会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 2. 发明授权
    • Method for analysis of the operation of a gas turbine
    • 燃气轮机运行分析方法
    • US08396689B2
    • 2013-03-12
    • US12739782
    • 2008-09-19
    • Uwe PfeiferVolkmar Sterzing
    • Uwe PfeiferVolkmar Sterzing
    • G06F19/00
    • G05B23/024
    • A method for analyzing the operation of a gas turbine is provided. A neural network based upon a normal operation of the gas turbine is learned. A dynamic pressure signal is read by a pressure sensor in or on the compressor of the turbine, and an operating parameter is read by a further sensor. The dynamic pressure signal is subjected to a frequency analysis, a parameter of a frequency spectrum of the pressure signal being determined. Based upon the measured operating parameter and the parameter of the frequency spectrum of the pressure signal, the neural network is learned. The measured operating parameter and the parameter of the frequency spectrum are input parameters, and a diagnostic characteristic value representing a probability of a presence of normal operation of the gas turbine as a function of the input parameters is output.
    • 提供了一种用于分析燃气轮机的操作的方法。 了解到基于燃气轮机正常运行的神经网络。 动态压力信号由涡轮压缩机中或压缩机上的压力传感器读取,并且另一传感器读取操作参数。 对动态压力信号进行频率分析,确定压力信号的频谱的参数。 基于测量的操作参数和压力信号的频谱参数,学习神经网络。 测量的操作参数和频谱的参数是输入参数,并且输出表示作为输入参数的函数的燃气轮机的正常操作的概率的诊断特征值。
    • 4. 发明申请
    • Method for computer-aided control or regualtion of a technical system
    • 计算机辅助控制或技术系统规范的方法
    • US20090271344A1
    • 2009-10-29
    • US12386639
    • 2009-04-21
    • Anton Maximillian SchaferVolkmar SterzingSteffen Udluft
    • Anton Maximillian SchaferVolkmar SterzingSteffen Udluft
    • G06N3/08
    • G05B13/027
    • A method for computer-aided control of any technical system is provided. The method includes two steps, the learning of the dynamic with historical data based on a recurrent neural network and a subsequent learning of an optimal regulation by coupling the recurrent neural network to a further neural network. The recurrent neural network has a hidden layer comprising a first and a second hidden state at a respective time point. The first hidden state is coupled to the second hidden state using a matrix to be learned. This allows a bottleneck structure to be created, in that the dimension of the first hidden state is smaller than the dimension of the second hidden state or vice versa. The autonomous dynamic is taken into account during the learning of the network, thereby improving the approximation capacity of the network. The technical system includes a gas turbine.
    • 提供了一种用于任何技术系统的计算机辅助控制的方法。 该方法包括两个步骤:基于循环神经网络学习具有历史数据的动态,以及通过将再循环神经网络耦合到另一神经网络来进一步学习最佳调节。 循环神经网络具有在相应时间点包括第一和第二隐藏状态的隐藏层。 使用要学习的矩阵将第一隐藏状态耦合到第二隐藏状态。 这允许创建瓶颈结构,因为第一隐藏状态的维度小于第二隐藏状态的维度,反之亦然。 在网络学习期间考虑自主动态,从而提高网络的近似能力。 技术系统包括燃气轮机。