Electromagnetic interference modeling and suppression techniques in variable-frequency drive systems

Electromagnetic interference (EMI) causes electromechanical damage to the motors and degrades the reliability of variable-frequency drive (VFD) systems. Unlike fundamental frequency components in motor drive systems, high-frequency EMI noise, coupled with the parasitic parameters of the trough system, are difficult to analyze and reduce. In this article, EMI modeling techniques for different function units in a VFD system, including induction motors, motor bearings, and rectifier-inverters, are reviewed and evaluated in terms of applied frequency range, model parameterization, and model accuracy. The EMI models for the motors are categorized based on modeling techniques and model topologies. Motor bearing and shaft models are also reviewed, and techniques that are used to eliminate bearing current are evaluated. Modeling techniques for conventional rectifier-inverter systems are also summarized. EMI noise suppression techniques, including passive filter, Wheatstone bridge balance, active filter, and optimized modulation, are reviewed and compared based on the VFD system models.     

船用舵机两种液压驱动方式振动噪声对比试验

液压驱动是目前船用舵机的主要驱动方式,其振动噪声不仅会影响系统的平稳运行、人员的健康舒适,还会对设备和元件的寿命产生影响,因此,振动噪声水平是现代船舶装备设计的关键指标之一。针对双柱塞缸对称驱动及单柱塞缸非对称驱动典型船用舵机,通过容积控制和节流控制两种方式,进行了两种舵机系统振动噪声的对比试验,探讨了不同驱动方式、不同驱动速度等因素对船用舵机振动噪声的影响。结果表明:采用阀控双柱塞缸对称驱动可有效降低舵机系统的振动噪声。     

直线电机直接驱动技术在高速精密加工中的应用

直线电机直接驱动系统具有结构简单、动态响应快、速度和加速度大、精度高、振动和噪声小等一系列优点,是各类高速精密机床的理想传动方式。本文介绍了直线电机的工作原理和结构类型,介绍了直线电机直接驱动系统的特点及其在高速精密加工中的应用状况。     

Neural Network Compact Ensemble and Its Applications

There has been many methods in constructing neural network (NN) ensembles, where the method of simultaneous training has succeed in generalization performance and efficiency. But just like regular methods of constructing NN ensembles, it follows the two steps, first training component networks, and then combining them. As the two steps being independent, an assumption is used to facilitate interactions among NNs during the training stage. This paper presents a compact ensemble method which integrates the two steps of ensemble construction into one step by attempting to train individual NNs in an ensemble and weigh the individual members adaptively according to their individual performance in the same learning process. This provides an opportunity for the individual NNs to interact with each other based on their real contributions to the ensemble. The classification performance of NN compact ensemble(NNCE) was validated through some benchmark problems in machine learning, including Australian credit card assessment, pima Indians diabetes, heart disease, breast cancer and glass. Compared with other ensembles, the classification error rate of NNCE can be decreased by 0.45% to 68%. In addition, the NNCE was applied to fault diagnosis for rolling element bearing. The 11 time-domain statistical features are extracted as the properties of data, and the NNCE is employed to classify the data. With the results of several experiments, the compact ensemble method is shown to give good generalization performance. The compact ensemble method can recognize the different fault types and various fault degrees of the same fault type.     

CM2000铣刨机皮带传动机构的有限元分析

CM2000铣刨机被广泛应用于公路及城市道路的养护中,皮带传动机构作为铣刨机最重要的一部分,它主要作用是将铣刨的碎料传递出去,其结构的设计直接影响着铣刨机的性能。利用大型有限元AGLOR分析软件对CM2000铣刨机皮带传动机构进行分析,得到了不同机构(采用方钢钢架和工字钢钢架)应力应变场量的分布情况,通过比较得出较为合理的皮带传动机构,可为铣刨机设计者提供一定参考依据。     

电动汽车电机驱动系统及其控制技术的研究

电动汽车驱动系统及其所采用的控制方案是决定电动汽车性能的关键技术。高性能的电动汽车采用闭环控制和先进的控制算法,并采用普通硬件和复杂软件相结合,实现电动汽车不同的使用要求。介绍了电机驱动系统的布置方式,比较了不同类型电动汽车驱动系统的优势和不足,探讨了驱动系统的参数选择,分析了电动汽车所采用的控制技术。最后,预测了电机驱动系统未来的发展方向。     

