基于蓝牙技术的数控机床无线电流采集系统

为优化数控加工过程中切削及进给速度,以测量数控机床主轴及进给轴电机电流为目标,设计研制了一套基于ARM及蓝牙技术的无线电流采集系统。系统以基于ARM-M3的嵌入式微控制器和基于CSR BC04的蓝牙模块为核心,重点研究了使用ARM进行多路数据采集的嵌入式应用以及采用HCI UART的蓝牙无线通信方式。试验结果表明系统软硬件工作正常,可同时测量4路交直流电流,单路采样频率最高可达720 Hz,具备一定的抗干扰能力,能够满足数控加工过程中电流采集任务的要求。     

Control approaches for high-precision machine tools with airbearings

Numerous control strategies have been developed to compensate for the effects caused by friction in linear guideways of feed-drive systems. For ultraprecision machining applications, these offer a wide variety of powerful, nonlinear algorithms, but generally use rather complex computing algorithms, exhausting system resources. By the use of a special sophisticated aerostatic bearing technology, no friction and, therefore, no stick-slip exist within linear guideways. This entails a lack of damping in the feed direction, which is a considerable setback for the classic cascaded control concept usually implemented in commercially available servo systems. This paper presents an approach to obtain superior behavior of the controlled system by combining the cascaded concept with a control design in the state space. Both simulation and implementation results are presented, together with tuning methods and aspects     

Testing linear macros in mixed-signal systems using transientresponse testing and dynamic supply current monitoring

Transient response testing (TRT) has been shown to be a powerful technique for the testing of linear macros in mixed-signal systems. Its most significant advantage is the ease with which the generic digital stimuli can be injected into, and propagated through, a mixed-signal system. However, with a deeply buried macro the resulting response is difficult to access, and these benefits cannot be fully exploited. The authors show how this problem can be overcome by forcing the transient response of interest to manifest itself in the device supply current, and also present a silicon efficient serial digital test access structure     

Applications of time-frequency analysis to signals frommanufacturing and machine monitoring sensors

Manufacturing industries are now demanding substantial increases in flexibility, productivity and reliability from their process machines as well as increased quality and value of their products. One important strategy to support this goal is sensor-based, on-line, real-time evaluation of key characteristics of both machines and products, throughout the manufacturing process. Recent advances in time-frequency (TF) analysis are particularly well suited to extracting key vibrational characteristics from monitoring sensors. Thus this paper presents applications of TF analysis to several important manufacturing and machine monitoring tasks, to show the value of these forms of digital signal processing applied to manufacturing     

Analysis of knee vibration signals using linear prediction

Clinical methods used at present for the diagnosis of cartilage pathology in the knee are invasive in nature, and carry some risks. There exists a need for the development of a safe, objective, noninvasive method for early detection, localization, and quantification of cartilage pathology in the knee. This paper investigates the possibility of developing such a method based on an analysis of vibrations produced by joint surfaces rubbing against one another during normal movement. In particular, the method of modeling by linear prediction is used for adaptive segmentation and parameterization of knee vibration signals. Dominant poles are extracted from the model system function for each segment based on their energy contributions and bandwidths. These dominant poles represent the dominant features of the signal segments in the spectral domain. Two-dimensional feature vectors are then constructed using the first dominant pole and the ratio of power in the 40-120 Hz band to the total power of the segment. The potential use of this method to distinguish between vibrations produced by normal volunteers and patients known to have cartilage pathology (chondromalacia) is discussed.     

利用DSP控制直流无刷电机

直流无刷电机实际属于永磁同步电机,一般转子为永磁材料,随定子磁场同步转动。这种电机结构简单,而且由于移去了物理电刷,使得电磁性能可靠,维护简单,从而被广泛应用于办公自动化、家电等领域。直流无刷电机运行过程要进行两种控制,一种是转速控制,也即控制提供给定子线圈的电流;另一种是换相控制,在转子到达指定位置改变定子导通相,实现定子磁场改变,这种控制实际上实现了物理电刷的机制。因此这种电机需要有位置反馈机制,比如霍尔元件、光电码盘,或者利用梯形反电动势特点进行反电动势过零检测等。利用光电编码器的系统在软件实现上更方便…     

