公开(公告)号：US20150058090A1

公开(公告)日：2015-02-26

申请号：US13971316

申请日：2013-08-20

Applicant: General Electric Company

Inventor： Achalesh Kumar Pandey ,  Eric Kauffman ,  Richard Kleinhample ,  Daniel Kish

IPC: G06Q10/06

CPC classification number: G06Q10/0637

Abstract: Systems and methods for generating solution recommendations for power plant operation can be provided by certain embodiments of the disclosure. In one embodiment, a system may include a processor configured to collect power plant operational data from power plant components. The power plant operational data may be analyzed to identify cost factors for the power plant components. Based at least in part on the power plant operational data and the cost factors, upgrade opportunities for the power plant components may be determined. Financial values may be calculated for the upgrade opportunities. Based at least in part on the financial values, recommendations may be generated using a product interaction database and provided as an electronic output to a user.

Abstract translation: 用于产生用于发电厂操作的解决方案建议的系统和方法可以由本公开的某些实施例提供。 在一个实施例中，系统可以包括被配置为从发电厂组件收集发电厂运行数据的处理器。 可以分析电厂运行数据以识别发电厂组件的成本因素。 至少部分地基于电厂运行数据和成本因素，可以确定发电厂组件的升级机会。 可以为升级机会计算财务价值。 至少部分地基于财务价值，可以使用产品交互数据库生成建议，并将其作为电子输出提供给用户。

公开(公告)号：US20160371405A1

公开(公告)日：2016-12-22

申请号：US14744291

申请日：2015-06-19

Applicant: General Electric Company

Inventor： Christopher Michael Raczynski ,  Achalesh Kumar Pandey

IPC: G06F17/50 ,  G06N3/08

CPC classification number: G06F17/5009 ,  G06F2217/16 ,  G06N3/08

Abstract: Embodiments of the disclosure relate to systems and methods of forecasting power plant performance. In one embodiment, a system can include a computer that is configured to use a calibrated physics-based simulation model to generate training data. The training data is used by the computer to effectuate a surrogate neural network model. Furthermore, the computer is configured to receive a periodic performance index. The periodic performance index, which is indicative of dynamic changes in one or more operating parameters of the power plant, is processed in combination with the surrogate neural network model by the computer for forecasting one or more performance parameters of the power plant.

Abstract translation: 本公开的实施例涉及预测发电厂性能的系统和方法。 在一个实施例中，系统可以包括被配置为使用校准的基于物理的仿真模型来生成训练数据的计算机。 计算机使用训练数据来实现替代神经网络模型。 此外，计算机被配置为接收周期性的性能指标。 指示发电厂的一个或多个运行参数的动态变化的周期性性能指标与计算机的代理神经网络模型结合进行处理，用于预测发电厂的一个或多个性能参数。

公开(公告)号：US09500563B2

公开(公告)日：2016-11-22

申请号：US14097540

申请日：2013-12-05

Applicant: General Electric Company

Inventor： Romano Patrick ,  Matthew Francis Lemmon ,  Subrat Nanda ,  Jonathan David White ,  Achalesh Kumar Pandey

IPC: F23M11/00 ,  G01M15/14 ,  F23R3/00 ,  F23N5/16 ,  F23N5/24

CPC classification number: G01M15/14 ,  F05D2260/80 ,  F23M11/00 ,  F23N5/16 ,  F23N5/242 ,  F23N2023/48 ,  F23N2023/54 ,  F23N2041/20 ,  F23R3/00 ,  F23R2900/00005 ,  Y02T50/677

Abstract: A system for detecting an at-fault combustor includes a sensor that is configured to sense combustion dynamics pressure data from the combustor and a computing device that is in electronic communication with the sensor and configured to receive the combustion dynamics pressure data from the sensor. The computing device is programmed to convert the combustion dynamics pressure data into a frequency spectrum, segment the frequency spectrum into a plurality of frequency intervals, extract a feature from the frequency spectrum, generate feature values for the feature within a corresponding frequency interval over a period of time, and to store the feature values to generate a historical database. The computing device is further programmed to execute a machine learning algorithm using the historical database of the feature values to train the computing device to recognize feature behavior that is indicative of an at-fault combustor.

