Method for detecting wear of a tyre containing a sonic wear gauge

• US 8,881,573 B2
• Filed: 12/01/2010
• Issued: 11/11/2014
• Est. Priority Date: 12/02/2009
• Status: Expired due to Fees

• Current Assignee: Compagnie générale des établissements Michelin, Michelin Recherche et Technique SA (Compagnie Generale DES Etablissements Michelin SCA)
• Original Assignee: Compagnie générale des établissements Michelin, Michelin Recherche et Technique SA (Compagnie Generale DES Etablissements Michelin SCA)
• Inventors: Mosnier, David, Paturle, Antoine
• Primary Examiner(s): Caputo, Lisa
• Assistant Examiner(s): Hernandez-Prewit, Roger
• Application Number:
  US13/513,005
• Publication Number:
  US 20120266649A1
• Time in Patent Office: 1,441 Days
• Field of Search: 73/8, 152/154.2, 701/31.5, 701/31.7, 702/34
• US Class Current: 73/8
• CPC Class Codes: B60C 11/24 Wear-indicating arrangements
• CPC Class Codes: B60C 11/246 Tread wear monitoring systems
• CPC Class Codes: Y10T 152/10027 with wear indicating feature

Abstract

A method for detecting wear of a tire involves at least one sonic wear gauge emitting an acoustic footprint noise that includes several acoustic footprint elementary frequency components. An acoustic signal that includes the acoustic footprint noise is acquired, with the acoustic signal including several elementary frequency components acquired in the frequency domain. Several series of elementary frequency components are enumerated, with each enumerated series forming some part of the acoustic footprint elementary frequency components. An acoustic footprint series is determined and, if a confidence index determined based on a local confidence index is greater or less than a predetermined threshold, an alert regarding the wear of the tire is emitted.

Claims

1. A method for detecting wear of a tyre, wherein the tyre includes at least one sonic wear gauge emitting, based on a predetermined radial wear threshold, an acoustic footprint noise that includes a plurality of acoustic footprint elementary frequency components, the method comprising steps of:

acquiring an acoustic signal that includes the acoustic footprint noise;

enumerating a plurality of series of elementary frequency components, each enumerated series of the enumerated plurality of series forming at least a part of the elementary frequency components of the acoustic signal;

selecting an acoustic footprint series from among the enumerated plurality of series, wherein the acoustic footprint series forms at least part of a Dirac comb;

determining a local confidence index of the acoustic footprint series; and

emitting a tyre wear alert, when a confidence index, which is determined based the local confidence index, is in absolute value at least one of greater than, less than, and equal to a predetermined threshold associated with the confidence index.

2. A method according to claim 1, wherein a plurality of sonic wear gauges are equi-distributed circumferentially in a tread of the tyre.

3. A method according to claim 1, wherein the tyre includes from 1 to 32 sonic wear gauges.

4. A method according to claim 1, wherein each of the at least one sonic wear gauge includes a sonic cavity structured so that:

beyond a predetermined radial wear threshold, the sonic cavity emerges radially to an exterior of the tyre,

the sonic cavity is closed by a ground in a substantially leak-tight manner as the sonic cavity passes across an area of contact of the tyre with the ground, and

a total volume of the sonic cavity or cavities is greater than or equal to 2 cm³.

5. A method according to claim 1, wherein the acquired acoustic signal is processed by implementing at least one of:

determining a frequency spectrum of the acquired acoustic signal;

isolating a frequency domain of the frequency spectrum of the acquired acoustic signal lying between 500 and 2500 Hz; and

isolating elementary frequency components of the frequency spectrum of the acquired acoustic signal exhibiting a level greater than a predetermined threshold.

6. A method according to claim 1, wherein a series of at least two elementary frequency components is selected, each elementary frequency component of the series being distant from at least one adjacent elementary frequency component of the series by a frequency gap lying in a predetermined reference frequency interval.

7. A method according to claim 6, wherein the predetermined reference frequency interval lies between 1 and 300 Hz.

8. A method according to claim 1, wherein, in the enumerating step,

pairs of elementary frequency components are enumerated, and,

for each pair of elementary frequency components, a frequency gap separating the elementary frequency components from one another is determined.

9. A method according to claim 8, wherein each frequency gap of each pair of elementary frequency components is classed in a frequency gap family defined by a family frequency gap interval.

10. A method according to claim 9, wherein, for each frequency gap family, all series of elementary frequency components that include at least two consecutive elementary frequency components separated by a serial frequency gap, lying in a corresponding family frequency gap interval, are enumerated.

