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    METHOD AND SYSTEM FOR MODELING THE PERFORMANCE OF A GAS TURBINE ENGINE
    1.
    发明申请
    METHOD AND SYSTEM FOR MODELING THE PERFORMANCE OF A GAS TURBINE ENGINE 有权
    用于建模气体涡轮发动机性能的方法和系统

    公开(公告)号：US20110153295A1

    公开(公告)日：2011-06-23

    申请号：US12643579

    申请日：2009-12-21

    申请人： Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

    发明人： Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

    IPC分类号： G06G7/64 ,  G06F7/00 ,  G06N3/02

    CPC分类号： G06F17/5009 ,  F02C9/00 ,  F05D2270/709 ,  G05B17/02 ,  G06F2217/16

    摘要： A method for modeling the performance of a gas turbine engine is provided. The method includes the steps of: 1) providing a processor; 2) inputting flight condition parameter data and engine output parameter data into a gas turbine engine model operating on the processor, which model includes a physics-based engine model that uses the flight condition parameter data to produce estimated engine output parameter data, and determines residuals from the engine output parameter data and the estimated engine output parameter data; 3) partitioning the flight condition parameter data and residuals into training data and testing data; 4) performing a correlation reduction on the training data, which analysis produces correlation adjusted training data; 5) performing an orientation reduction on the correlation adjusted training data, which reduction produces orientation adjusted training data; 6) reviewing the orientation adjusted training data relative to at least one predetermined criteria, and iteratively repeating the steps of performing a correlation reduction and an orientation reduction using the orientation adjusted training data if the criteria is not satisfied, and if the criteria is satisfied outputting the orientation adjusted training data; 7) producing estimated corrections to the orientation adjusted training data using one or more neural networks; 8) evaluating the neural adjusted data using the partitioned testing data; and 9) modeling the performance of the gas turbine using the estimated corrections to the orientation adjusted training data.

    摘要翻译： 提供了一种用于对燃气涡轮发动机性能进行建模的方法。 该方法包括以下步骤：1）提供处理器; 2）将飞行状态参数数据和发动机输出参数数据输入到在处理器上运行的燃气涡轮发动机模型中，该模型包括基于物理的发动机模型，其使用飞行状态参数数据来产生估计的发动机输出参数数据，并且确定残差 从发动机输出参数数据和估计的发动机输出参数数据; 3）将飞行条件参数数据和残差划分为训练数据和测试数据; 4）对训练数据进行相关性降低，该分析产生相关调整的训练数据; 5）对相关调整的训练数据执行取向减少，该减少产生取向调整的训练数据; 6）检查相对于至少一个预定标准的方位调整训练数据，并且如果不满足标准，则迭代地重复执行相关性降低和使用定向调整训练数据的取向减少的步骤，并且如果满足标准输出 方向调整训练数据; 7）使用一个或多个神经网络产生针对调整后的训练数据的估计校正; 8）使用分区测试数据评估神经调整数据; 以及9）使用所估计的校正校正训练数据对燃气轮机的性能进行建模。

    Method and system for modeling the performance of a gas turbine engine
    2.
    发明授权
    Method and system for modeling the performance of a gas turbine engine 有权
    用于对燃气涡轮发动机性能进行建模的方法和系统

    公开(公告)号：US08306791B2

    公开(公告)日：2012-11-06

    申请号：US12643579

    申请日：2009-12-21

    申请人： Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

    发明人： Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

    IPC分类号： G06F17/10 ,  G06G7/48

    CPC分类号： G06F17/5009 ,  F02C9/00 ,  F05D2270/709 ,  G05B17/02 ,  G06F2217/16

    摘要： A method for modeling the performance of a gas turbine engine is provided. The method includes the steps of: 1) providing a processor; 2) inputting flight condition parameter data and engine output parameter data into a gas turbine engine model operating on the processor, which model includes a physics-based engine model that uses the flight condition parameter data to produce estimated engine output parameter data, and determines residuals from the engine output parameter data and the estimated engine output parameter data; 3) partitioning the flight condition parameter data and residuals into training data and testing data; 4) performing a correlation reduction on the training data, which analysis produces correlation adjusted training data; 5) performing an orientation reduction on the correlation adjusted training data, which reduction produces orientation adjusted training data; 6) reviewing the orientation adjusted training data relative to at least one predetermined criteria, and iteratively repeating the steps of performing a correlation reduction and an orientation reduction using the orientation adjusted training data if the criteria is not satisfied, and if the criteria is satisfied outputting the orientation adjusted training data; 7) producing estimated corrections to the orientation adjusted training data using one or more neural networks; 8) evaluating the neural adjusted data using the partitioned testing data; and 9) modeling the performance of the gas turbine using the estimated corrections to the orientation adjusted training data.

    摘要翻译： 提供了一种用于对燃气涡轮发动机性能进行建模的方法。 该方法包括以下步骤：1）提供处理器; 2）将飞行状态参数数据和发动机输出参数数据输入到在处理器上运行的燃气涡轮发动机模型中，该模型包括基于物理的发动机模型，其使用飞行状态参数数据来产生估计的发动机输出参数数据，并且确定残差 从发动机输出参数数据和估计的发动机输出参数数据; 3）将飞行条件参数数据和残差划分为训练数据和测试数据; 4）对训练数据进行相关性降低，该分析产生相关调整的训练数据; 5）对相关调整的训练数据执行取向减少，该减少产生取向调整的训练数据; 6）检查相对于至少一个预定标准的方位调整训练数据，并且如果不满足标准，则迭代地重复执行相关性降低和使用定向调整训练数据的取向减少的步骤，并且如果满足标准输出 方向调整训练数据; 7）使用一个或多个神经网络产生针对调整后的训练数据的估计校正; 8）使用分区测试数据评估神经调整数据; 以及9）使用所估计的校正校正训练数据对燃气轮机的性能进行建模。

    Partitioning of turbomachine faults
    3.
    发明授权
    Partitioning of turbomachine faults 有权
    涡轮机械故障分区

    公开(公告)号：US08862433B2

    公开(公告)日：2014-10-14

    申请号：US12782685

    申请日：2010-05-18

    申请人： Sampath K. Yerramalla ,  William Donat ,  Ravi Rajamani

    发明人： Sampath K. Yerramalla ,  William Donat ,  Ravi Rajamani

    IPC分类号： G01F11/30 ,  G05B9/02 ,  G05B23/02

    CPC分类号： G05B23/0254 ,  G05B9/02 ,  G05B2219/37205 ,  G05B2219/37545

    摘要： An example method of partitioning turbomachine faults includes using a modeling computer to model a system, to establish a modeled gas path parameter, and to establish a modeled subsystem parameter. The method then determines a gas path condition representing a difference between an actual gas path parameter and the modeled gas path parameter. The method also determines a subsystem condition representing a difference between an actual subsystem parameter and the modeled subsystem parameter. The method diagnoses a sensor failure based on the gas path condition and the subsystem condition.

    摘要翻译： 划分涡轮机故障的示例方法包括使用建模计算机对系统建模，建立建模的气体路径参数，以及建立建模的子系统参数。 然后，该方法确定表示实际气体路径参数和建模的气体路径参数之间的差的气体路径条件。 该方法还确定表示实际子系统参数和建模子系统参数之间的差异的子系统条件。 该方法基于气体路径条件和子系统状况诊断传感器故障。