Abstract translation: 用于检测故障期间燃烧器的系统包括传感器，其被配置为感测来自燃烧器的燃烧动力学压力数据和与传感器电子通信并被配置为从传感器接收燃烧动力学压力数据的计算设备。 计算装置被编程为将燃烧动态压力数据转换成频谱，将频谱分段成多个频率间隔，从频谱中提取特征，在一段时间内在对应的频率间隔内生成特征的特征值 的时间，并存储特征值以生成历史数据库。 计算设备还被编程为使用特征值的历史数据库来执行机器学习算法，以训练计算设备以识别指示故障燃烧器的特征行为。

公开(公告)号：US09476584B2

公开(公告)日：2016-10-25

申请号：US14104313

申请日：2013-12-12

Applicant: General Electric Company

Inventor： Awadesh Kumar Tiwari ,  Sidharth Abrol ,  Rasika Suresh Kalwit ,  Achalesh Kumar Pandey ,  John Alexander Petzen ,  Charles William Weidner

IPC: F22D5/30 ,  F22B35/00

CPC classification number: F22D5/30 ,  F22B35/007 ,  Y10T137/0374

Abstract: A method of controlling a water level in a steam drum includes predicting a transient in the steam drum based on plant characteristics including steam flow from the steam drum, drum pressure in the steam drum, and one or both of a gas turbine load and a position of a bypass valve configured to control the steam flow from the steam drum to two or more steam flow conduits. The method further includes generating a sliding setpoint to control the water level based on predicting the transient in the steam drum.

Abstract translation: 一种控制蒸汽滚筒中的水位的方法包括基于植物特征来预测蒸汽轮中的瞬态，包括来自蒸汽鼓的蒸汽流，蒸汽鼓中的鼓压力以及燃气轮机负载和位置 旁通阀构造成控制从蒸汽鼓到两个或更多个蒸汽流动管道的蒸汽流。 该方法还包括产生滑动设定点以基于预测蒸汽滚筒中的瞬态来控制水位。

公开(公告)号：US09200982B2

公开(公告)日：2015-12-01

申请号：US13933416

申请日：2013-07-02

Applicant: General Electric Company

Inventor： Sascha Schieke ,  Vivek Venugopal Badami ,  Achalesh Kumar Pandey

IPC: G01M15/14 ,  G01N29/00 ,  G01N29/06 ,  G01N29/26 ,  G01F1/66

CPC classification number: G01M15/14 ,  G01F1/66 ,  G01F1/667 ,  G01N29/00 ,  G01N29/0672 ,  G01N29/262 ,  G01N2291/02836 ,  G01N2291/2693

Abstract: Various embodiments of the invention include a system having: at least one computing device connected with an array of ultrasonic probes on a gas turbomachine component, the at least one computing device configured to: instruct a first probe in the array of ultrasonic probes to transmit an ultrasonic beam to at least one additional probe in the array of ultrasonic probes; and determine a property of a medium between the first probe and the at least one additional probe based upon a time between transmission of the ultrasonic beam from the first probe and reception of the ultrasonic beam at the at least one additional probe.

Abstract translation: 本发明的各种实施例包括一种系统，该系统具有：与气体涡轮机组件上的超声波探头阵列连接的至少一个计算装置，所述至少一个计算装置被配置为：指示超声波探头阵列中的第一探针发射 超声波束到超声波探头阵列中的至少一个附加探针; 并且基于来自第一探针的超声波束的传输和在至少一个附加探针处的超声波束的接收之间的时间来确定第一探针和至少一个附加探针之间的介质的性质。

公开(公告)号：US20150252786A1

公开(公告)日：2015-09-10

申请号：US14198641

申请日：2014-03-06

Applicant: General Electric Company

Inventor： Awadesh Kumar Tiwari ,  Peter Alan Gregg ,  Raul Munoz Medina ,  Achalesh Kumar Pandey ,  Isaac Alejandro Martinez Tovar

