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    METHOD OF PERFORMING A PROCESS AND OPTIMIZING CONTROL SIGNALS USED IN THE PROCESS
    2.
    发明申请
    METHOD OF PERFORMING A PROCESS AND OPTIMIZING CONTROL SIGNALS USED IN THE PROCESS 审中-公开

    公开(公告)号：WO2020188328A1

    公开(公告)日：2020-09-24

    申请号：PCT/IB2019/057648

    申请日：2019-09-11

    申请人： 3M INNOVATIVE PROPERTIES COMPANY

    发明人： BROOKS, Brian E. ,  BENOIT, Gilles J. ,  OLSON, Peter O. ,  OLSON, Tyler W. ,  NAYAR, Himanshu ,  ARSENAULT, Frederick J. ,  JOHNSON, Nicholas A.

    IPC分类号： G05B19/042

    摘要： A method of performing a process using a plurality of control signals and resulting in a plurality of measurable outcomes is described. The method includes optimizing the plurality of control signals by at least: receiving a plurality of process constraints; receiving, for each measurable outcome, an optimum range; receiving, for each control signal, a plurality of potential optimum values; iteratively performing the process, where for each process iteration, the value of each control signal is selected from among the plurality of potential optimum values received for the control signal; for each process iteration, measuring each outcome in the plurality of measurable outcomes; and generating confidence intervals for the control signals to determine a causal relationship between the control signals and the measurable outcomes. The method includes performing the process using at least the control signals determined by the causal relationship to causally affect at least one of the measurable outcomes.

    SYSTEMS AND METHODS FOR SELECTING GRID ACTIONS TO IMPROVE GRID OUTCOMES
    3.
    发明申请
    SYSTEMS AND METHODS FOR SELECTING GRID ACTIONS TO IMPROVE GRID OUTCOMES 审中-公开
    选择网格行为以改善网路成果的系统和方法

    公开(公告)号：WO2016115002A1

    公开(公告)日：2016-07-21

    申请号：PCT/US2016/012787

    申请日：2016-01-11

    申请人： 3M INNOVATIVE PROPERTIES COMPANY

    发明人： BROOKS, Brian E. ,  BENOIT, Gilles J. ,  LU, Yang

    IPC分类号： H02J3/00 ,  G06Q50/06

    CPC分类号： H02J13/0006 ,  G05B15/02 ,  G06Q10/06 ,  G06Q50/06 ,  H02J13/001 ,  H02J2003/001 ,  H02J2003/007 ,  Y02E60/76 ,  Y04S10/40 ,  Y04S10/525 ,  Y04S40/22

    摘要： Systems and methods for automatically selecting actions to take on a utility grid to simultaneously reduce uncertainty while selecting actions that improve one or more effectiveness metrics. Grid action effects are represented as confidence intervals, the overlap of which is used as a weight when selecting actions within a constrained search space of grid actions. The response of the utility grid to the grid actions may be measured and parsed by the temporal and spatial reach of the grid action, then used to update the confidence intervals for that particular selected grid action.

    摘要翻译： 系统和方法，用于自动选择采取公用事业电网的行动，同时减少不确定性，同时选择改善一个或多个有效性指标的行动。 网格动作效应被表示为置信区间，其重叠被用作在网格动作的受限搜索空间内选择动作时的权重。 公用电网对网格动作的响应可以通过网格动作的时间和空间范围来测量和解析，然后用于更新该特定所选网格动作的置信区间。

    SYSTEMS AND METHODS FOR CLASSIFYING IN-SITU SENSOR RESPONSE DATA PATTERNS REPRESENTATIVE OF GRID PATHOLOGY SEVERITY
    4.
    发明申请
    SYSTEMS AND METHODS FOR CLASSIFYING IN-SITU SENSOR RESPONSE DATA PATTERNS REPRESENTATIVE OF GRID PATHOLOGY SEVERITY 审中-公开
    用于分类现场传感器响应数据模式的系统和方法网格病理学严重程度的表示

    公开(公告)号：WO2016011014A1

    公开(公告)日：2016-01-21

    申请号：PCT/US2015/040359

    申请日：2015-07-14

    申请人： 3M INNOVATIVE PROPERTIES COMPANY

    发明人： BROOKS, Brian E. ,  LU, Yang ,  TIO, Andrew T. ,  BENOIT, Gilles J.

