公开(公告)号：US20090300417A1

公开(公告)日：2009-12-03

申请号：US12129632

申请日：2008-05-29

Applicant: Piero Patrone Bonissone ,  John Erik Hershey ,  Robert James Mitchell, JR. ,  Rajesh Venkat Subbu, JR. ,  Avinash Vinayak Taware ,  Xiao Hu

Inventor： Piero Patrone Bonissone ,  John Erik Hershey ,  Robert James Mitchell, JR. ,  Rajesh Venkat Subbu, JR. ,  Avinash Vinayak Taware ,  Xiao Hu

IPC: G06F11/28

CPC classification number: G05B23/0254 ,  G05B2219/33295 ,  G05B2219/33296 ,  G07C3/00

Abstract: A method for advanced condition monitoring of an asset system includes using a plurality of auto-associative neural networks to determine estimates of actual values sensed by at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; and combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; and determining a change of the operation of the asset system by analysis of the combined residuals. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract translation: 一种用于资产系统的高级状态监测的方法包括使用多个自动关联神经网络来确定至少一个传感器在所述多个操作方案中的至少一个中感测到的实际值的估计; 从所述多个自相关神经网络中的每一个确定估计的感测值与由所述至少一个传感器感测的实际值之间的残差; 并通过使用模糊监督模型混合器组合残差; 对组合残差进行故障诊断; 以及通过分析组合残差来确定资产系统的操作变化。 必要时提供警报。 智能传感器系统包括用于执行本发明的方法的车载处理单元。

公开(公告)号：US07756678B2

公开(公告)日：2010-07-13

申请号：US12129632

申请日：2008-05-29

Applicant: Piero Patrone Bonissone ,  John Erik Hershey ,  Robert James Mitchell, Jr. ,  Rajesh Venkat Subbu, Jr. ,  Avinash Vinayak Taware ,  Xiao Hu

Inventor： Piero Patrone Bonissone ,  John Erik Hershey ,  Robert James Mitchell, Jr. ,  Rajesh Venkat Subbu, Jr. ,  Avinash Vinayak Taware ,  Xiao Hu

IPC: G06F11/28

CPC classification number: G05B23/0254 ,  G05B2219/33295 ,  G05B2219/33296 ,  G07C3/00

Abstract: A method for advanced condition monitoring of an asset system includes using a plurality of auto-associative neural networks to determine estimates of actual values sensed by at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; and combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; and determining a change of the operation of the asset system by analysis of the combined residuals. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention.

Abstract translation: 一种用于资产系统的高级状态监测的方法包括使用多个自动关联神经网络来确定至少一个传感器在所述多个操作方案中的至少一个中感测到的实际值的估计; 从所述多个自相关神经网络中的每一个确定估计的感测值与由所述至少一个传感器感测的实际值之间的残差; 并通过使用模糊监督模型混合器组合残差; 对组合残差进行故障诊断; 以及通过分析组合残差来确定资产系统的操作变化。 必要时提供警报。 智能传感器系统包括用于执行本发明的方法的车载处理单元。