公开(公告)号：US11314242B2

公开(公告)日：2022-04-26

申请号：US16743301

申请日：2020-01-15

Applicant: ExxonMobil Research and Engineering Company

Inventor： Weike Sun ,  Antonio R. Paiva ,  Peng Xu

IPC: G05B23/02

Abstract: An example method can comprise creating a non-linear neural network based model of a system based on historical operational data of the system and receiving first sensor data from a plurality of sensors associated with the system. Predicted next sensor data can be determined based on the received first sensor data and the non-linear network model. Second sensor data can be received from the plurality of sensors, and a measure of deviation between the predicted next sensor data and the received second sensor data is calculated. In response to the measured deviation exceeding a predefined threshold; it can be determined that a fault has occurred.

公开(公告)号：US20200241514A1

公开(公告)日：2020-07-30

申请号：US16743301

申请日：2020-01-15

Applicant: ExxonMobil Research and Engineering Company

Inventor： Weike Sun ,  Antonio R. Paiva ,  Peng Xu

IPC: G05B23/02

Abstract: An example method can comprise creating a non-linear neural network based model of a system based on historical operational data of the system and receiving first sensor data from a plurality of sensors associated with the system. Predicted next sensor data can be determined based on the received first sensor data and the non-linear network model. Second sensor data can be received from the plurality of sensors, and a measure of deviation between the predicted next sensor data and the received second sensor data is calculated. In response to the measured deviation exceeding a predefined threshold; it can be determined that a fault has occurred.