基于直线电机的数控机床驱动控制技术

针对传统传动链中作为动力源的电动机的不足,提出了直线电机。分析了直线电机原理、特点,介绍了基于直线电机的驱动控制技术。通过对比传统控制技术、现代控制技术、智能控制技术优缺点,提出了采用直线电机位置控制器解决在数控机床中活塞车削数控系统的响应和精度问题。设计采用了PC机与开放式可编程运动控制器构成数控系统。结果表明,利用直线电机结构简单、运动平稳、噪声小,运动部件摩擦小、磨损小、使用寿命长、安全可靠等特性,采用直线电机的开放式数控系统使数控机床驱动控制技术获得新发展。     

基于最小二乘支持向量机的线性特征地物亚像元定位(英文)

BP神经网络已被证明能有效实现遥感图像的亚像元定位,但其训练时间较长,容易陷入局部最优且依赖于大量的训练样本。而在实际应用中,训练样本即先验信息较难获取。然而,建筑物及道路等地物具有规则的线性空间分布。针对这些线性特征地物,研究了一种训练样本的几何合成方法,消除对先验信息的依赖,并提出利用最小二乘支持向量机实现亚像元定位。实验表明,这种结合合成训练样本与最小二乘支持向量机的亚像元定位方法是合理可行的,且与BP神经网络实现方法相比,训练过程明显加快,定位精度更高。     

In-line performance monitoring for RZ-DPSK signals using asynchronous amplitude histogram evaluation

The asynchronous amplitude histogram evaluation technique has been applied to in-line performance monitoring for return-to-zero differential phase-shift keying (RZ-DPSK) signals. The principle of operation was studied by simulation and experiment. It has been demonstrated that residual dispersion and signal optical signal-to-noise ratio can be obtained by Gaussian curve fitting of only one peak in the amplitude histogram of the RZ-DPSK signal.     

基于支持向量机的线性轮廓图控制方法研究

在质量控制的应用中,一些过程或产品质量可以由响应变量与多个解释变量之间的关系（轮廓图）更好地表征.提出了一种基于支持向量机的控制方法来检测第二阶段中线性轮廓图的变化.通过计算机仿真模拟实验与其他几种传统方法以及神经网络的方法做比较发现,仿真得出所提出的控制方法在检测截距和斜率的变化方面表现优异.     

Integrated linear giga-ohm resistance using current scaling

Integrated grounded resistors of very large value are essential circuit elements for the design of compact filters with very low cut-off frequencies. A typical application of such filters is the rejection of DC voltages in amplifier circuits especially in physiological recording systems exhibiting electrode offset and low-frequency drift. In this letter, the implementation of a giga-ohm resistance is presented using a conventional fixed-gain OTA and a cascade of weak-inversion current scalers. The circuit yields a short design time, small power and area consumption as well as high linearity. A test circuit having an area of 0.011 mm² integrated in 0.35 μm CMOS is presented which yields a 41 Hz cut-off frequency, 1 V input range and less than −52 dB THD when connected to an integrated 1 pF capacitor, making it a suitable solution for the rejection of mains interference and offset in wearable biomedical applications.     

Control of linear motor machine tool feed drives for end milling: Robust MIMO approach

Linear motors are getting promising for use as high speed, high accuracy machine tool feed drives. The cutting force in the machining process are directly reflected to the linear motor due to no gearing mechanism. To achieve high accuracy machining, the controller for the linear motor system should be designed to compensate for the cutting force.

In this work, a MIMO H_∞ controller for the linear motor machine tool feed drives has been designed to reduce tracking errors induced by cutting forces for end milling. The controller is designed using normalized coprime factorization method for the dynamic model of the linear motor system. The model includes constant in-line and cross coupling force gain, since the feedback cutting force can be considered as the product of the constant gain and the moving velocity of each axis.

Analysis of the structured singular value shows that the designed controller has good robust performance despite wide variations of the cutting force and physical parameters. It is directly implemented on a linear motor X–Y table which is mounted on a milling machine to have cutting experiments via a DSP board. Experimental results verified effectiveness of the proposed scheme to suppress the effects of the cutting force in the high feed rate.     

Design of single-sided linear induction motors for urban transit

A method of designing low-speed single-sided linear induction motors (SLIMs) for urban transit with maximum speed of 70 km/h is described. The SLIMs can be used not only for Maglev vehicles, but also for the vehicles of the LIM/wheel systems in which the SLIMs are used for propulsion and the wheels for suspension and guidance. The effects of varying principal design parameters on the performance characteristics and the motor weight are numerically investigated. The effects of small changes of the LIM specifications are also shown. The motor weight, the cost of secondary materials, and the energy consumption for a typical route (including regenerative braking operation) are considered as the criteria of goodness for SLIMs. A design example is tackled using the sequential unconstrained minimization technique and the simplex method     

