二极管钳位式三电平逆变器功率管开路故障诊断

针对二极管钳位式三电平逆变器的开路故障,为了准确、可靠地定位出发生故障的功率管,建立了基于杂交粒子群算法优化BP神经网络的故障诊断模型。分析了单管故障与双管故障输出电流信号的特点,将NPC三电平逆变器所有的故障进行编码,以傅里叶变换提取三相输出电流的直流分量、基波幅值、基波相位以及二次谐波相位作为故障特征向量建立神经网络,并用杂交粒子群算法将其优化。仿真结果表明,该模型能够准确诊断NPC三电平逆变器单管故障与双管故障,并且杂交粒子群算法优化能力优于基本粒子群算法。     

具有强泛化性的高铁逆变器开路故障诊断算法

针对高速铁路工况复杂、不同工况下牵引电机定子电流差异较大、传统逆变器开路故障诊断算法泛化能力较差等问题,提出新的牵引电机定子电流数据预处理方法和基于卷积神经网络的逆变器开路故障诊断算法.该数据预处理算法先对三相定子电流进行角度域同步重采样,再采用基于积分的波形修复算法对电流波形进行修复,并对数据进行规范.提出用于单相定子电流故障诊断的卷积神经网络(T-CNN),以及用于解决两个绝缘栅双极型晶体管同时故障可能导致T-CNN误诊断问题的故障冲突解决规则.实验证明,相比于传统的智能诊断算法,当仅采用单个工况的故障数据训练故障诊断算法时,所提算法在其他工况下具有更好的诊断精度和泛化能力.     

基于MEEMD和GRNN的轨道交通列车辅助逆变器故障诊断

针对轨道交通列车辅助逆变器故障信号的非平稳、非线性特征,提出了一种基于改进的总体平均经验模态分解方法(ModifiedEEMD,MEEMD)和广义回归神经网络的列车辅助逆变器的故障诊断方法。应用MEEMD分解方法对采集的原始故障信号进行处理,将原始故障信号分解成多个平稳的本征模函数(intrinsic mode function,IMF),提取到含有故障信息的特征向量。建立GRNN网络模型,对辅助逆变器的三种故障类型进行识别。仿真结果表明,基于广义回归神经网络的诊断方法与BP神经网络相比有更好的故障诊断效果,可以准确识别列车辅助逆变器的故障类型,并且满足了对故障诊断的准确性要求。     

基于神经网络的电动机逆变驱动系统故障诊断

针对电动机变频调速系统中逆变器开关元件故障类型多，传统故障诊断方法难以实现故障分离等情况，本文提出了一种基于神经网络的电动机变频调速系统故障诊断方法。通过对逆变器输出信号的谱分析可以获得对故障敏感的故障特征量，将这些故障特征量输入神经网络后，由网络输出层的结点输出可以判断故障类型，从而实现故障分离。研究结果表明，该方法可有效实现开关元件断路、短路故障，为进一步实现逆变器容错驱动奠定了理论基础。     

蚁群神经网络在齿轮箱故障诊断中的研究与应用

在ACO算法原理及框架的基础之上,将蚁群优化算法引入到神经网络的训练中来,提出了ACO训练神经网络的基本原理和方法步骤,并应用于发动机齿轮箱故障的故障诊断。本文采取经典的“频域”分析方法对齿轮箱进行故障诊断,并建立了基于蚁群神经网络的齿轮箱故障诊断模型。结果表明,用ACO算法训练的神经网络具有较高的故障诊断精度,可以有效地诊断齿轮箱中的故障,提高了诊断的效率和质量。     

基于FFT和神经网络的APF故障诊断方法

针对有源电力滤波器APF（active power filter）逆变器中IGBT易发生故障的问题,对APF中IGBT开路故障的仿真、故障分类、特征提取、故障诊断等方面进行了研究.对IGBT开路故障与故障特征进行了分析,提出了一种基于快速傅里叶变换（FFT）和神经网络的APF故障诊断方法,用FFT提取的故障特征向量来训练神经网络,并将训练好的神经网络诊断系统对IGBT开路故障进行了测试.实验结果表明,该诊断方法能用于APF运行状态监测,并可快速有效地识别IGBT故障位置.     

