基于遗传算法的SiC MOSFET导通电阻模型

提出了一种简洁、新颖的SiC MOSFET器件导通电阻模型,该模型采用遗传算法对其不同温度下的导通电阻进行准确描述。相比于传统的导通电阻建模方案,采用进化算法可以准确地得到MOSFET导通电阻与结温之间的关系。并探究了不同种群规模、交叉率和变异率对算法的影响。为了验证模型的准确性,采用一款自主封装的1 200 V/90 A SiC MOSFET模块去验证模型的静态特性,并与传统导通电阻建模方案进行对比,其最大误差为4.1%。     

基于正序电压变化量的故障电压暂降源定位算法

随着越来越多敏感负荷接入电网,由电压暂降问题直接及间接带来的经济损失日趋严重。在各类电压暂降中,故障引发的电压暂降占比最大,对其进行准确定位是高效治理电网故障的必要前提。文中针对故障型暂降源提出一种基于正序电压变化量的定位方法,基于发生故障时各监测点的正序电压分布特性,建立监测点信息库和各支路故障距离定位模型;然后基于马氏距离与Pearson相关系数定义相似度指标,利用信息库匹配的方法对故障所在支路进行初选;最后采用遗传算法对最优故障距离目标函数进行寻优,定位故障源。利用IEEE 14节点仿真系统对所提方法的有效性与准确性进行了验证。     

Probabilistic analysis of ultimate seismic bearing capacity of strip foundations

This paper presents a reliability analysis of the pseudo-static seismic bearing capacity of a strip foundation using the limit equilibrium theory. The first-order reliability method (FORM) is employed to calculate the reliability index. The response surface methodology (RSM) is used to assess the Hasofer–Lind reliability index and then it is optimized using a genetic algorithm (GA). The random variables used are the soil shear strength parameters and the seismic coefficients (k_h and k_v). Two assumptions (normal and non-normal distribution) are used for the random variables. The assumption of uncorrelated variables was found to be conservative in comparison to that of negatively correlated soil shear strength parameters. The assumption of non-normal distribution for the random variables can induce a negative effect on the reliability index of the practical range of the seismic bearing capacity.     

自身形状优化原则:薄壁型材截面承载力的优化

为实现经济效益,已对大批量生产的钢结构产品的优化进行了广泛研究。旨在不削弱结构构件的强度和实用性的条件下,尽量减少材料的用量。当前研究主要集中于传统截面形状主要尺寸的优化,而并未考虑采用新的最佳截面。介绍了一种新的优化方法,利用遗传算法(GA)的进化和自适应特点,使截面的自身形状达到最佳效果。采用该方法对薄壁型材的截面承载力进行优化,验证了该方法的可行性和精确性。特别地,通过简单参数对截面的优化方法中,这种分析方法是众所周知的,即双轴对称闭口截面的优化。结果表明,经过几代演化,截面自身形状产生出精确的最优解。给出了影响收敛的因素。该方法可推广至冷弯型钢开口截面柱的优化。     

Genetic algorithm optimization in building portfolio management

A significant proportion of building investment expenditure goes to replacement expenditure for organizations owning a large building stock or portfolio. Over the years, researchers have attempted to develop asset replacement models to aid decision-making in building portfolio management, based upon' a statistical or an heuristic approach. This study attempts to use genetic algorithms to develop models for forecasting long term asset replacement strategies, aiming at smoothing fluctuations of expenditure and resource requirements, and most importantly minimizing the total maintenance and replacement costs. Scenarios are presented to demonstrate how these can be achieved. Further refinement for practical application of the models is also presented.     

Improved state space model predictive fault-tolerant control for injection molding batch processes with partial actuator faults using GA optimization

A novel model predictive fault-tolerant control (MPFTC) strategy adopting genetic algorithm (GA) is proposed for batch processes under the case of disturbances and partial actuator faults. Based on the extended state space model in which the tracking error is contained, there are more degrees of freedom provided for the controller design and better control performance is obtained. In order to enhance the control performance further, the GA is introduced to optimize the relevant weighting matrices in the cost function. The effectiveness of the proposed MPFTC approach is tested on the injection velocity regulation of the injection molding process.     

基于量子遗传算法的军用道路纵断面优化设计

为实现军用道路纵断面变坡点里程和设计标高的同时优化,在分析传统纵断面优化设计方法的基础上,提出了一种基于量子遗传算法的纵断面优化设计方法,以工程量大小作为评价函数,建立了优化设计数学模型,并给出了详细的求解步骤,最后进行了实例仿真。实例仿真结果表明:与传统的遗传算法相比,本算法模型具有更好的全局寻优能力,能更快速地给出军用道路纵断面设计的初始优化方案,若在此基础上进行人工调整,优化效果更为明显。     

遗传算法在故障诊断中的应用

通过遗传算法的全局寻优能力优化BP神经网络的初始参数,使其收敛速度快、并能收敛至全局最小点,再利用BP网络来进行精确求解;实验表明:将二者有机结合后能对各种故障进行可靠的分类,有效地提高了故障诊断的效率和准确度。     

非战争军事行动装备保障资源运输方式选择模型

装备保障资源运输是非战争军事行动装备保障的重要环节,采用神经网络法选择保障资源运输方式,用遗传算法优化保障资源运输路径,并结合实际的交通网络图给出了运输方式选择的案例分析,表明该模型的可行性。     

重型AT锁止阀的流量特性分析与优化

为了提高锁止阀开启中液动力的计算效率,通过动网格技术在流体动力学软件Fluent中模拟锁止阀的阀芯开启过程,在对阀口过流面积进行数值计算的基础上,分析其流量及流量系数随阀芯位移的变化情况。使用BP神经网络对随机抽样法获得的样本数据进行训练和预测,并对预测的结果进行准确性评估。最后,以BP神经网络预测的数学模型为基础,使用遗传算法对锁止阀节流槽参数进行优化。结果表明：优化后的锁止阀开启过程中流量-开度特性更加稳定,有利于提高锁止阀的工作性能。