Patents by Inventor Ercan Mehment Dede

Ercan Mehment Dede 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).

  • Distributed architecture for fault monitoring
    Patent number: 11113168
    Abstract: Systems and methods for detecting an anomaly in a power semiconductor device are disclosed. A system includes a server computing device and one or more local components communicatively coupled to the server computing device. Each local component includes sensors positioned adjacent to the power semiconductor device for sensing properties thereof. Each local component receives data corresponding to one or more sensed properties of the power semiconductor device from the sensors and transmits the data to the server computing device. The server computing device utilizes the data, via a machine learning algorithm, to generate a set of eigenvalues and associated eigenvectors and select a selected set of eigenvalues and associated eigenvectors. Each local component conducts a statistical analysis of the selected set of eigenvalues and associated eigenvectors to determine that the data is indicative of the anomaly.
    Type: Grant
    Filed: March 9, 2018
    Date of Patent: September 7, 2021
    Assignees: Toyota Motor Engineering & Manufacturing North America, Inc., University of Connecticut
    Inventors: Ercan Mehment Dede, Shailesh N. Joshi, Lingyi Zhang, Weiqiang Chen, Krishna Pattipatti, Ali M. Bazzi
  • Distributed Architecture for Fault Monitoring
    Publication number: 20190278684
    Abstract: Systems and methods for detecting an anomaly in a power semiconductor device are disclosed. A system includes a server computing device and one or more local components communicatively coupled to the server computing device. Each local component includes sensors positioned adjacent to the power semiconductor device for sensing properties thereof Each local component receives data corresponding to one or more sensed properties of the power semiconductor device from the sensors and transmits the data to the server computing device. The server computing device utilizes the data, via a machine learning algorithm, to generate a set of eigenvalues and associated eigenvectors and select a selected set of eigenvalues and associated eigenvectors. Each local component conducts a statistical analysis of the selected set of eigenvalues and associated eigenvectors to determine that the data is indicative of the anomaly.
    Type: Application
    Filed: March 9, 2018
    Publication date: September 12, 2019
    Inventors: Ercan Mehment Dede, Shailesh N. Joshi, Lingyi Zhang, Weiqiang Chen, Krishna Pattipatti, Ali M. Bazzi