IPC: F03D7/04

CPC classification number: F03D7/04 ,  F03D7/046 ,  F05B2260/821 ,  Y02E10/723

Abstract: The present subject matter is directed to a system and method for optimizing wind turbine operation. For example, the present disclosure is configured to generate operating data for at least one operational parameter of the wind turbine for a predetermined time period. The system can then determine a robustness measurement of at least a portion of the operating data. In general, the robustness measurement indicates the tendency of the operating data to be affected by outliers present in the operating data. In addition, the robustness measurement is typically a function of a distribution of the operating data. The present disclosure is then configured to determine at least one optimal set point for the operational parameter as a function of the robustness measurement and a power production of the wind turbine. The wind turbine can then be operated based on the optimal set point.

Abstract translation: 本发明涉及用于优化风力涡轮机操作的系统和方法。 例如，本公开被配置为在预定时间段内生成风力涡轮机的至少一个操作参数的操作数据。 系统然后可以确定运行数据的至少一部分的鲁棒性测量。 一般来说，鲁棒性测量表明操作数据受操作数据中存在的异常值的影响。 另外，鲁棒性测量通常是操作数据分布的函数。 本公开然后被配置为根据鲁棒性测量和风力涡轮机的功率产生来确定操作参数的至少一个最优设定点。 然后可以基于最佳设定点来操作风力涡轮机。

公开(公告)号：US20150247464A1

公开(公告)日：2015-09-03

申请号：US14194228

申请日：2014-02-28

Applicant: General Electric Company

Inventor： Achalesh Kumar Pandey ,  John Edward Sholes ,  Dwayne David McDuffie ,  Kamlesh Mundra ,  Maria Cecilia Mazzaro

IPC: F02C9/56 ,  G05B15/02 ,  F02G5/00

CPC classification number: F02C9/56 ,  F01K5/02 ,  F02C6/18 ,  F02C9/00 ,  F02G5/00 ,  F05D2260/81 ,  F05D2260/821 ,  F05D2270/083 ,  F05D2270/112 ,  F05D2270/20 ,  F05D2270/3032 ,  F05D2270/332 ,  F05D2270/71 ,  G05B15/02 ,  G05B17/02 ,  Y02E20/16

Abstract: Systems and methods for improved control of a turbomachine system with a bottoming cycle system are presented. The systems and methods include a controller that utilizes modeling techniques to derive a plurality of load path curves. The controller utilizes a current load path, a minimum load path, and a constant efficiency load path. The systems and methods include a control process configured to receive a user input representative of a life cycle control modality and to execute a control action based on deriving a load efficiency by applying the current load path, the minimum load path, the constant efficiency load path, or a combination thereof, and the life cycle control modality. The control action is applied to control the turbomachine system and the bottoming cycle system fluidly coupled to the turbomachine system. Further, the life cycle control modalities may be selected by a user based upon known tradeoffs.

Abstract translation: 提出了一种用于改进具有底循环系统的涡轮机系统控制的系统和方法。 系统和方法包括利用建模技术来导出多个负载路径曲线的控制器。 控制器利用当前负载路径，最小负载路径和恒定效率负载路径。 所述系统和方法包括配置成接收代表生命周期控制模式的用户输入的控制过程，并且通过应用当前负载路径，最小负载路径，恒定效率负载路径来执行基于导出负载效率的控制动作 ，或其组合，以及生命周期控制模式。 控制动作用于控制涡轮机系统和流体耦合到涡轮机系统的底循环系统。 此外，生命周期控制模式可以由用户基于已知的权衡来选择。

公开(公告)号：US20150241308A1

公开(公告)日：2015-08-27

申请号：US14186560

申请日：2014-02-21

Applicant: General Electric Company

Inventor： Achalesh Kumar Pandey ,  Lucy Summerville Giametta

IPC: G01M15/14

CPC classification number: G01M15/14 ,  F02C9/00 ,  F05D2260/80 ,  F05D2270/8041

Abstract: Systems and methods for on-line monitoring of hot gas path components of a gas turbine are provided. According to one embodiment of the disclosure, a system may include a camera operable to monitor one or more hot gas path components of the gas turbine and a processor communicatively coupled to the camera. The processor is operable to receive realtime data from the camera monitoring the one or more hot gas path components of the gas turbine and compare the realtime data to reference data. Based on the comparison, the processor can determine that a difference between the realtime data and the reference data exceeds a predetermined threshold. If the difference exceeds the predetermined threshold, the processor can notify operators of an anomaly in the one or more hot gas path components.

