Application of differential evolution for cascaded multilevel VSI with harmonics elimination PWM switching

Harmonic elimination pulse width modulation (HEPWM) method has been widely applied to multilevel voltage source inverter (MVSI) to remove low frequency harmonics from its output voltage. However, the computation of the HEPWM switching angles for MVSI is very challenging due to several constraints, namely angle sequencing, very tight angular spacing and the numerous possibilities of angles distribution ratio. Realizing the potential of Differential Evolution (DE) to handle complex problems, this work proposes its application to solve the HEPWM problem for cascaded MVSI. Its emphasis is on improving the availability of HEPWM for higher output voltage by extending the maximum range of modulation index (M). It also removes the discontinuities in the switching angles and reduces the number of distribution ratio required to obtain the required solution. Compared to the most advanced (similar) work, i.e., 7-level MVSI with seventeen switching angles, DE covers a wider range of M; the maximum achievable M is 2.80. Furthermore, it exhibits very low second order distortion factor (DF₂): for the worst case, the value of DF₂ is 0.0014%. To verify the viability of the proposed algorithm, simulation is carried out and hardware prototype is constructed. Both results show very good agreement with the theoretical prediction.     

Survivability of systems under multiple factor impact

The paper considers vulnerable multi-state series-parallel systems operating under influence of external impacts. Both the external impacts and internal failures affect system survivability, which is determined as the probability of meeting a given demand. The external impacts are characterized by several destructive factors affecting the system or its parts simultaneously.In order to increase the system's survivability a multilevel protection against the destructive factors can be applied to its subsystems. In such systems, the protected subsystems can be destroyed only if all of the levels of their protection are destroyed.The paper presents an algorithm for evaluating the survivability of series-parallel systems with arbitrary configuration of multilevel protection against multiple destructive factor impacts. The algorithm is based on a composition of Boolean and the Universal Generating Function techniques.Illustrative examples are presented.     

用基函数神经网络实现多阈值图象分割

本文介绍了一种用基函数神经网络实现多阈值图象分割的新方法。它从函数逼近的角度研究基于灰度直方图的多阈值分割问题，提出了一种模糊反向传播学习算法，采用该算法的高斯基函数网络能够准确检测直方图中包含的子区域和它们的分布函数，而且速度很快。实验表明本文的方法在实际图象分割中是有效的。     

级联型多电平逆变器中多载波PWM控制方法的改进

级联型多电平逆变器由于其模块化结构、便于生产高度、更换容易等特点，受到电力电子工程技术人员的广泛关注。本文通过对于级联型多电平逆变器几种典型的控制方法的分析比较，提出了一种改进多载波PWM控制方法。该方法通过改变载波的幅值，使级联逆变器的各个逆变单元开关规律相同，并使所有的开关器件的损耗一致，有利于逆变单元的统一设计和可靠运行。     

Efficient multilevel image segmentation through fuzzy entropy maximization and graph cut optimization

The fuzzy c-partition entropy has been widely adopted as a global optimization technique for finding the optimized thresholds for multilevel image segmentation. However, it involves expensive computation as the number of thresholds increases and often yields noisy segmentation results since spatial coherence is not enforced. In this paper, an iterative calculation scheme is presented for reducing redundant computations in entropy evaluation. The efficiency of threshold selection is further improved through utilizing the artificial bee colony algorithm as the optimization technique. Finally, instead of performing thresholding for each pixel independently, the presented algorithm oversegments the input image into small regions and uses the probabilities of fuzzy events to define the costs of different label assignments for each region. The final segmentation results is computed using graph cut, which produces smooth segmentation results. The experimental results demonstrate the presented iterative calculation scheme can greatly reduce the running time and keep it stable as the number of required thresholds increases. Quantitative evaluations over 20 classic images also show that the presented algorithm outperforms existing multilevel segmentation approaches.     

红外图像统计闭值分割方法

经典的统计阈值方法采用某种形式的类方差和作为阈值选择的准则,未考虑实际图像的特性,对目标和背景具有相似统计分布的图像的分割效果不甚理想。为此,利用阈值分割后两个类的标准偏差定义了一个新的阈值选择准则,并通过最小化此准则选择出最佳分割阈值。通过一系列实际图像上的实验结果表明,与现有的几种经典阈值分割方法相比,本方法分割图像的效果更好,尤其是对红外图像分割的效果更为明显。     

一种光斑图像的阈值分割和光斑中心坐标的计算方法

工业测量中经常需要从获取的光斑图像中提取光斑区域,计算光斑中心的坐标。针对光斑图像具有背景区域较暗且面积大,目标(光斑)区域较亮且面积小的特点,提出了一种适用于光斑图像的阈值分割方法,计算单个光斑中心坐标的重心法,以及采用连通区域标记和区域大小排序计算多个光斑中心坐标的方法。与其他阈值分割方法比较后的实验结果表明,所提出的方法可更好地分割光斑图像,与期望的人工选取的阈值最接近,计算得到的光斑中心坐标准确,且运行时间较短。     

基于改进粒子群算法的多阈值图像分割

提出了一种改进的粒子群算法,在初始化种群时采用相对基学习原理,以获得较优的初始候选解;在后期迭代过程中引入扩张模型,使粒子不易陷入局部极小值点,并将其用于多阈值图像分割。由最大熵阈值法得到所要优化的目标函数,用改进的粒子群算法对其进行优化,使其能够准确并迅速的得到分割的最佳阈值组合,并用该阈值组合对图像进行分割。将此分割结果与遗传算法的多阈值分割结果相比较可以看出,该算法可更为准确快速的实现图像分割。     

轨道交通站台安全门控制系统

轨道交通站台安全门作为公共安全防护设备,广泛应用在地铁、轻轨等轨道交通中的高架和地面站台上,具有节能、环保和安全功能。因此它在设计、制造、安装过程中需要充分考虑其自身的可靠性及乘客安全、行车安全。本文将对安全门系统的网络、控制及软件三方面进行详细论述。