Stephen R Hanson

US Patent:

55766323, Nov 19, 1996

Filed:

Jun 30, 1994

Appl. No.:

8/269466

Inventors:

Thomas Petsche - Neshanic Station NJ
Stephen J. Hanson - Princeton NJ

Assignee:

Siemens Corporate Research, Inc. - Princeton NJ

International Classification:

G06G 760
H02P 736

US Classification:

324772

Abstract:

A method for detecting a departure from normal operation of an electric motor comprises obtaining a set of normal current measurements for a motor being monitored; training a neural network auto-associator using the set of normal current measurements; making current measurements for the motor in operation; comparing the current measurements with the normal current measurements; and indicating abnormal operation whenever the current measurements deviate more than a predetermined amount from the normal current measurements. The method models a set of normal current measurements for the motor being monitored, and indicates a potential failure whenever measurements from the motor deviate significantly from a model. The model takes the form of an neural network auto-associator which is "trained"--using current measurements collected while the motor is known to be in a normal operating condition--to reproduce the inputs on the output. A new set of current measurements are classified as "good" or "bad" by first transforming the measurement using a Fast Fourier Transform (FFT) and an internal scaling procedure, and then applying a subset of the transformed measurements as inputs to the neural network auto-associator.