Abstract translation: 提供了一种用于在线监测燃气轮机的热气路径部件的系统和方法。 根据本公开的一个实施例，系统可以包括可操作以监测燃气涡轮机的一个或多个热气体路径部件和通信地耦合到相机的处理器的照相机。 处理器可操作以从摄像机接收监视燃气轮机的一个或多个热气路径部件的实时数据，并将实时数据与参考数据进行比较。 基于比较，处理器可以确定实时数据和参考数据之间的差异超过预定阈值。 如果差异超过预定阈值，则处理器可以通知操作者一个或多个热气体路径部件中的异常。

公开(公告)号：US20150167961A1

公开(公告)日：2015-06-18

申请号：US14104313

申请日：2013-12-12

Applicant: General Electric Company

Inventor： Awadesh Kumar Tiwari ,  Sidharth Abrol ,  Rasika Suresh Kalwit ,  Achalesh Kumar Pandey ,  John Alexander Petzen ,  Charles William Weidner

IPC: F22D5/30

CPC classification number: F22D5/30 ,  F22B35/007 ,  Y10T137/0374

Abstract: A method of controlling a water level in a steam drum includes predicting a transient in the steam drum based on plant characteristics including steam flow from the steam drum, drum pressure in the steam drum, and one or both of a gas turbine load and a position of a bypass valve configured to control the steam flow from the steam drum to two or more steam flow conduits. The method further includes generating a sliding setpoint to control the water level based on predicting the transient in the steam drum.

Abstract translation: 一种控制蒸汽滚筒中的水位的方法包括基于植物特征来预测蒸汽轮中的瞬态，包括来自蒸汽鼓的蒸汽流，蒸汽鼓中的鼓压力以及燃气轮机负载和位置 旁通阀构造成控制从蒸汽鼓到两个或更多个蒸汽流动管道的蒸汽流。 该方法还包括产生滑动设定点以基于预测蒸汽滚筒中的瞬态来控制水位。

公开(公告)号：US09945264B2

公开(公告)日：2018-04-17

申请号：US14587682

申请日：2014-12-31

Applicant: General Electric Company

Inventor： Lisa Anne Wichmann ,  Achalesh Kumar Pandey ,  Eric Thomas Pool ,  Christopher Michael Raczynski ,  Suresh Pamujula

IPC: G05D3/12 ,  G05D5/00 ,  G05D9/00 ,  G05D11/00 ,  G05D17/00 ,  F01K13/02 ,  G05B13/04 ,  F01K23/10 ,  F02C6/00 ,  G05F1/66 ,  F02C9/28

CPC classification number: F01K13/02 ,  F01K23/101 ,  F02C6/00 ,  F02C9/28 ,  F05D2220/32 ,  F05D2220/72 ,  F05D2260/80 ,  F05D2270/053 ,  F05D2270/709 ,  G05B13/04 ,  G05F1/66 ,  Y02E20/16

Abstract: A control method for optimizing or enhancing an operation of a power plant that includes thermal generating units for generating electricity. The power plant may include multiple possible operating modes differentiated by characteristics of operating parameters. The method may include tuning a power plant model so to configure a tuned power plant model. The method may further include simulating proposed operating modes of the power plant with the tuned power plant model. The simulating may include a simulation procedure that includes: defining a second operating period; selecting the proposed operating modes from the possible operating modes; with the tuned power plant model, performing a simulation run for each of the proposed operating modes whereby the operation of the power plant during the second operating period is simulated; and obtaining simulation results from each of the simulation runs.