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    SCALABLE DATA PROCESSING FRAMEWORK FOR DYNAMIC DATA CLEANSING
    2.
    发明申请
    SCALABLE DATA PROCESSING FRAMEWORK FOR DYNAMIC DATA CLEANSING 审中-公开
    用于动态数据清理的可扩展数据处理框架

    公开(公告)号：US20140108359A1

    公开(公告)日：2014-04-17

    申请号：US13781623

    申请日：2013-02-28

    Applicant: CHEVRON U.S.A. INC. ,  UNIVERSITY OF SOUTHERN CALIFORNIA

    Inventor： Farnoush Banaei-Kashani ,  Yingying Zheng ,  Si-Zhao Qin ,  Mohammad Asghari ,  Mahdi Rahmani Mofrad ,  Cyrus Shahabi ,  Lisa A. Brenskelle

    IPC: G06F17/30

    CPC classification number: G06F16/215 ,  G06F11/0745 ,  G06F11/0763

    Abstract: Methods and systems for reconstructing data are disclosed. One method includes receiving a selection of one or more input data streams at a data processing framework, and receiving a definition of one or more analytics components at the data processing framework. The method further includes applying a dynamic principal component analysis to the one or more input data streams, and detecting a fault in the one or more input data streams based at least in part on a prediction error and a variation in principal component subspace generated based on the dynamic principal component analysis. The method also includes reconstructing data at the fault within the one or more input data streams based on data collected prior to occurrence of the fault.

    Abstract translation: 公开了重建数据的方法和系统。 一种方法包括在数据处理框架处接收一个或多个输入数据流的选择，以及在数据处理框架处接收一个或多个分析组件的定义。 该方法还包括将动态主成分分析应用于所述一个或多个输入数据流，以及至少部分地基于预测误差和基于所述主成分子空间的变化来检测所述一个或多个输入数据流中的故障 动态主成分分析。 该方法还包括基于故障发生之前收集的数据，在一个或多个输入数据流内的故障重建数据。

    DATA PROCESSING FRAMEWORK FOR DATA CLEANSING
    5.
    发明申请
    DATA PROCESSING FRAMEWORK FOR DATA CLEANSING 审中-公开
    数据处理框架，用于数据清理

    公开(公告)号：US20160179599A1

    公开(公告)日：2016-06-23

    申请号：US14937701

    申请日：2015-11-10

    Applicant: Chevron U.S.A. Inc. ,  University of Southern California

    Inventor： Alisha Deshpande ,  Yining Dong ,  Gang Li ,  Yingying Zheng ,  Si-Zhao Qin ,  Lisa Ann Brenskelle

    IPC: G06F11/07 ,  H04L29/06

    CPC classification number: H04L65/601 ,  G05B23/024 ,  G06F16/215 ,  H04L65/4069

    Abstract: A computer-implemented method for reconstructing data includes receiving a selection of one or more input data streams at a data processing framework. The method can include determining existence of a fault in the input data stream(s). This determination can be based on receiving a definition of one or more analytics components at the data processing framework and applying a dynamic principal component analysis (DPCA) to the input data streams. Detection of the fault can be based at least in part on a prediction error and a variation in principal component subspace generated based on the DPCA. Detection of the fault can also be based on performing a wavelet transform to generate a set of coefficients defining the data stream, the set of coefficients including one or more coefficients representing a high frequency portion of data included in the data stream. The method can include reconstructing data at the fault.

    Abstract translation: 用于重建数据的计算机实现的方法包括在数据处理框架处接收一个或多个输入数据流的选择。 该方法可以包括确定输入数据流中的故障的存在。 该确定可以基于在数据处理框架处接收一个或多个分析组件的定义并且将动态主成分分析（DPCA）应用于输入数据流。 故障的检测至少部分可以基于DPCA生成的预测误差和主成分子空间的变化。 故障的检测还可以基于执行小波变换以产生定义数据流的系数集合，所述系数集合包括表示数据流中包括的数据的高频部分的一个或多个系数。 该方法可以包括重建故障中的数据。

    SYSTEM AND METHOD FOR CONTROL PERFORMANCE MONITORING
    6.
    发明申请
    SYSTEM AND METHOD FOR CONTROL PERFORMANCE MONITORING 有权
    用于控制性能监测的系统和方法

    公开(公告)号：US20130226348A1

    公开(公告)日：2013-08-29

    申请号：US13774561

    申请日：2013-02-22

    Applicant: Chevron U.S.A., Inc. ,  University of Southern California

    Inventor： Yingying ZHENG ,  Si-Zhao Qin ,  Michael Barham

    IPC: G05D21/02

    CPC classification number: G05D21/02 ,  G05B23/0237 ,  G05B2219/42318 ,  G05B2219/45031

    Abstract: A method for monitoring a control of a parameter of one or more devices or systems in an oil or gas production site includes receiving process data, the process data being a result of the control of the parameter of the one or more devices or systems in the production site; smoothing the process data using a polynomial filter while preserving features of the process data to obtain smoothed data; and applying a pattern recognition algorithm to the smoothed data to determine whether there is a malfunction condition in the one or more devices or systems.

    Abstract translation: 用于监测油气生产场地中的一个或多个装置或系统的参数的控制的方法包括接收过程数据，所述过程数据是控制所述一个或多个装置或系统中参数的结果 生产现场; 使用多项式滤波器平滑处理数据，同时保留处理数据的特征以获得平滑数据; 以及对所述平滑数据应用模式识别算法，以确定所述一个或多个设备或系统中是否存在故障状况。

    System and method for extracting principal time series data
    7.
    发明授权
    System and method for extracting principal time series data 有权

    公开(公告)号：US10955818B2

    公开(公告)日：2021-03-23

    申请号：US15926962

    申请日：2018-03-20

    Applicant: University of Southern California

    Inventor： Si-Zhao Qin ,  Yining Dong

    IPC: G05B19/408 ,  G05B19/418 ,  G05B13/04 ,  G06K9/00 ,  G05B23/02 ,  G06F17/11

    Abstract: A method for extracting a set of principal time series data of dynamic latent variables. The method includes detecting, by a plurality of sensors, dynamic samples of data each corresponding to one of a plurality of original variables. The method also includes analyzing, using a controller, the dynamic samples of data to determine a plurality of latent variables that represent variation in the dynamic samples of data. The method also includes selecting, by the controller, at least one inner latent variable that corresponds to at least one of the plurality of original variables. The method also includes estimating an estimated current value of the at least one inner latent variable based on previous values of the at least one inner latent variable.

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