    IPC分类号： G06Q50/06

    CPC分类号： G05B13/045 ,  G06Q50/06

    摘要： The present invention is directed towards methods and systems for characterizing sensors and developing classifiers for sensor responses on a utility grid. Experiments are conducted by selectively varying utility grid parameters and observing the responses of utility grid to the variation. Methods and systems of this invention then associate the particular responses of the utility grid sensors with specific variations in the grid parameters, based on knowledge of the areas of space and periods of time where the variation in grid parameters may affect the sensor response. This associated data is then used to updating a model of grid response.

    摘要翻译： 本发明涉及用于表征传感器和开发用于公用电网上的传感器响应的分类器的方法和系统。 通过选择性地改变公用电网参数并观察公用电网对变化的响应来进行实验。 然后，本发明的方法和系统基于对电网参数变化可能影响传感器响应的空间区域和时间段的知识将公用电网传感器的特定响应与电网参数中的具体变化相关联。 然后将该关联数据用于更新网格响应的模型。

    SCENE CONTENT AND ATTENTION SYSTEM
    8.
    发明申请
    SCENE CONTENT AND ATTENTION SYSTEM 审中-公开

    公开(公告)号：WO2021048765A1

    公开(公告)日：2021-03-18

    申请号：PCT/IB2020/058388

    申请日：2020-09-09

    申请人： 3M INNOVATIVE PROPERTIES COMPANY

    发明人： BROOKS, Brian E. ,  LONG, Andrew W. ,  SMITH, Kenneth L. ,  SNYDER, James B. ,  TIKOTEKAR, Payas ,  BARNES, Carla H.

    IPC分类号： B60W40/02 ,  B60W60/00 ,  B60W50/14 ,  G06T7/11 ,  G06T11/60 ,  G06F3/01 ,  G06K9/00 ,  B60W50/00

    摘要： In some examples, a computing device includes one or more computer processors configured to receive, from an image capture device, an image of a physical scene that is viewable by an operator of a vehicle, wherein the physical scene is at least partially in a trajectory of the vehicle; receive, from an eye-tracking sensor, eye-tracking data that indicates a portion of the physical scene at which vision of the operator is directed; generate, based at least in part on excluding the portion of the physical scene at which vision of the operator is directed, a description of the physical scene; and perform at least one operation based at least in part on the description of the physical scene that is generated based at least in part on excluding the portion of the physical scene at which the vision of the operator is directed.

    DEEP CAUSAL LEARNING FOR CONTINUOUS TESTING, DIAGNOSIS, AND OPTIMIZATION
    9.
    发明申请
    DEEP CAUSAL LEARNING FOR CONTINUOUS TESTING, DIAGNOSIS, AND OPTIMIZATION 审中-公开

    公开(公告)号：WO2020188331A1

    公开(公告)日：2020-09-24

    申请号：PCT/IB2019/057673

    申请日：2019-09-11

    申请人： 3M INNOVATIVE PROPERTIES COMPANY

    发明人： BENOIT, Gilles J. ,  BROOKS, Brian E. ,  OLSON, Peter O. ,  OLSON, Tyler W.

    IPC分类号： G06N3/08

    摘要： A system and methods for multivariant learning and optimization repeatedly generate self-organized experimental units (SOEUs) based on the one or more assumptions for a randomized multivariate comparison of process decisions to be provided to users of a system. The SOEUs are injected into the system to generate quantified inferences about the process decisions. Responsive to injecting the SOEUs, at least one confidence interval is identified within the quantified inferences, and the SOEUs are iteratively modified based on the at least one confidence interval to identify at least one causal interaction of the process decisions within the system. The causal interaction can be used for testing, diagnosis, and optimization of the system performance.