Synthetic Assessment of Power Transformer Condition Based on Matter-element Theory

Condition assessment on power transformer is an important approach to improve reliability of transformer and provide proper decision-making for condition-based maintenance. For long, static assessment method used in the past has already not adapted to the development of modem electricity transmission and distribution technology. So based on the deficiency of fuzzy synthetic assessment method, matter-element synthetic assessment method is introduced. The method can evaluate transformer condition not only in quality but also in quantity. Because each index weight can be given fairly and fast through improved analytic hierarchy process, which need not carry on consistency chec accuracy of assessment can be improved. Examples analysis has proved that assessment method of power transformer condition based on matter-element theory is rational and effective.     

Automatic Fingerprint Classification by GA-Based Neural Network

Fingerprint classification can provide an important indexing mechanism in a fingerprint database. An accurate and consistent classification can greatly reduce fingerprint matching time for large database. In the paper, by combining genetic algorithm and neural network is presented a fingerprint classification algorithm which is able to achieve an accurate classification. By inputting the global feature represented by directional image to three layer neural network trained by genetic algorithm, the fingerprints were classified into six categories: whorl, right loop, left loop, arch, double loop and undiscerning type successfully.     

Avoiding Obstacle Planning for Robots on Molecular Optimization Algorithm

Interest in DNA computing has increased overwhelmingly since Adleman successfully demonstrated its capability to solve Hamiltonian Path Problem. This article introduces the improving method in virtue of the biological thery of DNA technology, a new molecular algorithm is advanced. After a numerical simulation, the result shows that it avoids the prematurely and lower convergent speed of the classic genetic algorithm, and inherits global search capability, the validity and the speed of the genetic algorithm have been increased. The best result can be obtained in few iterative times. It is fit for solving path planning problem.     

基于混沌算法的工程车辆自动变速神经网络控制

为了克服BP神经网络收敛速度慢和易陷入局部极小点的不足，提出了一种基于混沌算法的工程车辆自动变速神经网络控制方法，并利用ZL50型装载机传动系统换挡控制试验的数据进行了验证性仿真试验。仿真结果表明：该方法对于车辆自动换挡智能控制是可行的，可以根据操作工况实现正确的变速挡位决策。     

泵站竖井进水流道数值模拟与装置特性试验

采用雷诺平均纳维—斯托克斯方程(RANS)和标准kε湍流模型,运用SIMPLEC算法,对椭圆型线前置竖井贯流进水流道内的流动进行了三维数值计算,揭示了竖井进水流道内流场、特征断面的速度分布及水力损失规律。对椭圆型线竖井进水流道与出水流道匹配组成的模型泵装置进行动力特性试验,得出了4种叶片角度下的泵装置特性曲线。研究结果表明:采用椭圆型线设计的竖井进水流道合理;大型低扬程泵站采用卧式竖井贯流结构,泵装置效率较高。     

联合收获机前进速度模糊控制系统多目标遗传优化

针对联合收获机前进速度模糊控制系统参数设计具有主观性,导致作业性能不理想的问题,以切纵流联合收获机样机为研究对象,构建联合收获机前进速度模糊控制系统仿真模型,并建立控制性能和收获性能的优化目标函数来衡量联合收获机的作业性能,利用多目标遗传算法对模糊控制系统的隶属函数和输送槽、割台螺旋输送器和切流滚筒对前进速度的影响因子进行优化。通过对优化前后模型仿真对比和两组田间试验数据分析,表明优化后的控制系统在受外界干扰情况下控制性能得到了较好的保持,收获性能在喂入量变化不大情况下,单位平均损失率分别由1.45%和1.26%降至1.12%和1.14%,联合收获机的总体作业性能得到改善。     

马蹄形过水断面正常水深计算的遗传算法

马蹄形过水断面是无压输水隧洞中常采用的断面形式之一 ,因其几何形状复杂 ,水力计算困难。目前常采用的方法有试算法、图解法和迭代法 ,这些方法由于计算量大且精度不易保证 ,不便于在生产实践中应用推广。将马蹄形过水断面正常水深计算转化为非线性优化问题 ,采用实数编码的遗传算法进行求解 ,实例计算表明该方法精度高、通用性强、操作简便 ,便于在生产实践中应用。     

基于遗传算法的机械产品多参数选配方法

对机械产品多参数选配问题进行了描述，并以同时满足多个装配精度，使不适配零件数量最小化为目标，建立了求解该问题的数学模型。针对机械产品多参数选配的特点，提出了一种基于遗传算法的选配方法。根据问题的特殊性，设计了相应的编码方法和遗传算子。最后给出了应用该算法解决机械产品多参数选配问题的一个实例，证明了该算法的可行性与有效性。     

基于改进PSO算法的电机控制系统PID参数优化

粒子群算法(PSO,Particle Swarm Optimization)作为一种新型的随机优化方法,其算法结构简单,鲁棒性强,在组合优化和自适应控制等领域的非线性优化中有着广泛的应用前景.为此,提出一种改进的PSO优化算法,并将该算法应用于电机控制系统的PID参数优化设计.仿真结果表明,利用改进PSO算法优化的PID参数能有效改善控制系统的性能指标.     

优化运行理论在泵站综合自动化系统中的应用

利用改进的神经元网络构建了泵站流量以及效率预测模型，并利用改进的遗传算法构建了泵站优化模型。将这两个模型应用到泵站综合自动化系统中，可以完成对泵站流量及效率的准确预测，并在此基础上实现泵站的优化运行。讨论了泵站优化运行理论在泵站综合自动化系统中应用的步骤和方法。