PARAMETER INDEPENDENT DETECTION OF ROTATING MACHINERY FAULTS

• US 20100139403A1
• Filed: 12/04/2009
• Published: 06/10/2010
• Est. Priority Date: 12/04/2008
• Status: Active Grant

• Current Assignee: University of Ottawa
• Original Assignee: University of Ottawa
• Inventors: BOZCHALOOI, Iman Soltani, LIANG, Ming
• Granted Patent: US 8,544,331 B2
• Time in Patent Office: Days
• US Class Current: 73/587
• CPC Class Codes: G01N 2291/2696 Wheels, Gears, Bearings
• CPC Class Codes: G01N 29/14 using acoustic emission techniques echo of particles G01N29/046; measuring mechanical vibrations or acoustic waves in solids in general G01H1/00
• CPC Class Codes: G01N 29/4454 Signal recognition, e.g. specific values or portions, signal events, signatures
• CPC Class Codes: G01N 29/46 by spectral analysis, e.g. Fourier analysis or wavelet analysis spectral signal processing per se G06F17/14

Abstract

A parameter-free method to analyze sensor signals incorporates two or more of frequency demodulation, amplitude demodulation and phase demodulation of the raw signal data. The resulting signal is transformed to a frequency domain, and target fault characteristics from the demodulated signal are identified. The method is used to detect faults in bearings, gears and other mechanical components.

Claims

1. A method for detecting the existence of a mechanical component fault from a raw data source signal comprising a target fault characteristic signal, one or more interference signals and intrinsic noise signals, said target fault characteristic signal featuring periodically occurring frequency, phase and amplitude modulations, said method comprising:

a) transforming said raw data source signal using one or more transformations which incorporate any combination of two or more of frequency, phase and amplitude demodulations of said raw data source signal;

b) transforming said signal obtained in step a) to a frequency domain; and

c) identifying a target fault characteristic signature which corresponds to said target fault characteristic signal.

2. The method as defined in claim 1 wherein said one or more interference signals have a frequency range which is lower than that of said target fault characteristic signal.

3. The method as defined in claim 1 further comprising the step of removing said intrinsic noise signals from said raw data source signal prior to step a).

4. The method as defined in claim 3 wherein the removal of said intrinsic noise signals is performed by a thresholding noise reduction or removal technique.

5. The method as defined in claim 1 wherein said step a) uses a Teager Energy Operator.

6. The method as defined in claim 1 wherein said raw data source signal is obtained from an acoustic or vibration sensor for measuring an acoustic signal or vibrations of a mechanical system.

7. The method as defined in claim 6 wherein said vibration sensor is an accelerometer or laser vibrometer.

8. The method as defined in claim 6 wherein said acoustic sensor is an acoustic emission sensor or a microphone.

9. The method as defined in claim 1 wherein said mechanical component is chosen from the group consisting of one or more bearings, gears, journal bearings, slider cranks, cams, shafts, springs, wheels, fans, turbines, rotors, disks, impellers, propellers and dampers.

10. The continuous use of the method as defined in claim 1 to monitor conditions of a mechanical system comprising one or more mechanical components.

11. The continuous use of the method as defined in claim 3 to monitor conditions of a mechanical system comprising one or more mechanical components.

12. The continuous use of the method as defined in claim 5 to monitor conditions of a mechanical system comprising one or more mechanical components.