会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 3. 发明申请
    • Adaptive Multi-Stage Disturbance Rejection
    • 自适应多级干扰抑制
    • US20170017216A1
    • 2017-01-19
    • US14797674
    • 2015-07-13
    • Seagate Technology LLC
    • Zhiqiang XingLou Supino
    • G05B19/042
    • G05B19/042G05B2219/37435
    • Apparatus and method for controlling the position of a control object using a multi-stage actuator. In some embodiments, a multi-stage actuator is provided with first and second actuation stages adapted to position a control object. A control circuit includes a multi-tap lattice structure and parallel first and second multiple regression filters coupled to respective taps of the multi-tap lattice structure. The control circuit concurrently generates and applies first and second disturbance rejection signals to the respective first and second actuation stages to compensate a disturbance signal component in a position error signal (PES) indicative of position error of the control object.
    • 使用多级致动器控制控制对象的位置的装置和方法。 在一些实施例中,多级致动器设置有适于定位控制对象的第一和第二致动级。 控制电路包括多抽头晶格结构以及耦合到多抽头晶格结构的相应抽头的并行的第一和第二多元回归滤波器。 控制电路同时产生并施加第一和第二干扰抑制信号到相应的第一和第二致动级,以补偿指示控制对象的位置误差的位置误差信号(PES)中的干扰信号分量。
    • 4. 发明申请
    • Parallel Digital Signal Processing of Machine Vibration Data
    • 机械振动数据并行数字信号处理
    • US20160025599A1
    • 2016-01-28
    • US14807202
    • 2015-07-23
    • Computational Systems, Inc.
    • John W. Willis
    • G01M99/00
    • G05B19/4065G01M7/00G05B2219/33273G05B2219/37252G05B2219/37434G05B2219/37435
    • A field programmable gate array (FPGA) in a machine health monitoring (MHM) module includes interface circuitry, vibration data processing circuitry, and tachometer data processing circuitry. The interface circuitry de-multiplexes a synchronous serial data stream comprising multiple multiplexed data channels, each containing machine vibration data or tachometer data, into separate input data streams. The vibration data processing circuitry comprises parallel processing channels for the separate input data streams containing vibration data, each channel including a highpass filter, two stages of integration circuits, a digital tracking bandpass filter, and multiple parallel scalar calculation channels. The tachometer data processing circuitry processes the tachometer data to generate RPM and other values. A cross-point switch in the FPGA distributes tachometer signals between MHM modules in a distributed control system, thereby allowing multiple modules to share tachometer information.
    • 机器健康监测(MHM)模块中的现场可编程门阵列(FPGA)包括接口电路,振动数据处理电路和转速表数据处理电路。 接口电路将包含多个复用数据信道的同步串行数据流解码多路复用数据通道,每个多路复用数据通道包含机器振动数据或转速计数据,分离成独立的输入数据流。 振动数据处理电路包括用于包含振动数据的单独输入数据流的并行处理通道,每个通道包括高通滤波器,两级积分电路,数字跟踪带通滤波器和多个并行标量计算通道。 转速计数据处理电路处理转速计数据以产生RPM和其他值。 FPGA中的交叉点开关在分布式控制系统中的MHM模块之间分配转速计信号,从而允许多个模块共享转速计信息。
    • 5. 发明授权
    • Operating method for a machine which is driven using a drive, with state identification by means of frequency analysis
    • 使用驱动器驱动的机器的操作方法,通过频率分析进行状态识别
    • US08026687B2
    • 2011-09-27
    • US12399403
    • 2009-03-06
    • Karl Gebert
    • Karl Gebert
    • G05B11/36
    • G05B19/4065G05B2219/37252G05B2219/37435
    • A machine having a drive that directly or indirectly excites vibrations in the machine over a frequency range when the drive is connected to the power supply. A sensor detects a time-dependent signal that is characteristic of the excited vibrations. The time-dependent signal is transmitted to a control device that analyzes the frequency of the time-dependent signal and relates the frequency analysis to the excitation that produces the excitation and uses this relationship to determine a state of at least one element of the machine. The control device outputs a message to an operator of the machine on the basis of the state that is determined. Preferably, the control device applies an interference variable that has at least one frequency inside the frequency range to the drive so as to excite vibrations. The interference variable may be a sinusoidal interference variable whose frequency passes through the frequency range, or a pseudobinary interference variable whose spectrum covers the frequency range. If the drive is an electrical three-phase drive, asymmetrical energization may be used.
