Patents by Inventor David C. Korim

David C. Korim has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • System and method for training anomaly detection analytics to automatically remove outlier data
    Patent number: 11703424
    Abstract: A method for detecting anomalies during operation of an asset to improve performance of the asset includes collecting, via a server, data relating to operation of the asset or a group of assets containing the asset. The data includes normal and abnormal asset behavior of the asset or the group of assets containing the asset. Further, the method includes automatically removing, via an iterative algorithm programmed in the server that utilizes one or more inputs or outputs of an anomaly detection analytic, portions of the data containing the abnormal asset behavior to form a dataset containing only the normal asset behavior. The method also includes training, via a computer-based model programmed in the server, the anomaly detection analytic using, at least, the dataset containing only the normal asset behavior. Moreover, the method includes applying, via the server, the anomaly detection analytic to the asset so as to monitor for anomalies during operation thereof.
    Type: Grant
    Filed: May 21, 2020
    Date of Patent: July 18, 2023
    Assignee: General Electric Company
    Inventors: Dayu Huang, Frederick Wilson Wheeler, John Joseph Mihok, David C. Korim
  • SYSTEM AND METHOD FOR TRAINING ANOMALY DETECTION ANALYTICS TO AUTOMATICALLY REMOVE OUTLIER DATA
    Publication number: 20210364392
    Abstract: A method for detecting anomalies during operation of an asset to improve performance of the asset includes collecting, via a server, data relating to operation of the asset or a group of assets containing the asset. The data includes normal and abnormal asset behavior of the asset or the group of assets containing the asset. Further, the method includes automatically removing, via an iterative algorithm programmed in the server that utilizes one or more inputs or outputs of an anomaly detection analytic, portions of the data containing the abnormal asset behavior to form a dataset containing only the normal asset behavior. The method also includes training, via a computer-based model programmed in the server, the anomaly detection analytic using, at least, the dataset containing only the normal asset behavior. Moreover, the method includes applying, via the server, the anomaly detection analytic to the asset so as to monitor for anomalies during operation thereof.
    Type: Application
    Filed: May 21, 2020
    Publication date: November 25, 2021
    Inventors: Dayu Huang, Frederick Wilson Wheeler, John Joseph Mihok, David C. Korim