高承压泥水平衡盾构机主驱动压力补偿系统研究

基于高承压泥水平衡盾构机的市场需求,研究了一种主驱动压力补偿系统。首先对组合密封形式的承压能力进行了仿真分析;其次对两种不同控制方式的压力补偿系统设计方案进行了对比研究;最终确定了一种性能稳定、可靠性高的全气动控制的主驱动压力补偿系统,从而提高了泥水平衡盾构机的整机承压能力。通过模拟盾构机掘进过程中各密封腔体压力变化,搭载自适应密封压力补偿系统试验台进行实验分析,并成功应用于国内多个超大直径泥水平衡盾构机。     

电机群网络管控一体化PLC-SCADA设计及应用

针对电机数量众多、时序复杂、传动要求高、地域分布分散等工业生产过程,利用PLC、SCADA、变频器在工控领域中的优点,设计了一种基于网络和PROFIBUS-DP、RS-485总线技术的电机群网络管控一体化的PLC-SCADA系统。借助网络和总线实现对电机群传动系统的管理和控制。通过在纺织印染机构多单元电机传动中的应用,实践证明该控制方案可靠、有效。     

永磁直驱皮带机系统关键技术的研究

为了改变带式输送机传统驱动系统效率低、启动不平稳、重载启动困难等缺点,达到高效、节能、启动平稳、恒转矩控制的目的,永磁直驱系统采用了无齿轮永磁同步变频直驱系统,即驱动系统由永磁同步电机与变频器相结合实现动力的传递。由于去掉了减速器、液力耦合器,因此整个驱动系统具有低噪声、免维护、输出转矩大、启动平稳、恒转矩控制等优点。     

Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks

This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control system. Performance of the control system is successfully tested by performing several six-degrees-of-freedom nonlinear simulations.     

液压阀的噪声控制探讨

分析了液压阀噪声的类型及其产生的原因,针对不同类型,从液压阀结构设计、加工制造、系统优化、安装和维护等方面人手,提出了控制和降低噪声的有效措施.     

Learning from adaptive neural network output feedback control of a unicycle-type mobile robot

This paper studies learning from adaptive neural network (NN) output feedback control of nonholonomic unicycle-type mobile robots. The major difficulties are caused by the unknown robot system dynamics and the unmeasurable states. To overcome these difficulties, a new adaptive control scheme is proposed including designing a new adaptive NN output feedback controller and two high-gain observers. It is shown that the stability of the closed-loop robot system and the convergence of tracking errors are guaranteed. The unknown robot system dynamics can be approximated by radial basis function NNs. When repeating same or similar control tasks, the learned knowledge can be recalled and reused to achieve guaranteed stability and better control performance, thereby avoiding the tremendous repeated training process of NNs.     

带式啮合介质齿轮传动动力学性能分析

针对带式啮合介质齿轮传动中存在的动力学性能问题,首先建立了考虑齿轮啮合刚度、误差激励、介质带阻尼等参数的带式啮合介质齿轮传动系统简化振动模型,然后利用Solidworks软件对带式啮合介质齿轮传动系统进行了实体建模,最后导入ANSYS有限元分析软件对该模型进行了动力学性能分析仿真。研究结果表明：介质带的存在没有改变齿轮传动过程中的应力变化规律;带式啮合介质齿轮传动相比普通渐开线齿轮传动,其振动幅度减小,振动周期增大,介质带的存在改变了传动系统啮合刚度和啮合阻尼,起到了减振降噪的作用。     

稳健的仿射投影符号自适应滤波算法

非高斯的冲击噪声在现实世界广泛存在,严重影响了基于l2范数优化准则的自适应滤波算法的性能。在各类自适应滤波算法中仿射投影符号算法(APSA)结合了仿射投影算法(APA)良好的收敛特性和符号算法对非高斯冲击噪声干扰的抑制能力,因而其在非高斯冲击噪声条件下具有良好的性能。但是该算法的步长选择是固定的,且未考虑系统稀疏特性,因而在参数选择和收敛速度方面有一定的局限性。将变步长的方法和比例矩阵的思想融合到一起,引入步长函数,提出了一种稳健的仿射投影符号自适应滤波算法—变步长的改进比例仿射投影符号算法(VSS-IPAPSA)。该算法不仅可以缓解收敛速度与稳态失调之间的矛盾,同时也可以增加其对系统的不同稀疏特性和噪声特性的适应性。理论分析和仿真实验结果验证了其稳健性和有效性。     