    • 具有驱动器的机器,其在驱动器连接到电源时在频率范围内直接或间接地激励机器中的振动。 传感器检测到受激振动的特征的时间相关信号。 时间相关信号被发送到控制装置,该控制装置分析时间相关信号的频率,并将频率分析与产生激励的激励相关联,并使用该关系来确定机器的至少一个元件的状态。 控制装置根据所确定的状态向机器的操作者输出消息。 优选地,控制装置将具有频率范围内的至少一个频率的干扰变量应用于驱动器以便激发振动。 干扰变量可以是频率通过频率范围的正弦干扰变量,或者频谱覆盖频率范围的伪二进制干扰变量。 如果驱动器是电气三相驱动器,则可以使用非对称通电。
    • 7. 发明申请
    • Device for overall machine tool monitoring
    • 整机检测装置
    • US20080133439A1
    • 2008-06-05
    • US11987440
    • 2007-11-30
    • Kazutaka Ikeda
    • Kazutaka Ikeda
    • G06F15/18
    • G01H1/003G01H1/12G05B19/406G05B2219/33296G05B2219/37435
    • A first and a second neural network classify, into normal and abnormal categories, amounts of characteristics extracted from target signals generated when a machine tool is racing prior to machining a workpiece and while the machine tool is machining the workpiece, respectively. A determination unit determines whether an anomaly exists before the machine tool machines the workpiece and while the machine tool is machining the workpiece, and whether there is a fault in the machine tool, based on the classification results from the first and the second neural networks, deviation history between weight coefficients of neurons in an output layer included in the first neural network and the amounts of characteristics extracted by the first characteristics extracting unit, and deviation history between weight coefficients of neurons in an output layer included in the second neural network and the amounts of characteristics extracted by the second characteristics extracting unit.
    • 第一和第二神经网络分类为正常和异常类别,分别在机床加工工件之前和机床加工工件时分别产生的目标信号中提取的特征量。 确定单元基于第一和第二神经网络的分类结果来确定在机床加工工件之前和机床加工工件以及机床是否存在故障之前是否存在异常, 包括在第一神经网络中的输出层中的神经元的权重系数与由第一特征提取单元提取的特征量之间的偏差历史以及包括在第二神经网络中的输出层中的神经元的权重系数之间的偏差历史,以及 由第二特征提取单元提取的特征量。
    • 8. 发明申请
    • Device for estimating machining dimension of machine tool
    • 机床加工尺寸估算装置
    • US20080082200A1
    • 2008-04-03
    • US11902546
    • 2007-09-24
    • Kazutaka Ikeda
    • Kazutaka Ikeda
    • G06F19/00
    • G05B19/406G05B2219/33296G05B2219/37435Y10T82/2595Y10T409/309576
    • A device for estimating machining dimensions of a machine tool which employs tool members each being rotatably driven by a driving unit includes: a vibration sensor; a characteristics extracting unit for extracting amounts of characteristics from an output of the vibration sensor; a neural network for classifying the amounts of characteristics into categories; and a conversion unit. Amounts of characteristics of generated output by racing the tool member are used for training the neural network, and inputted again to the trained competitive learning neural network to excite neurons so that the relationships between Euclidean distances and machining dimensions of workpieces are registered in the conversion unit. The Euclidean distances are obtained between weight vectors of the excited neurons and respective corresponding training samples, and the machining dimensions are obtained when the workpieces are machined by the tool members at the same condition as the respective corresponding training samples are obtained.
    • 一种用于估计机床的加工尺寸的装置,其采用各自由驱动单元旋转驱动的工具构件,包括:振动传感器; 特征提取单元,用于从所述振动传感器的输出中提取特征量; 用于将特征量分类为类别的神经网络; 和转换单元。 通过赛车工具构件产生的输出的特征量用于训练神经网络,并再次输入训练有素的竞争学习神经网络,以激发神经元,使得欧氏距离与工件加工尺寸之间的关系被记录在转换单元中 。 在激发的神经元的权重向量和相应的训练样本之间获得欧几里德距离,并且当在与获得相应的相应训练样本相同的条件下工具被加工时获得加工尺寸。