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    • 2. 发明申请
    • SYSTEMS AND METHODS FOR PROVIDING TEMPERATURE COMPENSATION IN STRUCTURAL HEALTH MONITORING
    • 在结构健康监测中提供温度补偿的系统和方法
    • US20120323517A1
    • 2012-12-20
    • US13163116
    • 2011-06-17
    • Lawrence E. Pado
    • Lawrence E. Pado
    • G06F19/00G06F17/18
    • G01N29/326G01M7/00G01N29/043G01N29/245G01N29/30G01N29/38G01N2291/0258
    • A method for compensating for environment induced variations in structural health monitoring data is described. The method includes imparting a vibration onto a structure first location, the structure at a first temperature, receiving a comparison signal resulting from the vibration at a second location, accessing data representing a reference signal previously received at the second location, based on vibration at the first location, the reference signal received when the structure was at a second temperature, dividing the signals across multiple time windows, performing a cross correlation between the signals in each window to maximally correlate the signals within each window, performing a weighted regression on time to estimate time shift, the weights based on reference signal energy in each window, to determine a relationship between time and time shift, and using the relationship between time and time shift of the comparison signal to reduce the effects of environment on the comparison signal.
    • 描述了用于补偿环境诱导的结构健康监测数据变化的方法。 所述方法包括:在结构第一位置上施加振动,所述结构在第一温度下,接收由第二位置处的振动产生的比较信号,基于所述第二位置处的振动访问表示先前在第二位置接收的参考信号的数据 第一位置,当结构处于第二温度时接收到的参考信号,在多个时间窗口之间划分信号,执行每个窗口中的信号之间的互相关,以使每个窗口内的信号最大程度地相关,对时间进行加权回归 估计时间偏移,基于每个窗口中的参考信号能量的权重,以确定时间和时间偏移之间的关系,并且使用比较信号的时间和时间偏移之间的关系来减少环境对比较信号的影响。
    • 4. 发明授权
    • Neural network predictive control method and system
    • 神经网络预测控制方法及系统
    • US06185470B2
    • 2001-02-06
    • US08966327
    • 1997-11-07
    • Lawrence E. PadoPeter F. Lichtenwalner
    • Lawrence E. PadoPeter F. Lichtenwalner
    • G06F1900
    • G05B13/027
    • A method and system for controlling a dynamic nonlinear plant. An input signal controls the plant and an output signal represents a state of the plant in response to the received input signal. A memory stores input and output signals corresponding to m consecutive past states of the plant. A computer neural network predicts a set of future output states representative of the output signal corresponding to the next n consecutive future states of the plant in response to a set of trial control inputs. The trial control inputs represent the input signal corresponding to the next n consecutive future states of the plant. The neural network predicts the future output states based on the past input and output signals and the future trial control inputs. A processor generates the trial control inputs and determines a performance index, indicative of plant performance over time in response to the trial control inputs, as a function of the future output states. The processor generates the input signal for controlling the plant and modifies it as a function of the trial control inputs so that the performance index reaches a desired value.
    • 一种用于控制动态非线性工厂的方法和系统。 输入信号控制设备,并且输出信号响应于所接收的输入信号表示设备的状态。 存储器存储对应于工厂的连续过去状态的输入和输出信号。 计算机神经网络响应于一组试验控制输入来预测表示对应于工厂的下一个n个连续未来状态的输出信号的一组未来输出状态。 试验控制输入表示对应于工厂的下一个n个连续未来状态的输入信号。 神经网络基于过去的输入和输出信号以及未来的试验控制输入来预测未来的输出状态。 处理器产生试验控制输入,并且根据未来的输出状态确定响应于试验控制输入指示工厂性能随时间变化的性能指标。 处理器产生用于控制设备的输入信号并根据试验控制输入进行修改,使得性能指标达到期望值。
    • 5. 发明授权
    • Systems and methods for providing temperature compensation in structural health monitoring
    • 在结构健康监测中提供温度补偿的系统和方法
    • US08892384B2
    • 2014-11-18
    • US13163116
    • 2011-06-17
    • Lawrence E. Pado
    • Lawrence E. Pado
    • G06F19/00G06F17/18G01N29/32G01N29/04G01N29/38G01N29/24G01M7/00G01N29/30
    • G01N29/326G01M7/00G01N29/043G01N29/245G01N29/30G01N29/38G01N2291/0258
    • A method for compensating for environment induced variations in structural health monitoring data is described. The method includes imparting a vibration onto a structure first location, the structure at a first temperature, receiving a comparison signal resulting from the vibration at a second location, accessing data representing a reference signal previously received at the second location, based on vibration at the first location, the reference signal received when the structure was at a second temperature, dividing the signals across multiple time windows, performing a cross correlation between the signals in each window to maximally correlate the signals within each window, performing a weighted regression on time to estimate time shift, the weights based on reference signal energy in each window, to determine a relationship between time and time shift, and using the relationship between time and time shift of the comparison signal to reduce the effects of environment on the comparison signal.
