Patents by Inventor Martin Gawecki

Martin Gawecki 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).

  • Gas turbine engine anomaly detections and fault identifications
    Patent number: 9818242
    Abstract: System and methods for detecting anomalies and identifying faults of a gas turbine engine may include a recorder in communication with a processor. The recorder may be configured to capture archival data of the gas turbine engine. A flight normalizer module may be configured to produce normalized results based on the archival data. A flight parameter features module may be configured to generate flight parameter features based on the normalized results. A data warehouse module may be configured to determine suspected fault classes by comparing the flight parameter features against training parameter features stored in the data warehouse module based on queries from the flight parameter features module. A majority vote module may be configured to determine a diagnosed fault class based on the suspected fault classes.
    Type: Grant
    Filed: November 6, 2015
    Date of Patent: November 14, 2017
    Assignees: UNIVERSITY OF SOUTHERN CALIFORNIA, INHA UNIVERSITY
    Inventors: Allan J. Volponi, Andrew F. Geib, Martin Gawecki, Chung Chieh Kuo, Wonik Choi
  • Gas Turbine Engine Anomaly Detections and Fault Identifications
    Publication number: 20160171796
    Abstract: System and methods for detecting anomalies and identifying faults of a gas turbine engine may include a recorder in communication with a processor. The recorder may be configured to capture archival data of the gas turbine engine. A flight normalizer module may be configured to produce normalized results based on the archival data. A flight parameter features module may be configured to generate flight parameter features based on the normalized results. A data warehouse module may be configured to determine suspected fault classes by comparing the flight parameter features against training parameter features stored in the data warehouse module based on queries from the flight parameter features module. A majority vote module may be configured to determine a diagnosed fault class based on the suspected fault classes.
    Type: Application
    Filed: November 6, 2015
    Publication date: June 16, 2016
    Inventors: Allan J. Volponi, Andrew F. Geib, Martin Gawecki, Chung Chieh Kuo, Wonik Choi
  • MFCC and CELP to detect turbine engine faults
    Patent number: 8655571
    Abstract: A fault detection and diagnosis method for a gas turbine engines comprises collecting a sensor signal from an acoustic or vibrational sensor at the gas turbine engine, pre-processing the sensor signal to remove predictable background, and extracting a feature set from the sensor signal using Mel-Frequency Cepstral Coefficients (MFCC) algorithms and/or Code Excited Linear Prediction (CELP) algorithms. Fault and non-fault states are reported based on comparison between the feature set and a library of fault and non-fault feature profiles corresponding to fault and non-fault states of the gas turbine engine.
    Type: Grant
    Filed: June 23, 2011
    Date of Patent: February 18, 2014
    Assignee: United Technologies Corporation
    Inventors: Andrew F. Geib, Chung Chieh Kuo, Martin Gawecki, EnShuo Tsau, Je Won Kang, Paul Raymond Scheid
  • MFCC AND CELP TO DETECT TURBINE ENGINE FAULTS
    Publication number: 20120330495
    Abstract: A fault detection and diagnosis method for a gas turbine engines comprises collecting a sensor signal from an acoustic or vibrational sensor at the gas turbine engine, pre-processing the sensor signal to remove predictable background, and extracting a feature set from the sensor signal using Mel-Frequency Cepstral Coefficients (MFCC) algorithms and/or Code Excited Linear Prediction (CELP) algorithms. Fault and non-fault states are reported based on comparison between the feature set and a library of fault and non-fault feature profiles corresponding to fault and non-fault states of the gas turbine engine.
    Type: Application
    Filed: June 23, 2011
    Publication date: December 27, 2012
    Applicant: UNITED TECHNOLOGIES CORPORATION
    Inventors: Andrew F. Geib, Chung Chieh Kuo, Martin Gawecki, EnShuo Tsau, Je Won Kang, Paul Raymond Scheid