Patents by Inventor Sandesh J. Ghimire

Sandesh J. Ghimire 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 for determining most probable cause of a problem in a plant
    Patent number: 8209080
    Abstract: A system for determining a most probable cause or causes of a problem in a plant is disclosed. The system includes a plant, the plant having a plurality of subsystems that contribute to the operation of the plant, the plurality of subsystems having operating functions that produce operational signals. A plurality of sensors that are operable to detect the operational signals from the plurality of subsystems and transmit data related to the signals is also provided. An advisory system is disclosed that receives an input, the input being in the form of data from the plurality of sensors, possible input root causes of the problem, possible input symptoms of the problem and/or combinations thereof. The advisory system has an autoencoder in the form of a recurrent neural network.
    Type: Grant
    Filed: April 27, 2009
    Date of Patent: June 26, 2012
    Assignee: Toyota Motor Engineering & Manufacturing North America, Inc.
    Inventors: Danil V. Prokhorov, Setu Madhavi Namburu, Sandesh J. Ghimire, Liu Qiao
  • SYSTEM FOR DETERMINING MOST PROBABLE CAUSE OF A PROBLEM IN A PLANT
    Publication number: 20100274433
    Abstract: A system for determining a most probable cause or causes of a problem in a plant is disclosed. The system includes a plant, the plant having a plurality of subsystems that contribute to the operation of the plant, the plurality of subsystems having operating functions that produce operational signals. A plurality of sensors that are operable to detect the operational signals from the plurality of subsystems and transmit data related to the signals is also provided. An advisory system is disclosed that receives an input, the input being in the form of data from the plurality of sensors, possible input root causes of the problem, possible input symptoms of the problem and/or combinations thereof. The advisory system has an autoencoder in the form of a recurrent neural network.
    Type: Application
    Filed: April 27, 2009
    Publication date: October 28, 2010
    Applicant: Toyota Motor Engineering & Manufacturing North America, Inc.
    Inventors: Danil V. Prokhorov, Setu Madhavi Namburu, Sandesh J. Ghimire, Liu Qiao