    • 描述了用于补偿环境诱导的结构健康监测数据变化的方法。 所述方法包括:在结构第一位置上施加振动,所述结构在第一温度下,接收由第二位置处的振动产生的比较信号,基于所述第二位置处的振动访问表示先前在第二位置接收的参考信号的数据 第一位置,当结构处于第二温度时接收到的参考信号,在多个时间窗口之间划分信号,执行每个窗口中的信号之间的互相关,以使每个窗口内的信号最大程度地相关,对时间进行加权回归 估计时间偏移,基于每个窗口中的参考信号能量的权重,以确定时间和时间偏移之间的关系,并且使用比较信号的时间和时间偏移之间的关系来减少环境对比较信号的影响。
    • 8. 发明授权
    • Method and apparatus for creating at least one parameter for algorithmically evaluating damage in a structure
    • 用于创建用于算法评估结构中的损伤的至少一个参数的方法和装置
    • US07734429B2
    • 2010-06-08
    • US11872335
    • 2007-10-15
    • Lawrence E. Pado
    • Lawrence E. Pado
    • G01B5/28
    • G05B23/0283G01N29/4481G01N29/50G01N2291/0289G01N2291/103G01N2291/2694
    • A method for creating at least one input parameter for an algorithmic system to evaluate damage in a structure may include: (a) Determining a plurality of damage index factors using first signal information relating to a first signal transmitted through the structure before the damage is imposed, and second signal information relating to a second signal transmitted through the structure after the damage is imposed. (b) determining a plurality of condensed damage index factors using the plurality of damage index factors. (c) Correlating selected of the condensed damage index factors with selected measured dimensions relating to the damage to determine a correlation index for selected combinations of the condensed damage index factors and the dimensions. (d) Selecting the at least one input parameter from among the selected condensed damage index factors having a correlation index meeting at least one predetermined criterion.
    • 一种用于为算法系统创建至少一个输入参数以评估结构中的损伤的方法可以包括:(a)使用与施加损伤之前通过结构传输的第一信号相关的第一信号信息来确定多个损伤指数因子 并且与施加了损坏之后通过结构传输的第二信号有关的第二信号信息。 (b)使用所述多个损伤指标因子确定多个冷凝损伤指数因子。 (c)将所选择的浓缩损失指数因子与与损害有关的所选测量尺寸相关,以确定冷凝损伤指数因子和尺寸的选定组合的相关指数。 (d)从具有满足至少一个预定标准的相关指数的所选择的缩合损伤指数因子中选择至少一个输入参数。
    • 10. 发明授权
    • Neural network predictive control cost function designer
    • 神经网络预测控制成本函数设计器
    • US07447664B2
    • 2008-11-04
    • US10653010
    • 2003-08-28
    • Lawrence E. Pado
    • Lawrence E. Pado
    • G06E1/00G06E3/00G06F15/18G06G7/00G06N3/02
    • G05B13/027Y10S706/906
    • A method, a computer-readable medium, and a system for tuning a cost function to control an operational plant are provided. A plurality of cost function parameters is selected. Predicted future states generated by the neural network model are selectively incorporated into the cost function, and an input weight is applied to a control input signal. A series of known signals are iteratively applied as control input inputs, and the cost output is calculated. A phase is taken of the control and plant outputs in response to each of the known signals and combined, thereby allowing effective combinations of the cost function parameters, the input weight, and the predicted future states to be identified.
    • 提供了一种方法,计算机可读介质和用于调整成本函数以控制可操作设备的系统。 选择多个成本函数参数。 由神经网络模型生成的预测未来状态被选择性地并入成本函数中,并且输入权重被应用于控制输入信号。 一系列已知信号被迭代地应用作为控制输入输入,并计算成本输出。 响应于每个已知信号采取控制和设备输出的相位并组合,从而允许要识别成本函数参数,输入权重和预测未来状态的有效组合。