WEB LONGITUDINAL POSITION SENSOR
    13.
    发明申请
    WEB LONGITUDINAL POSITION SENSOR 有权
    WEB LONGITUDINAL位置传感器

    公开(公告)号:US20100097462A1

    公开(公告)日:2010-04-22

    申请号:US12522493

    申请日:2007-12-19

    Abstract: Methods and systems for determining longitudinal position of an elongated web are described. Sensors are used to detect one or more substantially continuous fiducial marks disposed longitudinally on the web. The sensors generate signals associated with the fiducial marks. A position detector receives the signals and determines a longitudinal position of the web using the sensor signals. The fiducial marks may be periodic fiducial marks, such as sine and/or cosine marks on the web and/or may be piecewise continuous marks. The coarse longitudinal position of the web can be determined based on periodically recurring features of the fiducial marks. The fine longitudinal position can be determined based on continuous portions of the fiducial marks between the periodically recurring features.

    Abstract translation: 描述了用于确定细长网的纵向位置的方法和系统。 传感器用于检测纵向放置在幅材上的一个或多个基本连续的基准标记。 传感器产生与基准标记相关的信号。 位置检测器接收信号并使用传感器信号确定幅材的纵向位置。 基准标记可以是周期性基准标记,例如幅材上的正弦和/或余弦标记和/或可以是分段连续标记。 可以基于基准标记的周期性重复特征来确定幅材的粗略纵向位置。 可以基于周期性重复特征之间的基准标记的连续部分来确定精细纵向位置。

    APPARATUS AND METHODS FOR FABRICATION OF THIN FILM ELECTRONIC DEVICES AND CIRCUITS
    14.
    发明申请
    APPARATUS AND METHODS FOR FABRICATION OF THIN FILM ELECTRONIC DEVICES AND CIRCUITS 审中-公开
    薄膜电子器件和电路的制造方法和装置

    公开(公告)号:US20080171422A1

    公开(公告)日:2008-07-17

    申请号:US11622209

    申请日:2007-01-11

    CPC classification number: H01L51/001 Y02E10/549

    Abstract: Methods and systems for forming layered electronic devices on a flexible, elongated substrate are described. The layered electronic devices include at least one electronically or optically active layer. Deposition of one more layers of the electronic devices occurs as the flexible substrate is moved through one or more deposition stations. At each deposition station the substrate is aligned with an aperture mask having apertures arranged in a pattern. The aperture mask and the substrate are brought into proximity over a portion of a circumference of a rotating drum. A layer of the layered electronic devices is formed by deposition of material through the apertures of the aperture mask. At each deposition station, registration between at least two layers of the layered electronic devices is maintained.

    Abstract translation: 描述了在柔性细长衬底上形成分层电子器件的方法和系统。 分层电子器件包括至少一个电子或光学有源层。 当柔性基板移动通过一个或多个沉积站时,会发生一层电子设备的沉积。 在每个沉积站处,基板与具有以图案布置的孔的孔径掩模对准。 孔径掩模和基底在旋转鼓的圆周的一部分附近。 层状电子器件的层通过孔径掩模的孔隙沉积材料形成。 在每个沉积站处,保持至少两层分层电子器件之间的对准。

    Real-time determination of web tension and control using position sensors
    16.
    发明授权
    Real-time determination of web tension and control using position sensors 有权
    使用位置传感器实时确定纸张张力和控制

    公开(公告)号:US06985789B2

    公开(公告)日:2006-01-10

    申请号:US10743206

    申请日:2003-12-22

    CPC classification number: B65H23/18 B65H23/1888

    Abstract: Web tension in web material passing through a web transport system is determined in real time using position sensors coupled to driven rollers that define a beginning and an end of a tension zone. The position sensors on the rollers provide information related to the amount of strained web material that has been added and subtracted from the web material present in the tension zone. The amount of web material added to, subtracted from and present in the tension zone in a sample time period is then converted to an unstrained amount of web material that when combined provides an estimate for the present amount of unstrained web material present in the tension zone. Because the length of the tension zone is both fixed and known, the tension in the web material is determined from the present amount of unstrained web material in the tension zone.

    Abstract translation: 通过纸幅传送系统的纸幅材料中的网张力通过与定义张紧区域的开始和结束的从动辊连接的位置传感器实时确定。 辊子上的位置传感器提供了与从张力区域中存在的纤维网材料中加入和减去的应变幅材材料量相关的信息。 然后将在样品时间段内从拉伸区域中减去和存在的纤维网材料的量转化为无限量的纤维网材料,当其组合时,提供存在于张力区域中的当前量的未应变纤维网材料的估计值 。 由于张力区域的长度是固定的并且是已知的,因此幅材材料中的张力是根据张力区域中的当前无量纲的纤维网材料量确定的。

    Web longitudinal position sensor
    17.
    发明授权
    Web longitudinal position sensor 有权
    Web纵向位置传感器

    公开(公告)号:US09440812B2

    公开(公告)日:2016-09-13

    申请号:US12522493

    申请日:2007-12-19

    Abstract: Methods and systems for determining longitudinal position of an elongated web are described. Sensors are used to detect one or more substantially continuous fiducial marks disposed longitudinally on the web. The sensors generate signals associated with the fiducial marks. A position detector receives the signals and determines a longitudinal position of the web using the sensor signals. The fiducial marks may be periodic fiducial marks, such as sine and/or cosine marks on the web and/or may be piecewise continuous marks. The coarse longitudinal position of the web can be determined based on periodically recurring features of the fiducial marks. The fine longitudinal position can be determined based on continuous portions of the fiducial marks between the periodically recurring features.

    Abstract translation: 描述了用于确定细长网的纵向位置的方法和系统。 传感器用于检测纵向放置在幅材上的一个或多个基本连续的基准标记。 传感器产生与基准标记相关的信号。 位置检测器接收信号并使用传感器信号确定幅材的纵向位置。 基准标记可以是周期性基准标记,例如幅材上的正弦和/或余弦标记和/或可以是分段连续标记。 可以基于基准标记的周期性重复特征来确定幅材的粗略纵向位置。 可以基于周期性重复特征之间的基准标记的连续部分来确定精细纵向位置。

    Facet classification neural network
    20.
    发明授权
    Facet classification neural network 失效
    方面分类神经网络

    公开(公告)号:US6167390A

    公开(公告)日:2000-12-26

    申请号:US163825

    申请日:1993-12-08

    CPC classification number: G06K9/6272

    Abstract: A classification neural network for piecewise linearly separating an input space to classify input patterns is described. The multilayered neural network comprises an input node, a plurality of difference nodes in a first layer, a minimum node, a plurality of perceptron nodes in a second layer and an output node. In operation, the input node broadcasts the input pattern to all of the difference nodes. The difference nodes, along with the minimum node, identify in which vornoi cell of the piecewise linear separation the input pattern lies. The difference node defining the vornoi cell localizes input pattern to a local coordinate space and sends it to a corresponding perceptron, which produces a class designator for the input pattern.

    Abstract translation: 描述了用于分段线性分离输入空间以分类输入模式的分类神经网络。 多层神经网络包括输入节点,第一层中的多个差分节点,最小节点,第二层中的多个感知节点和输出节点。 在操作中,输入节点将输入模式广播到所有差分节点。 差分节点以及最小节点识别输入模式所在的分段线性分离的哪个单元格。 限定vornoi单元的差异节点将输入模式定位到局部坐标空间,并将其发送到相应的感知器,该感知器产生输入模式的类指示符。

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