General Electric Company

Ramesh Ramachandran

Piero Patrone Bonissone

Yu-To Chen

Rasiklal Punjalal Shah

Vipin Kewal Ramani

Phillip Edward Steen

John Andrew Johnson

A system and method for diagnosing and validating a machine with waveform data generated therefrom. Historical waveform data are obtained from machines having known faults along with corresponding actions for repairing the machines and are used to develop fault classification rules. The fault classification rules are stored in a diagnostic knowledge database. The database of classification rules are used to diagnose new waveform data from a machine having an unknown fault.

System and method for diagnosing and validating a machine using waveform data

A diagnostic system is provided for identifying faults in a machine (e.g., CT scanner, MRI system, x-ray apparatus) by analyzing a data file generated thereby. The diagnostic system includes a trained database containing a plurality of trained data, each trained data associated with one of plurality of known fault types. Each trained data is represented by a trained set of feature values and corresponding weight values. Once a data file is generated by the machine, a current set of feature values are extracted from the data file by performing various analyses (e.g., time domain analysis, frequency domain analysis, wavelet analysis). The current set of feature values extracted is analyzed by a fault detector which produces a candidate set of faults based on the trained set of feature values and corresponding weight values for each of the fault types. The candidate set of faults produced by the fault detector is presented to a user along with a recommend repair procedure. In cases where no fault is identified or in response to a misdiagnosis produced by the diagnostic system, the user may interactively input a faulty condition associated with the machine being diagnosed (e.g., based on his/her experience). The diagnostic system further includes a learning subsystem which automatically updates the plurality of trained data based on the faulty condition input by the user.

Diagnostic system with learning capabilities

The present invention discloses a system and method for diagnosing and validating a machine with waveform data generated therefrom. In this invention, historical waveform data are obtained from machines having known faults along with corresponding actions for repairing the machines and are used to develop fault classification rules. The fault classification rules are stored in a diagnostic knowledge database. The database of classification rules are used to diagnose new waveform data from a machine having an unknown fault.

Growing community of inventors

Niskayuna, NY, United States of America

Ramesh Ramachandran