基于蚁群算法的机械故障智能诊断方法研究

介绍了蚁群算法基本原理,实验验证了蚁群聚类算法可用于轴承故障诊断,对比蚁群算法和BP神经网络在故障诊断中的不同,分析了蚁群算法在故障模式识别中的特点。     

蚁群优化BP神经网络的电机故障诊断设计与实现

针对传统的故障诊断方法采用专家知识推理方法在获取知识方面的困难,提出了一种采用蚁群优化算法和BP神经网络的自适应电机故障诊断系统。使用BP神经网络对样本数据进行训练,可以建立故障征兆到故障之间的对应关系,从而可以克服专家系统的不足,同时,由于传统的BP算法采用梯度下降算法,具有收敛速度慢和容易陷入局部最优解的问题,且BP神经网络的网络结构和初始参数在确定时往往依靠经验,从而限制了其在故障诊断领域的进一步发展。蚁群算法是一种启发式的模拟进化优化算法,具有正反馈及其分布式计算等特点,因此,将蚁群算法应用于BP神经网络的结构和参数进行优化,然后采用优化后的BP神经网络进行故障诊断,电机诊断实例证明文中方法较BP神经网络和遗传算法优化的BP神经网络具有更高的诊断精度和训练效率。     

蚁群算法融合BP神经网络的齿轮故障模式识别

为了提高齿轮故障诊断的准确性,引入了一种蚁群算法融合BP神经网络的方法。根据齿轮的故障特征量,建立其神经网络的故障诊断模型。以网络的权值和阈值为自变量,通过蚁群算法的迭代运算,搜索出误差全局最小值,再进行网络的二次学习训练,最终实现对齿轮的故障诊断。实例仿真结果表明,该方法具有较高的故障诊断精度,可减少诊断的不确定性。     

基于蚁群神经网络的滚动轴承故障诊断

为了提高滚动轴承故障诊断的准确性,将蚁群算法与神经网络相结合,根据轴承故障产生的机理,建立其BP神经网络的诊断模型,以网络的误差为目标函数,通过蚁群算法进行BP网络的权值优化,并用优化好的BP网络进行故障诊断。仿真结果表明,该方法具有较高的故障诊断准确度,具有较强的实用性。     

On the Relation of Load to Average Gap in the Contact Between Surfaces with Longitudinal Roughness

A computer simulation model for the contact between longitudinally-oriented rough surfaces has been formulated. This model closely duplicates the actual surf ace contact deformation behavior by taking into account the elastic interactions between the asperities. There were no assumptions made about the shapes, or any deformation behavior of the asperities, except for their obeying the laws of elasticity. The plastic deformations on the high asperity peaks were taken into account by setting a ceiling on their contact pressures at the material hardness value. The simulations used real surface profiles which were digitized from unworn circumferentially ground steel surfaces. Each pair of these profiles was mathematically combined to form an equivalent rough profile pressing against an infinitely rigid flat and having the appropriately adjusted elastic modulus. A total of 28 different pairs of profiles were used in the simulations. Each contacting pair was subjected to 30 different load levels and the local contact pressures and deformations were calculated. The contact simulations yielded some important mathematical relationships between parameters, such as the real area of contact, average gap, and average asperity load through statistical curve fitting. Two analytical functions were generated to relate the average load to average gap and the real area of contact to load.     

三绕组变压器的双绕组等效建模及在Matpower中的应用

针对实际电网存在着大量的三绕组变压器,但国际上一些著名商业软件,如BPA仿真软件、Matpower这一权威潮流计算开源软件,均只提供双绕组变压器模型,限制了其在具有三绕组变压器的电力系统中的应用的问题,潮流计算是自主开发的电力系统各种应用软件的核心模块,因此依托国际权威开源程序进行二次开发,是一种较好的选择。对Matpower要求的数据格式进行了归纳,对变压器的一般的等值电路及带理想变压器的等值电路和带标幺值的等值电路进行了分析研究,提出了三绕组变压器转换为双绕组等效模型的建模方法,使得原先只适应双绕组变压器的潮流计算软件可以适用于三绕组变压器电网的潮流计算;最后以Matpower软件为例进行了案例计算,并用PSASP仿真软件进行对比验证。研究结果证明,所提出的建模方法是有效的。     

电站锅炉模糊风险评价方法研究与应用

针对电站锅炉风险等级评价问题,将模糊综合评价技术应用到电站锅炉风险等级评价中。开展了电站锅炉失效影响因素及模糊评价因素的重要程度分析,建立了一套科学合理适于在线评价的电站锅炉风险评价体系,提出了模糊综合评价技术与改进的模糊层次分析法相结合的模糊风险评价方法,利用改进的模糊层次分析法计算了指标体系中各层指标权重。对某一台电站锅炉的实际运行工况影响子因素进行了模糊风险评价,采用模糊合成算子进行模糊综合运算得到电了站锅炉运行工况影响子因素的评价向量。研究结果表明:电站锅炉的运行工况影响子因素的风险评价等级为第6级,失效可能性等级为小,该电站锅炉运行工况良好。     

交通荷载作用下桥梁结构参数识别方法

应用动力节点加载法,将作用在桥梁上的交通荷载转化为等效节点荷载,再用两步构造法识别结构物理参数.第1步,用Newmark-β方法变换结构运动方程,并用结构的加速度响应求得变换空间内的位移、速度和加速度响应;第2步,基于最小二乘原理,构造出变换空间内求解结构参数的递推式,进行结构物理参数识别.数值模拟结果表明,在交通荷载作用下,该方法能够快速、准确地进行桥梁结构参数识别.     

