 13,120 backfill panel of Pingmei 12# mine shows the theoretical maximum of roof convergence in backfill mining to be415 mm which is in significant agreement with the measured value. During the advancing process of solid backfill mining at the panel, the maximum tensile stress on the roof is less than its tensile strength which does not satisfy the conditions for roof breakage. Drilling results on the roof and ground pressure monitoring show that the integrity of roof is strong, which is consistent with the theoretical calculations described in this study. The results presented in the study provide a basis for further investigation into strata movement theory in solid dense backfill mining.     

基于动态优化PCA人脸识别算法的实现

提出一种人脸识别动态优化PCA算法。采用ORL人脸数据库,对数据库中图像进行放缩归一化操作并按升序或降序排列。然后,将数据库分为最大值类、中值类、最小值类三个部分,求其各类平均值,特征值个数选取9和10,实现人脸识别和重建。随机采样人脸图像,采用DCT算法将其转换到频域进行分析,通过比较整个数据库平均脸与三类中各自平均脸,算法运行后,特征值个数可以实现自动优化。实验结果显示,该算法在一定程度上可用来对传统PCA算法部分关键参数进行优化。     

高精度电液位置伺服系统的设计

将小流量的伺服阀用于低速液压缸的定位控制和跟踪控制，建立了该液压伺服系统的非线性数学模型，实验表明其随动性优于传统的线性控制器，抗干扰能力强。