公开(公告)号：US20090276136A1

公开(公告)日：2009-11-05

申请号：US12112021

申请日：2008-04-30

Applicant: Steven Wayne Butler

Inventor： Steven Wayne Butler

IPC: G06F17/00

CPC classification number: G05B23/0281 ,  F05B2260/80

Abstract: A method and system is developed that provides a confidence measure of a prediction of a fault in a gas turbine engine. The confidence measure is developed based upon evaluating the results of a plurality of past predictions and comparing them to an actual fault.

Abstract translation: 开发了一种方法和系统，其提供对燃气涡轮发动机中的故障的预测的可信度测量。 基于评估多个过去预测的结果并将其与实际故障进行比较来开发置信度量度。

公开(公告)号：US08417432B2

公开(公告)日：2013-04-09

申请号：US12112021

申请日：2008-04-30

Applicant: Steven Wayne Butler

Inventor： Steven Wayne Butler

IPC: G06F19/00 ,  G06F11/07 ,  G06F11/30 ,  G01M15/14

CPC classification number: G05B23/0281 ,  F05B2260/80

Abstract: A method and system is developed that provides a confidence measure of a prediction of a fault in a gas turbine engine. The confidence measure is developed based upon evaluating the results of a plurality of past predictions and comparing them to an actual fault.

Abstract translation: 开发了一种方法和系统，其提供对燃气涡轮发动机中的故障的预测的可信度测量。 基于评估多个过去预测的结果并将其与实际故障进行比较来开发置信度量度。

公开(公告)号：US08306791B2

公开(公告)日：2012-11-06

申请号：US12643579

申请日：2009-12-21

Applicant: Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

Inventor： Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

IPC: G06F17/10 ,  G06G7/48

CPC classification number: G06F17/5009 ,  F02C9/00 ,  F05D2270/709 ,  G05B17/02 ,  G06F2217/16

Abstract: 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.

Abstract translation: 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。

公开(公告)号：US20100017092A1

公开(公告)日：2010-01-21

申请号：US12174015

申请日：2008-07-16

Applicant: Steven Wayne Butler

Inventor： Steven Wayne Butler

IPC: G06F19/00

CPC classification number: F01D21/003 ,  B64D2045/0085 ,  F05D2270/44 ,  F05D2270/708 ,  F05D2270/709

Abstract: A method of operating and a fault diagnosis system compares readings to predicted faults using a model-based component, and a database of previous actual fault examples. A predicted fault is provided to an output based upon a combination of both the model-based component and the actual fault examples.

Abstract translation: 操作方法和故障诊断系统使用基于模型的组件将数据与预测故障进行比较，以及之前实际故障示例的数据库。 基于基于模型的组件和实际故障示例的组合，将预测故障提供给输出。

公开(公告)号：US20110153295A1

公开(公告)日：2011-06-23

申请号：US12643579

申请日：2009-12-21

Applicant: Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

Inventor： Sampath K. Yerramalla ,  Steven Wayne Butler ,  William Donat

IPC: G06G7/64 ,  G06F7/00 ,  G06N3/02

CPC classification number: G06F17/5009 ,  F02C9/00 ,  F05D2270/709 ,  G05B17/02 ,  G06F2217/16

Abstract: 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.

Abstract translation: 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。