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公开(公告)号：US20170298836A1
公开(公告)日：2017-10-19
申请号：US15132782
申请日：2016-04-19
CPC分类号： F02C9/18 , F01D17/105 , F04D27/001 , F04D27/0215 , F04D27/023 , F05D2260/80 , F05D2260/81 , F05D2270/44 , F05D2270/709 , F05D2270/71
摘要： In one example embodiment, a gas turbine system includes a gas turbine, a compressor bleed valve, various sensors, and a valve health assessment system. The compressor bleed valve bleeds a portion of air received by the compressor during certain operating modes. The valve health assessment system includes a processor that uses a neural network model to generate a first failure mode predictor of the compressor bleed valve by processing operational data provided by the various sensors. The processor also generates a second failure mode predictor of the compressor bleed valve by using empirical data and a valve transfer function. The processor further generates a third failure mode predictor of the compressor bleed valve by using predictive data and a prediction model. The processor then applies a holistic procedure to the three failure mode predictors to derive a probability of occurrence of a failure in the compressor bleed valve.
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公开(公告)号：US20170175680A1
公开(公告)日：2017-06-22
申请号：US15301496
申请日：2015-04-02
申请人： SNECMA
IPC分类号： F02K9/96 , G05B19/048 , G06N3/04
CPC分类号： F02K9/96 , F02K9/00 , F02K9/56 , F05D2220/80 , F05D2260/80 , F05D2260/81 , F05D2260/821 , F05D2270/301 , F05D2270/303 , F05D2270/304 , F05D2270/3061 , F05D2270/334 , F05D2270/44 , F05D2270/709 , G05B19/048 , G05B23/0221 , G05B23/0235 , G05B23/0254 , G05B2219/24015 , G05B2219/25255 , G06N3/0472
摘要： An obtaining step for obtaining a measurement of the monitored parameter as measured by a sensor and corresponding to an operating point of the engine, the operating point being defined by at least one regulation parameter of the engine; an estimation step for estimating a value of the monitored parameter for this operating point on the basis of a regulated value or a filtered setpoint value of the at least one regulation parameter of the engine defining the operating point; a comparison step for comparing an error between the measurement of the monitored parameter and its estimate relative to at least one threshold determined on the basis of an uncertainty on the error evaluated for the operating point; and a notification step for sending a notification in the event of the at least one threshold being crossed.
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公开(公告)号：US20020195821A1
公开(公告)日：2002-12-26
申请号：US10033826
申请日：2001-12-19
发明人： Joel Wacknov
IPC分类号： B61C009/38
CPC分类号： F01D15/10 , F02C7/08 , F02C9/28 , F05D2270/303 , F05D2270/709 , H02P9/48 , H02P2101/15
摘要： A power generation system is disclosed. In one embodiment, the power generation system includes a fuel source to provide fuel, a turbogenerator, coupled to the fuel source, to generate AC power, and a power controller electrically coupled to the turbogenerator. The power controller includes a first power converter to convert the AC power to DC power on a DC bus, and a second power converter to convert the DC power on the DC bus to an output power to supply a load. The power controller to regulate the fuel to the turbogenerator, independent of a DC voltage on the DC bus. A capacitor, such as an electrochemical capacitor or a hybrid capacitor, is coupled to the DC bus to source instantaneous power to and sink instantaneous power from the DC bus, due to load changes, to stabilize the DC voltage on the DC bus.
摘要翻译： 公开了发电系统。 在一个实施例中，发电系统包括用于提供燃料的燃料源，耦合到燃料源的涡轮发电机以产生AC电力，以及电耦合到涡轮发电机的功率控制器。 功率控制器包括：第一功率转换器，用于将AC功率转换为DC总线上的DC电力;以及第二功率转换器，用于将DC总线上的DC电力转换为输出功率以提供负载。 功率控制器调节燃料到涡轮发电机，独立于直流母线上的直流电压。 诸如电化学电容器或混合电容器的电容器被耦合到DC总线，以便由于负载变化而将瞬时功率从DC总线吸收并吸收，从而稳定DC总线上的DC电压。
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公开(公告)号：US20180268288A1
公开(公告)日：2018-09-20
申请号：US15458340
申请日：2017-03-14
CPC分类号： G07C5/0816 , F01D21/003 , F05D2260/80 , F05D2260/81 , F05D2270/20 , F05D2270/30 , F05D2270/709 , F05D2270/80 , G05B23/024 , G06N3/04 , G06N3/082 , G06N3/084
摘要： Systems and methods that include and/or leverage a neural network to approximate the steady-state performance of a turbine engine are provided. In one exemplary aspect, the neural network is trained to model a physics-based, steady-state cycle deck. When properly trained, novel input data can be input into the neural network, and as an output of the network, one or more performance indicators indicative of the steady-state performance of the turbine engine can be received. In another aspect, systems and methods for approximating the steady-state performance of a “virtual” or target turbine engine based at least in part on a reference neural network configured to approximate the steady-state performance of a “fielded” or reference turbine engine are provided.
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公开(公告)号：US20180258785A1
公开(公告)日：2018-09-13
申请号：US15454581
申请日：2017-03-09
CPC分类号： B64D27/10 , F01D11/24 , F05D2260/81 , F05D2260/821 , F05D2270/707 , F05D2270/708 , F05D2270/709 , F05D2270/71
摘要： Systems and methods for adjusting blade tip clearance targets and utilizing the adjusted targets to optimize the clearances between the blade tips and surrounding shrouds of a turbine engine are provided. In one exemplary aspect, one or more engine controllers utilize a machine-learned model to customize blade tip clearance targets based on the way an engine has been uniquely operated in the past for a particular flight mission. Present flight data associated with a present flight of a given flight mission is obtained. A model blade tip clearance target is adjusted based at least in part on the machine-learned model and the present flight data. The machine-learned model is trained at least in part on past flight data indicative of the manner in which the turbine engine has been operated for one or more past flights of the flight mission. An adjusted blade tip clearance target is then generated.
