首页> 外国专利> SCALABLE SYSTEM AND METHOD FOR FORECASTING WIND TURBINE FAILURE USING SCADA ALARM AND EVENT LOGS

SCALABLE SYSTEM AND METHOD FOR FORECASTING WIND TURBINE FAILURE USING SCADA ALARM AND EVENT LOGS

机译:利用SCADA警报和事件日志预测风轮机故障的可伸缩系统和方法

摘要

An example method comprises receiving event and alarm data from event logs, failure data, and asset data from SCADA system(s), retrieve patterns of events from the SCADA data, receiving historical sensor data from sensors of components of wind turbines, training a set of models to predict faults for each component using the patterns of events and historical sensor data, each model of a set having different observation time windows and lead time windows, evaluating each model of a set using standardized metrics, comparing evaluations of each model of a set to select a model with preferred lead time and accuracy, receive current sensor data from the sensors of the components, apply the selected model(s) to the current sensor data to generate a component failure prediction, compare the component failure prediction to a threshold, and generate an alert and report based on the comparison to the threshold.
机译:一种示例方法包括从事件日志接收事件和警报数据,来自SCADA系统的故障数据和资产数据,从SCADA数据检索事件的模式,从风力涡轮机的组件的传感器接收历史传感器数据,训练一组使用事件的模式和历史传感器数据来预测每个组件的故障的模型,一组模型的每个模型具有不同的观察时间窗口和提前期窗口,使用标准化指标评估一组模型的每个模型,比较模型的每个模型的评估结果设置为选择具有首选交付周期和准确性的模型,从组件的传感器接收当前传感器数据,将所选模型应用于当前传感器数据以生成组件故障预测,将组件故障预测与阈值进行比较,并根据与阈值的比较生成警报和报告。

著录项

  • 公开/公告号US2020201950A1

    专利类型

  • 公开/公告日2020-06-25

    原文格式PDF

  • 申请/专利权人 UTOPUS INSIGHTS INC.;

    申请/专利号US201816231122

  • 发明设计人 YAJUAN WANG;YOUNGHUN KIM;

    申请日2018-12-21

  • 分类号G06F17/50;G06N20;

  • 国家 US

  • 入库时间 2022-08-21 11:23:49

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