公开(公告)号：US11378063B2

公开(公告)日：2022-07-05

申请号：US16797593

申请日：2020-02-21

Applicant: GENERAL ELECTRIC COMPANY

Inventor： Zhanpan Zhang ,  Peter Alan Gregg ,  Jin Xia ,  John Mihok ,  Guangliang Zhao ,  Bouchra Bouqata

IPC: F03D17/00 ,  F03D7/04

Abstract: A method of correcting turbine underperformance includes calculating a power production curve using monitored data, detecting changes between the monitored data and a baseline power production curve, generating operability curves for paired operational variables from the monitored data, detecting changes between the operability curves and corresponding baseline operability curves, comparing the changes to a respective predetermined metric, and if the change exceeds the metric, providing feedback to a turbine control system identifying at least one of the paired operational variables for each paired variable in excess of the metric. A system and a non-transitory computer-readable medium are also disclosed.

公开(公告)号：US20220099532A1

公开(公告)日：2022-03-31

申请号：US17032218

申请日：2020-09-25

Applicant: General Electric Company

Inventor： Zhanpan Zhang ,  Guangliang Zhao ,  Jin Xia ,  John Joseph Mihok ,  Frank William Ripple, JR. ,  Kyle Raymond Barden ,  Alvaro Enrique Gil

IPC: G01M99/00 ,  G06N20/00 ,  G05B19/042

Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.

公开(公告)号：US12038354B2

公开(公告)日：2024-07-16

申请号：US17032218

申请日：2020-09-25

Applicant: General Electric Company

Inventor： Zhanpan Zhang ,  Guangliang Zhao ,  Jin Xia ,  John Joseph Mihok ,  Frank William Ripple, Jr. ,  Kyle Raymond Barden ,  Alvaro Enrique Gil

IPC: G01M99/00 ,  G05B19/042 ,  G06N20/00

CPC classification number: G01M99/005 ,  G05B19/042 ,  G06N20/00 ,  G05B2219/2619

Abstract: A system and method are provided for operating a power generating asset. Accordingly, a plurality of operational data sets are received by a controller. The operational data sets include at least one indication of a performance anomaly. A plurality of predictive models are implemented by the controller to determine a plurality of potential root causes of the performance anomaly and a plurality of corresponding probabilities for each of the potential root causes. A consolidation model is generated for classifying the plurality of potential root causes and corresponding probabilities. The consolidation model is trained via a training data set to correlate the plurality of potential root causes to an actual root cause for the performance anomaly. The consolidation model is implemented by the controller to determine the actual root cause of the performance anomaly based on the plurality of potential root causes and corresponding probabilities.