MRT letter: Quantum noise removal and classification of breast mammogram images

Because of the limitations of the X‐ray hardware systems in mammogram machines, the quality of the breast mammogram images may undergo from poor resolution or low contrast. Quantum noise occurs in the mammogram images during acquisition due to low‐count X‐ray photons. In this work, an adaptive frost filter has been used to remove quantum noise. Local binary patterns have been extracted to classify breast mammograms into benign and malignant using different classifiers. Results show the superiority of the proposed algorithm in terms of sensitivity, specificity, and accuracy. Mammographic Institute Society Analysis database of mammography has been used for experimentation. Peak signal‐to‐noise ratio and structural similarity index measure are used to test the validity of adaptive frost filter. Experiment results show that proposed technique produces better results. Microsc. Res. Tech. 2012. © 2012 Wiley Periodicals, Inc.     

Algorithms of wavefront generation for aspheric surface measurement

For aspheric surface measurement with wavefront sensing technology, after obtaining the slope or curvature as the measurement raw data, the data processing algorithm must be re-studied for high performance in practical application. This paper designs, analyzes and compares five different algorithms to generate wavefront for aspheric surface measurements, especially for practical measurements with noises and missing data. Simulation and experimental results show that in ideal condition without any noise in the system, direct fitting yields perfect results without error; the algorithms including Southwell reconstruction achieve better results under practical conditions, where there exist real issues such as noise and abnormal data. Reconstruction is therefore an essential step as it significantly improves the measurement stability and reliability, and enables the system feasible for practical applications. Furthermore, Southwell algorithm is extended for applications with missing data, which is most likely happen when the surfaces to be measured possess large dynamic range.     

基于神经网络PID的冗余伺服系统自适应控制

建立冗余直接驱动式电液伺服系统的数学模型。针对电液伺服系统时变、强非线性的特点以及冗余伺服系统在余度降级过程中的故障瞬态现象和余度降级后的性能降级现象,考虑传统PID控制器自适应能力不强、鲁棒性差等缺陷,提出神经网络自适应控制方案。根据冗余电液伺服系统的特点和目前神经网络控制的发展水平,采用基于径向基函数神经网络的智能PID控制器实现冗余伺服系统的自适应控制。研究结果表明：该控制器能够根据控制指令、被控对象结构参数等因素的变化实时调整控制器参数,和传统PID控制器相比具有控制精度高、鲁棒性强的特点,可以有效地克服冗余伺服系统余度切换时的故障瞬态现象和余度降级后的性能降低现象。     

Adaptive Control of Neutralization Process using Neural Networks

Abstract

A neural network (NN) based adaptive interaction technique is proposed for controlling highly nonlinear neutralization processes. In this approach, the controller is decomposed into interconnected subsystems and adaptation occurs during the interactions. This approach is adaptive in structure and doesn't use an explicit model of the process in the design. The NN is used to establish the adaptive interaction technique for the development of a nonlinear pH controller, which calculates the necessary change in a manipulated variable to drive the system to the desired value. By applying this adaptive algorithm, the same adaptation as the back‐propagation algorithm is achieved without the need of backward propagating the error throughout a feedback network. This important property makes it possible to adapt the NN controller directly without a process model. This advantage reduces the computational complexity drastically in comparison to the well known back‐propagation algorithm based adaptive NN system and a model based system. The designed model‐free online adaptive controller was implemented to a laboratory scaled pH process in real time by use of a dSPACE 1104 interfacing card. The responses of pH and acid flow rate show good tracking for both the set point and load changes over the entire nonlinear region.     

HMJ型桌式号码打印机传动机构

简要介绍该机的用途和性能。分析主传动、拨号、色带打印和压印等机构的传动原理及各机构的运动周期。