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6.发明授权Method for computer-aided control and/or regulation using two neural networks wherein the second neural network models a quality function and can be used to control a gas turbine 有权使用两个神经网络的计算机辅助控制和/或调节方法，其中所述第二神经网络建立质量函数并且可用于控制燃气轮机公开(公告)号：US08447706B2
公开(公告)日：2013-05-21
申请号：US12675555
申请日：2008-08-26
申请人： Daniel Schneegaβ , Steffen Udluft
发明人： Daniel Schneegaβ , Steffen Udluft
IPC分类号： G06F11/00
CPC分类号： G05B13/027 , F02C9/00 , F05D2270/707 , F05D2270/709 , G06N3/0454 , G06N3/08
摘要： A method for a computer-aided control of a technical system is provided. The method involves use of a cooperative learning method and artificial neural networks. In this context, feed-forward networks are linked to one another such that the architecture as a whole meets an optimality criterion. The network approximates the rewards observed to the expected rewards as an appraiser. In this way, exclusively observations which have actually been made are used in optimum fashion to determine a quality function. In the network, the optimum action in respect of the quality function is modeled by a neural network, the neural network supplying the optimum action selection rule for the given control problem. The method is specifically used to control a gas turbine.
摘要翻译： 提供了一种用于技术系统的计算机辅助控制的方法。 该方法涉及使用协作学习方法和人工神经网络。 在这种情况下，前馈网络彼此链接，使得整体架构满足最优性标准。 网络近似于作为评估者观察到的预期奖励的奖励。 以这种方式，实际上已经进行的专门观察以最佳方式被使用以确定质量函数。 在网络中，关于质量函数的最佳动作由神经网络建模，神经网络为给定的控制问题提供最佳动作选择规则。 该方法专门用于控制燃气轮机。
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公开(公告)号：US06639328B2
公开(公告)日：2003-10-28
申请号：US10033826
申请日：2001-12-19
申请人： Joel Wacknov
发明人： Joel Wacknov
IPC分类号： H02P900
CPC分类号： F01D15/10 , F02C7/08 , F02C9/28 , F05D2270/303 , F05D2270/709 , H02P9/48 , H02P2101/15
摘要： A power generation system is disclosed. In one embodiment, the power generation system includes a fuel source to provide fuel, a turbogenerator, coupled to the fuel source, to generate AC power, and a power controller electrically coupled to the turbogenerator. The power controller includes a first power converter to convert the AC power to DC power on a DC bus, and a second power converter to convert the DC power on the DC bus to an output power to supply a load. The power controller to regulate the fuel to the turbogenerator, independent of a DC voltage on the DC bus. A capacitor, such as an electrochemical capacitor or a hybrid capacitor, is coupled to the DC bus to source instantaneous power to and sink instantaneous power from the DC bus, due to load changes, to stabilize the DC voltage on the DC bus.
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8.发明授权公开(公告)号：US09472026B2
公开(公告)日：2016-10-18
申请号：US14183820
申请日：2014-02-19
申请人： SNECMA
CPC分类号： G07C5/00 , F01D19/02 , F01D21/06 , F01D25/04 , F05D2260/80 , F05D2260/81 , F05D2270/04 , F05D2270/709
摘要： A method of characterizing a turbine engine, the method comprising: steps of using measurements from an accelerometer monitoring a particular turbine engine while it is starting to detect the energy released by any contact during said starting between the rotor and the stator of the turbine engine, and of associating any such detection of contact with thermodynamic data measured on the particular turbine engine; and then a recognition training step, based on the associations, to enable a thermal context of the turbine engine to be used to recognize the presence of a rotor thermal unbalance to be taken into account in order to avoid contacts between the rotor and the stator on starting.
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公开(公告)号：US20160146119A1
公开(公告)日：2016-05-26
申请号：US15010258
申请日：2016-01-29
申请人： IHI Corporation
发明人： Hiroyuki FURUKAWA , Moe KINOSHITA
CPC分类号： F02C9/54 , F02C9/22 , F02C9/44 , F05D2270/20 , F05D2270/709 , G05B13/021 , G05B13/024
摘要： A gas turbine engine optimization control device estimates a specific fuel consumption using a given control parameter of a variable mechanism, determines a change between a specific fuel consumption estimation value by the control parameter of the variable mechanism in a previous operation period and a specific fuel consumption estimation value by the control parameter of the variable mechanism in this operation period, determines a new control parameter of the variable mechanism with which the specific fuel consumption estimation value approaches a minimum, adds the new control parameter of the variable mechanism to a preset control parameter initial value, and sets the addition value to be a control parameter command value of the variable mechanism in a next operation period.
摘要翻译： 燃气轮机发动机优化控制装置使用可变机构的给定控制参数来估计特定燃料消耗，通过前一操作时段中的可变机构的控制参数确定特定燃料消耗量估计值与特定燃料消耗之间的变化 通过该操作期间的可变机构的控制参数的估计值，确定特定燃料消耗量估计值接近最小值的可变机构的新控制参数，将可变机构的新控制参数与预设控制参数 初始值，并将加法值设定为下一个操作期间的可变机构的控制参数指令值。
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10.发明申请公开(公告)号：US20110153295A1
公开(公告)日：2011-06-23
申请号：US12643579
申请日：2009-12-21
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。
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