基于B/S数控机床远程监测系统设计及实现

为了提高数控机床的智能化水平,实时、快速、及时地检测机床运行状态下可能发生的故障,保证机床的正常运转,提出了基于B/S模式的数控机床远程监测系统的设计方案,系统利用多传感器、嵌入式ARM微处理器组成的数据采集模块对机床运行状态下主要部件的信号进行采集、处理、传输,存储到PC机上的数据库中,并通过Web服务器读取,将信号以实时数据及图形曲线的形式显示在浏览器上,同时通过预设报警阈值,来对异常数据进行报警,为数控机床的智能化、实时监测运行状态下可能发生的故障提供了可靠的解决方案。     

Estimation of co-channel signals with linear complexity

To increase wireless system capacity using co-channel signals and multiple receiver antennas, we develop the partitioned Viterbi algorithm (PVA). The PVA estimation complexity increases linearly with each additional co-channel signal rather than exponentially as it does with joint maximum-likelihood sequence estimation (MLSE). The estimation problem involves multiple signals simultaneously transmitted and observed through slow-fading, frequency-selective channels. Although transmission is assumed to be in bursts according to a time-division multiple-access scheme, more than one signal can occupy the same time and frequency slot (these signals are referred to as “co-channel” signals). Separation and estimation of the symbol bursts is accomplished by exploiting channel differences, PVA estimation consists of a set of Viterbi detectors, one per signal, that operate in parallel with cross-coupling to allow approximate interference cancellation by means of tentative decisions. The forward filter of a decision feedback equalizer (DFE) is used to “prefilter” received signals prior to PVA estimation. Prefiltering delays the energy of interfering signals so that tentative decisions become reliable enough to use. Simulation results show PVA performance remains near-optimal with respect to the performance of joint MLSE     

Cross-coupled fuzzy logic control for multiaxis machine tools

This paper presents a design and implementation case study that focuses on contour control of a biaxial CNC machine tools. Since, it is difficult to obtain an accurate nonlinear mathematical model of cross-coupled multiaxis machine tools, here we investigate an alternative to conventional approaches where we employ crosscoupled fuzzy logic controllers for improving the contouring accuracy of multiaxis CNC machine tools. A new fuzzy rule-generated method which is based on a performance index of the contour error obtained from an on-line estimation algorithm is proposed. An adapted output scale factor is adopted to improve the system performance. Experimental results have shown that the desired contouring accuracy can be achieved, and the proposed approach outperforms over uncoupled approaches. In conventional control, increasing contour feedrate for productivity may result in larger contour errors. However, the experimental results have shown that the performance of the proposed approach is still quite good with increasing contour feedrate.     

Genetic algorithms for feature selection in machine conditionmonitoring with vibration signals

Artificial neural networks (ANNs) can be used successfully to detect faults in rotating machinery. Using statistical estimates of the vibration signal as input features. In any given scenario, there are many different possible features that may be used as inputs for the ANN. One of the main problems facing the use of ANNs is the selection of the best inputs to the ANN, allowing the creation of compact, highly accurate networks that require comparatively little preprocessing. The paper examines the use of a genetic algorithm (GA) to select the most significant input features from a large set of possible features in machine condition monitoring. Using a GA, a subset of six input features is selected from a set of 66 giving a classification accuracy of 99.8%, compared with an accuracy of 87.2% using an ANN without feature selection and all 66 inputs. From a larger set of 156 different features, the GA is able to select a set of six features to give 100% recognition accuracy     

Step-out detection and error compensation for a micro-stepper motor using current feedback

We propose a method to detect step-outs for a micro-stepper motor and a way to compensate the missing steps to maintain appropriate operation. Coil currents and their behaviors are investigated to determine the onset and termination of a step-out. Exact step-out values are identified, and a corresponding compensation scheme is proposed. Even though the use of an encoder to measure position error provides a means of compensating for the error, the primary cause of the error due to the step-outs may not be clearly identified. Rather, the coil current feedback is used in place of encoder measurements, we can clearly determine amount of the step-outs which results in the position error compensation.     

OPGW断股状态的光学监测技术研究

针对OPGW(光纤复合架空地线)易发生断股的现象,提出了采用布里渊光时域反射仪测量其内部光纤应变的断股检测方法。实验中将一段OPGW的两端固定在拉力机上并施加固定的拉力值,逐渐增加OPGW中断开的单丝数,记录布里渊光时域反射仪测量的光纤应变值。实验结果表明,该方法可实现对25%以上的断股区域截面积比的监测,为在线监测OPGW断股状态提供了一种新的思路。