Multi-scale enveloping spectrogram signal processing for condition monitoring and the like
A signal processing technique that decomposes complex, dynamically changing non-stationary signals from machine components such as bearings into different scales by means of a continuous wavelet transform. The envelope signal in each scale is then calculated from the modulus of the wavelet coefficients. Subsequently, Fourier transform is performed repetitively on the envelope of the signal at each scale, resulting in an “envelope spectrum” of the original signal at the various scales. The final output is a three-dimensional scale-frequency map that indicates the intensity and location of the defect-related frequency lines. The technique is generic in nature, and applicable not only to machine condition monitoring, but also to the health monitoring of a wide range of dynamic systems, including human beings.
1. A method of signal processing, said method comprising the steps of:
(a) obtaining a signal from physical phenomena to monitor operation of an underlying system, wherein the signal is provided from a sensor monitoring a condition of the system, and the signal is indicative of the condition being monitored;
(b) processing the signal using a continuous wavelet transform at a plurality of different scales;
(c) extracting signal envelope for the processed signal for each scale;
(d) applying spectral analysis to the extracted envelopes to determine the frequency compositions thereof;
(e) generating a three-dimensional frequency map from the determined frequency compositions; and
(f) displaying the three-dimensional frequency map, whereby the signal provided by the sensor is transformed into a visual presentation that indicates the intensity and location of defect-induced or condition-induced frequencies that are indicative of the condition being monitored.
2. The method of claim 1 wherein the signal to be processed is obtained from a mechanical system.
3. The method of claim 2 wherein the signal to be processed is a vibration signal.
4. The method of claim 1 wherein the signal to be processed is obtained from a physiological signal.
5. The method of claim 1 wherein the continuous wavelet transform employs the complex Morlet wavelet.
6. The method of claim 1 wherein extracting the signal envelope includes determining a root sum square from real and imaginary parts of the processed signal for each scale.
7. The method of claim 1 wherein applying spectral analysis includes using a Fourier transform.
8. The method of claim 1 comprising displaying the three-dimensional frequency map in a plurality of different colors indicating different frequency energy levels.
9. A method of signal processing, said method comprising the steps of:
(a) obtaining a signal from physical phenomena to monitor operation of an underlying system, wherein the signal is provided from a sensor monitoring a condition of a machine and/or machine component or a condition in a physiological system and the signal is indicative of the condition being monitored;
(b) processing the signal using a continuous wavelet transform at a plurality of different scales;
(c) extracting signal envelope for the processed signal for each scale;
(d) applying spectral analysis to the extracted envelopes to determine the frequency compositions thereof;
(e) generating a three-dimensional frequency map from the determined frequency compositions; and
(f) displaying the three-dimensional frequency map, whereby the signal provided by the sensor is transformed into a visual presentation that indicates the intensity and location of defect-induced or condition-induced frequencies that are indicative of the condition being monitored.
10. The method of claim 9 wherein the signal to be processed is obtained from a mechanical system.
11. The method of claim 10 wherein the signal to be processed is a vibration signal.
12. The method of claim 9 wherein the signal to be processed is obtained from a physiological signal.
13. The method of claim 9 wherein the continuous wavelet transform employs the complex Morlet wavelet.
14. The method of claim 9 wherein extracting the signal envelope includes determining a root sum square from real and imaginary parts of the processed signal for each scale.
15. The method of claim 9 wherein applying spectral analysis includes using a Fourier transform.
16. The method of claim 9 wherein displaying the three-dimensional frequency map includes displaying the three-dimensional frequency map in a plurality of different colors indicating different frequency energy levels.
17. A system for processing a signal, said system comprising:
a sensor for obtaining a signal from physical phenomena to monitor operation of an underlying system, wherein the sensor is monitoring a condition of a machine and/or machine component or a condition in a physiological system, and the signal is indicative of the condition being monitored;
a processor adapted to receive the signal provided by the sensor,
an output display coupled to the processor;
the processor being programmed to:
(a) process the signal using a continuous wavelet transform at a plurality of different scales;
(b) extract signal envelopes for the processed signal for each scale;
(c) apply spectral analysis to the extracted envelopes to determine the frequency compositions thereof;
(d) generate a three-dimensional frequency map from the determined frequency compositions; and
(e) display the three-dimensional frequency map on the output display, whereby the signal provided by the sensor is transformed into a visual presentation that indicates the intensity and location of defect-induced or condition-induced frequencies that are indicative of the condition being monitored.
18. The system of claim 17 wherein the sensor is a vibration sensor.
19. The system of claim 17 wherein the sensor is a physiological signal sensor.
20. The system of claim 17 wherein the continuous wavelet transform employs the complex Morlet wavelet.
21. The system of claim 17 wherein extracting the signal envelope includes determining a root sum square from real and imaginary parts of the processed signal for each scale.
22. The system of claim 17 wherein applying spectral analysis includes using a Fourier transform.
23. The system of claim 17 wherein the processor is further programmed to generate and display the three-dimensional frequency map in a plurality of different colors indicating different frequency energy levels.