Patents by Inventor Athanasios SIGANOS

Athanasios SIGANOS 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).

  • Apparatus and computer implemented method in marine vessel data system for training neural network
    Patent number: 11492083
    Abstract: A computer implemented method and apparatus for a marine vessel data system, the method comprising: receiving data from at least one sensor configured to measure vibration and operationally arranged to the marine vessel to provide time-domain reference sensor data; maintaining the time-domain reference sensor data within a data storage system; generating a Fast Fourier Transform (FFT) on the time-domain reference sensor data to provide a plurality of reference spectra files in frequency-domain, wherein each reference spectra file comprises spectra data defined by amplitude information and frequency information, and each spectra file is associated with condition information determined based on collection of the time-domain reference sensor data; normalizing each reference spectra file by converting the frequency information to order information using the condition information to provide normalized reference spectra files; and training a convolutional autoencoder type of neural network using the normalized refe
    Type: Grant
    Filed: June 12, 2020
    Date of Patent: November 8, 2022
    Assignee: Wärtsilä Finland Oy
    Inventor: Athanasios Siganos
  • Apparatus and computer implemented method in marine vessel data system for generating anomaly heatmap information using neural network
    Patent number: 11341743
    Abstract: A computer implemented method and apparatus for a marine vessel data system, the method comprising: receiving data from at least one sensor configured to measure vibration and operationally arranged to the marine vessel to provide time-domain reference sensor data; maintaining the time-domain reference sensor data within a data storage system; generating a Fast Fourier Transform (FFT) on the time-domain reference sensor data to provide a plurality of reference spectra files in frequency-domain, wherein each reference spectra file comprises spectra data defined by amplitude information and frequency information, and each spectra file is associated with condition information determined based on collection of the time-domain reference sensor data; normalizing each reference spectra file by converting the frequency information to order information using the condition information to provide normalized reference spectra files; and training a convolutional autoencoder type of neural network using the normalized refe
    Type: Grant
    Filed: June 12, 2020
    Date of Patent: May 24, 2022
    Assignee: Wärtsilä Finland Oy
    Inventor: Athanasios Siganos
  • APPARATUS AND COMPUTER IMPLEMENTED METHOD IN MARINE VESSEL DATA SYSTEM FOR GENERATING ANOMALY HEATMAP INFORMATION USING NEURAL NETWORK
    Publication number: 20210390279
    Abstract: A computer implemented method and apparatus for a marine vessel data system, the method comprising: receiving data from at least one sensor configured to measure vibration and operationally arranged to the marine vessel to provide time-domain reference sensor data; maintaining the time-domain reference sensor data within a data storage system; generating a Fast Fourier Transform (FFT) on the time-domain reference sensor data to provide a plurality of reference spectra files in frequency-domain, wherein each reference spectra file comprises spectra data defined by amplitude information and frequency information, and each spectra file is associated with condition information determined based on collection of the time-domain reference sensor data; normalizing each reference spectra file by converting the frequency information to order information using the condition information to provide normalized reference spectra files; and training a convolutional autoencoder type of neural network using the normalized refe
    Type: Application
    Filed: June 12, 2020
    Publication date: December 16, 2021
    Applicant: Wärtsilä Finland Oy
    Inventor: Athanasios SIGANOS
  • APPARATUS AND COMPUTER IMPLEMENTED METHOD IN MARINE VESSEL DATA SYSTEM FOR TRAINING NEURAL NETWORK
    Publication number: 20210387706
    Abstract: A computer implemented method and apparatus for a marine vessel data system, the method comprising: receiving data from at least one sensor configured to measure vibration and operationally arranged to the marine vessel to provide time-domain reference sensor data; maintaining the time-domain reference sensor data within a data storage system; generating a Fast Fourier Transform (FFT) on the time-domain reference sensor data to provide a plurality of reference spectra files in frequency-domain, wherein each reference spectra file comprises spectra data defined by amplitude information and frequency information, and each spectra file is associated with condition information determined based on collection of the time-domain reference sensor data; normalizing each reference spectra file by converting the frequency information to order information using the condition information to provide normalized reference spectra files; and training a convolutional autoencoder type of neural network using the normalized refe
    Type: Application
    Filed: June 12, 2020
    Publication date: December 16, 2021
    Applicant: Wärtsilä Finland Oy
    Inventor: Athanasios SIGANOS