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1.发明申请公开(公告)号：US20140369591A1
公开(公告)日：2014-12-18
申请号：US14366791
申请日：2012-12-19
CPC分类号： G06T7/004 , D06H3/08 , G01N21/89 , G06F17/30244 , G06T7/0004 , G06T7/70 , G06T2207/30124
摘要： Techniques are described for maintaining synchronization of inspection data when a web roll is converted into intermediate smaller rolls prior to cutting the web into individual parts. A system comprises a database that stores anomaly data acquired from a manufactured web. The anomaly data specifies positions anomalies within a manufactured web relative to a set of fiducial marks on the manufactured web. A conversion processing line comprises a fiducial mark reader to output position information for the set of fiducial marks on the manufactured web, a slitter that cuts the manufactured web into slit rolls, and a fiducial mark printer to print a set of fiducial marks on each slit roll. A position monitoring system maintains spatial synchronization of the anomaly data by computing an updated position for the anomalies relative to the set of fiducial marks printed on the slit rolls.
摘要翻译： 描述了当在将卷材切割成单个部件之前将卷筒纸卷转换成中间较小的卷筒时，描述了用于维持检查数据同步的技术。 系统包括存储从制造的网络获取的异常数据的数据库。 异常数据指定制造的网中相对于制成的网上的一组基准标记的位置异常。 转换处理线包括：基准标记读取器，用于输出所制造的幅材上的一组基准标记的位置信息;将制作的幅材切割成切割辊的分切机;以及基准标记打印机，以在每个狭缝上印刷一组基准标记 滚。 位置监测系统通过计算相对于印刷在切割辊上的基准集合的异常的更新位置来维持异常数据的空间同步。
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公开(公告)号：US20210379783A1
公开(公告)日：2021-12-09
申请号：US17283604
申请日：2019-10-14
发明人： Steven P. Floeder , Steven R. Wageman , Benjamin L. Brown , Carl J. Skeps , Matthew V. Rundquist , Barbara E. Rokke , David P. Bradbury
摘要： This disclosure describes techniques for automatically controlling the operation of a slitter (40) to convert a web (20) of material into smaller slit rolls (64, 66, 68). A slitter director (60) may automatically control the operation of a slitter (40) for defect removal, web splicing, and/or slit roll rejection based on continually registering previously-generated anomaly data (62) with physical locations of the web (20).
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3.发明授权公开(公告)号：US09142023B2
公开(公告)日：2015-09-22
申请号：US14366791
申请日：2012-12-19
CPC分类号： G06T7/004 , D06H3/08 , G01N21/89 , G06F17/30244 , G06T7/0004 , G06T7/70 , G06T2207/30124
摘要： Techniques are described for maintaining synchronization of inspection data when a web roll is converted into intermediate smaller rolls prior to cutting the web into individual parts. A system comprises a database that stores anomaly data acquired from a manufactured web. The anomaly data specifies positions anomalies within a manufactured web relative to a set of fiducial marks on the manufactured web. A conversion processing line comprises a fiducial mark reader to output position information for the set of fiducial marks on the manufactured web, a slitter that cuts the manufactured web into slit rolls, and a fiducial mark printer to print a set of fiducial marks on each slit roll. A position monitoring system maintains spatial synchronization of the anomaly data by computing an updated position for the anomalies relative to the set of fiducial marks printed on the slit rolls.
摘要翻译： 描述了当在将卷材切割成单个部件之前将卷筒纸卷转换成中间较小的卷筒时，描述了用于维持检查数据同步的技术。 系统包括存储从制造的网络获取的异常数据的数据库。 异常数据指定制造的网中相对于制成的网上的一组基准标记的位置异常。 转换处理线包括：基准标记读取器，用于输出所制造的幅材上的一组基准标记的位置信息;将制作的幅材切割成切割辊的分切机;以及基准标记打印机，以在每个狭缝上印刷一组基准标记 滚。 位置监测系统通过计算相对于印刷在切割辊上的基准集合的异常的更新位置来维持异常数据的空间同步。
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公开(公告)号：US20240071059A1
公开(公告)日：2024-02-29
申请号：US18269657
申请日：2021-12-23
发明人： Samuel S. Schreiner , Steven P. Floeder , Jeffrey P. Adolf , Carl J. Skeps , Shane T. Van Kampen
IPC分类号： G06V10/778 , G06V10/77
CPC分类号： G06V10/778 , G06V10/7715
摘要： An example method for selecting product images for training a machine-learning model includes obtaining product images to include in an image population; receiving an indication of an image selection strategy for determining if a product image is to be included in a set of images of interest; determining image transforms based on configuration data for the indicated image selection strategy, wherein the image transforms perform image manipulation operations to obtain transformed image data for each of the product images in the image population; selecting a subset of images from the image population for inclusion in the set of images of interest based on the indicated image selection strategy and the transformed image data; determining one or more descriptive labels and applying the one or more descriptive labels to the respective sets of images; and training an inspection model for a product inspection system based on the labeled images.
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