Isolation, extraction and evaluation of transient distortions from a composite signal

Patent metadata

Field	Value
Publication number	US-9668074-B2
Application number	US-201414450071-A
Country	US
Kind code	B2
Filing date	Aug 1, 2014
Priority date	Aug 1, 2014
Publication date	May 30, 2017
Grant date	May 30, 2017

Abstract

A method for processing a time-domain signal with transient oscillations includes: performing, by one or more computer systems, a time-frequency representation transform on the time-domain signal to obtain a plurality of coefficients for, with a coefficient corresponding to a presence of an impulse response of a filter used by the time-frequency representation transform; selecting one or more of the coefficients, with the selected one or more of the coefficients having attributes that are more indicative of the transient oscillations; and reconstructing, based on performing an inverse transform on the selected one or more coefficients, a portion of the time-domain signal that represents the transient oscillations.

First claim

What is claimed is:

1. A method for processing a time-domain signal with transient oscillations, the method comprising:
performing, by one or more computer systems, a time-frequency representation transform on the time-domain signal to obtain a plurality of coefficients, with a coefficient corresponding to a presence of an impulse response of a filter used by the time-frequency representation transform;
selecting one or more of the coefficients, with the selected one or more of the coefficients having attributes that are associated with the transient oscillations and excluding one or more of the coefficients having attributes that are unassociated with the transient oscillations; and
reconstructing, based on performing an inverse transform on the selected one or more coefficients, a portion of the time-domain signal that represents the transient oscillations.

2. The method of claim 1 , wherein the impulse response is represented by a model transient waveform.

3. The method of claim 2 , wherein the attributes of the selected one or more coefficients represent a similarity of the model transient waveform to the transient oscillations in the time-domain signal.

4. The method of claim 1 , wherein the time-frequency representation transform is a discrete wavelet transform.

5. The method of claim 1 , wherein the transient oscillations are associated with coefficients with frequency bands above a threshold frequency band, and wherein selecting comprises:
removing one or more of the obtained coefficients with one or more frequency bands below the threshold frequency band to remove coefficients that are unassociated with the transient oscillations;
wherein selecting comprises selecting from remaining ones of the obtained coefficients.

6. The method of claim 1 , further comprising:
performing segmentation in time on the remaining ones of the coefficients, with segmentation in time for a coefficient dividing the coefficient into one or more portions indicative of a characteristic of the coefficient.

7. The method of claim 6 , wherein the segmentation is a Kurtosis-based segmentation that is based on one or more sliding Kurtosis windows in time, and wherein the method further comprises:
for a remaining coefficient, determining a maximum Kurtosis value of a Kurtosis-based segmentation for the remaining coefficient;
for maximum Kurtosis values of the remaining coefficients, determining a ratio of (i) a highest maximum Kurtosis value, to (ii) a lowest maximum Kurtosis value;
wherein selecting comprises selecting the coefficient, when the maximum coefficient value exceeds a maximum coefficient threshold and the ratio exceeds a ratio threshold.

8. The method of claim 6 , wherein the segmentation is a Kurtosis-based segmentation that is based on one or more sliding Kurtosis windows, and wherein the method further comprises:
correlating a resulting Kurtosis sliding window result against an expected model result for a particular stimulus frequency;
wherein the selected one or more coefficients are based on correlations among the Kurtosis sliding window results and expected models.

9. A method for detecting transient oscillations in a response signal from a device under test, the method comprising:
performing a transform on the response signal;
reconstructing, by one or more computer systems, a time-domain signal that represents the transient oscillations of the response signal, with reconstruction being based on the transform;
executing a time-varying psychoacoustic model, with the reconstructed time-domain signal being an input to the time-varying psychoacoustic model;
obtaining, based on executing, a value indicative of an attribute for at least a portion of the transient oscillations;
comparing the obtained value to a threshold value; and
determining, based on comparing, a pass state or a fail state for the device under test.

10. The method of claim 9 , wherein the device under test is an acoustic transducer, and wherein the transient oscillations are indicative of rub and buzz distortions in the acoustic transducer, wherein a rub and buzz distortion comprises a non-linear sound distortion.

11. The method of claim 9 , further comprising:
identifying a relative time location in the reconstructed time-domain signal in which specified features occur, based on a cycle-by-cycle analysis of the reconstructed time-domain signal, with respect cycles of an original stimulus waveform.

12. The method of claim 11 , wherein the specified features comprise the transient oscillations or modulated noise.

13. The method of claim 9 , wherein the transform provides a time-frequency representation of the time-domain signal.

14. The method of claim 9 , wherein a stimulus is transmitted to the device under test in a plurality of stimulus cycles, wherein the transform provides a time-frequency representation of the time-domain signal, and wherein reconstructing comprises:
reconstructing, in the time-domain for the plurality of stimulus cycles, the time-domain signal, with reconstructing based on the time-frequency representation;
wherein the reconstructed time-domain signal comprises portions, with each portion associated with one of the stimulus cycles; and
wherein the method further comprises:
for a particular stimulus cycle, identifying a time location, relative to the particular stimulus cycle, of features included in a portion of the reconstructed time-domain signal by identifying a location in time of the features included in the portion of the reconstructed time-domain signal that is associated with the particular stimulus cycle; and

determining a failure type of the device under test based on time locations, relative to the stimulus cycles, of the features in the reconstructed time-domain signal.

15. The method of claim 14 , wherein the time locations, relative to the stimulus cycles, of the features are substantially the same among the stimulus cycles, and wherein the failure type comprises one or more of:
voice coil rubbing resulting only from a misaligned voice coil in the device under test;
voice coil bottoming in the device under test; and
an air leak in the device under test.

16. The method of claim 14 , wherein the time locations, relative to the stimulus cycles, of the features vary among the stimulus cycles of different frequencies, and wherein the failure type comprises one or more of:
voice coil wire buzzing in the device under test; and
voice coil rubbing resulting from uneven cone mass distribution in the device under test.

17. The method of claim 14 , wherein the time locations, relative to the stimulus cycles, of the features vary among the stimulus cycles of same and different frequencies and for different applications of the same stimulus frequency, and wherein the failure type comprises: audio distortions from a trapped foreign object in the device under test.

18. The method of claim 9 , further comprising:
removing noise from the reconstructed time-domain signal, prior to executing the time-varying psychoacoustic model, to promote the obtained value being based primarily on the transient oscillations and not based on noise.

19. The method of claim 9 , further comprising:
measuring a magnitude and a phase of a voltage across and a current into the device under test, when a stimulus signal is fed to the device under test;
estimating a voice coil temperature in real time, at least partly based on the voltage across the device under test, the current into the device under test, a metal type of a voice coil in

Assignees

• Litepoint Corp

Inventors

• Drullinger Todd
• Smedegaard Michael
• Chao Rick
• Pedersen Soren Louis

Classifications

• H04R29/00

  Monitoring arrangements; Testing arrangements {(for hearing aids H04R25/30; detection of loudspeaker connection H04R5/04; sound-field adaptation dependent on speaker detection H04S7/308)} · CPC title

• H04R29/001 Primary

  for loudspeakers (H04R29/007 takes precedence) · CPC title