Quantum Cooperative Robotics and Autonomy

The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper.The two areas are brought together in establishing an interdisci...     

考虑进油孔有限长滑动轴承油膜力的近似解析解

针对具有进油孔的有限长滑动轴承油膜力求解问题,采用变分原理和分离变量法,求得了有限长滑动轴承油膜压力分布的近似解析表达式。将油膜压力分布的近似解析表达式在油膜存在区域上进行积分,即得到了油膜力。将提出的计算有限长滑动轴承油膜力方法与无限长轴承模型、有限元方法的计算结果进行了比较,发现了提出的方法与有限元方法的计算结果很接近。最后,研究了进油孔位置和进油压力对油膜存在区域、油膜力等的影响,研究结果表明进油孔位置和进油压力对油膜存在区域和油膜力有较大的影响。     

RLS and LMS blind adaptive multi-user detection method and comparison in acoustic communication

RLS and LMS blind adaptive multi-user detection algorithm and multi-user detector was proposed to solve the problem of multi-user signal detection problem encountered in underwater acoustic communication networks.In simulation analysis,RLS and the LMS blind adaptive multi-user detector were designed and tested for synchronous and asynchronous multi-user communication process.The results of SIR comparison and MMSE comparison show that,both of the two methods can realize blind adaptive detection when any user change in multi-user communication,during this process,the training communication sequences are not needed.The RLS algorithm has about 5 dB higher in SIR compared with LMS algorithm,and the convergence velocity of RLS algorithm is also higher than LMS algorithm when the communication users change.RLS algorithm has better ability in multi-user detection than that of LMS algorithm,and it has great attraction and guiding significance for solving the problem of multiple access interference(MAI) in multi-user communication.     

Robust Impedance Control of Robots Using an Adaptive Interaction Force Observer

For robot interaction control,the interaction force between the robot and the manipulated object or environment should be monitored.Impedance control is a type ...     

Research on key techniques of expendable conductivity temperature depth measuring system

This paper analysis the developing of expendable conductivity temperature depth measuring system(XCTD)and introduce its principle of measuring about temperature,salinity and depth of ocean.Some key techniques are put forward.According to the real needs of XCTD,conductivity sensor with high sensitivity is designed by principle of electromagnetic induce,the ocean conductivity from induced electromotive force has been calculated.Adding temperature correction circuit would help to reduce error of conductivity measurement because of sharply changing temperature.Advanced temperature measuring circuit of high precision and the constant current source is used to weaken effect of self-heating of resistance and fluctuation of the source.On respect of remote data transmission,LVDS is a good choice for the purpose of guarantee the quality of data transmitted and the transmission distance is reaching to thousand meters in the seawater.Modular programming method is also brought into this research aimed at improve the stability,reliability and maintainability of the whole measuring system.In February,2015,the trials in South China Sea demonstrate that the developed XCTD realize effective measurement at a speed of 6 knots and detection depth at 800 m.The consistency coefficient of the acquired data is greater than 0.99 and the success rate of probe launching is above 90%.     

CHARACTERISTCS OF FLUID FILM IN OPTIMIZED SPIRAL GROOVE MECHANICAL SEAL

In order to investigate the sealing performance variation resulted from the thermal deformation of the end faces, the equations to calculate the fluid film pressure distribution, the bearing force and the leakage rate are derived, for the fluid film both in parallel gap and in wedgy gap. The geometrical parameters of the sealing members are optimized by means of heat transfer analysis and complex method. The analysis results indicate that the shallow spiral grooves can generate hydrodynamic pressure while the rotating ring rotates and the bearing force of the fluid film in spiral groove end faces is much larger than that in the flat end faces. The deformation increases the bearing force of the fluid film in flat end faces, but it decreases the hydrodynamic pressure of the fluid film in spiral groove end faces. The gap dimensions which determine the characteristics of the fluid film is obtained by coupling analysis of the frictional heat and the thermal deformation in consideration of the equilibrium condition of the bearing force and the closing force. For different gap dimensions, the relationship between the closing force and the leakage rate is also investigated, based on which the leakage rate can be controlled by adjusting the closing force.