11. A method according to claim 10, wherein, for each enumerated series of elementary frequency components:

a search is conducted for at least one elementary frequency component that is distant from one of the elementary frequency components of the enumerated series by a frequency gap that is a multiple of the corresponding family frequency gap interval, and

the enumerated series is supplemented with the elementary frequency component or components that are found in the search.

12. A method according to claim 10, wherein, for each frequency gap family, a serial index of each enumerated series is determined as a function of at least one first predetermined characteristic of the enumerated series.

13. A method according to claim 12, further comprising steps of:

for each frequency gap family, selecting a series by comparing each serial index of the enumerated series;

for each selected series, determining a family index of the selected series as a function of at least one second predetermined characteristic of the selected series; and

selecting the acoustic footprint series by comparing each family index of the selected series.

14. A method according to claim 13, wherein a relevance index of each second predetermined characteristic is determined, with each relevance index being defined by a variable function of sigmoid type of each second predetermined characteristic.

15. A method according to claim 14, wherein the local confidence index is determined based on the relevance index of each second predetermined characteristic.

16. A method according to claim 13, wherein each second predetermined characteristic includes at least one of:

a signal/noise frequency ratio,

a number of elementary frequency components in the selected series,

a dispersion of the frequency gap between the elementary frquency components of the selected series, and

a density of the elementary frequency components of the selected series.

17. A method according to claim 12, wherein the acoustic footprint series is selected by comparing each serial index of each selected series of each frequency gap family.

18. A method according to claim 12, wherein a relevance index of each first predetermined characteristic is determined, with each relevance index being defined by a variable function of sigmoid type of each first predetermined characteristic.

19. A method according to claim 18, wherein the local confidence index is determined based on the relevance index of each first predetermined characteristic.

20. A method according to Claim 12, wherein each first predetermined characteristic includes at least one of:

a signal/noise frequency ratio,

a number of elementary frequency components in the selected series,

a dispersion of the frequency gap between the elementary frequency components of the selected series, and

a density of the elementary frequency components of the selected series.

21. A method according to claim 8, wherein

each frequency gap of each pair of elementary frequency components is classed in a frequency gap family defined by a family frequency gap interval, and

each family frequency gap interval is determined as a function of a predetermined reference frequency interval and of a frequency resolution of a frequency spectrum of the acquired acoustic signal.

22. A method according to claim 1, further comprising steps of:

acquiring a plurality of temporally successive acoustic signals of the acoustic footprint noise, each of the acoustic signals including a plurality of elementary frequency components;

for each of the acoustic signals, selecting an acoustic footprint series, and determining a local confidence index of the selected acoustic footprint series; and

determining a global confidence index based on the local confidence indices of the selected acoustic footprint series,

wherein the emitting of the tyre wear alert occurs when the global confidence index is, in absolute value, at least one of greater than, less than, and equal to a predetermined threshold associated with the global confidence index.

23. A method according to claim 1, further comprising steps of:

acquiring a plurality of temporally successive acoustic signals of the acoustic footprint noise, each of the acoustic signals including a plurality of elementary frequency components;

for each of the acoustic signals, selecting an acoustic footprint series; and

for each selected acoustic footprint series, determining a global confidence index based on a temporal continuity between the elementary frequency components of the selected acoustic footprint series,

wherein the emitting of the tyre wear alert occurs when the global confidence index is, in absolute value, at least one of greater than, less than, and equal to a predetermined threshold associated with the global confidence index.

24. A method according to claim 1, wherein the method is performed by a computer executing a computer program that includes code instructions for implementing the steps of the method.

25. A non-transient computer-readable storage medium storing code instructions that, when executed by a computer, causes the computer to implement a method for detecting wear of a tyre, wherein the tyre includes at least one sonic wear gauge emitting, based on a predetermined radial wear threshold, an acoustic footprint noise that includes a plurality of acoustic footprint elementary frequency components, the method including steps of:

acquiring an acoustic signal that includes the acoustic footprint noise;

enumerating a plurality of series of elementary frequency components, each enumerated series of the enumerated plurality of series forming at least a part of the elementary frequency components of the acoustic signal;

selecting an acoustic footprint series from among the enumerated plurality of series, wherein the acoustic footprint series forms at least part of a Dirac comb;

determining a local confidence index of the acoustic footprint series; and

emitting a tyre wear alert, when a confidence index, which is determined based the local confidence index, is in absolute value at last one of greater than, less than, and equal to a predetermined threshold associated with the confidence index.

26. A method for providing tyre wear detection, the method comprising steps of:

storing code instructions on a non-transient computer-readable storage medium, wherein the code instructions, when executed by a computer, causes the computer to implement a wear-detection method for detecting wear of a tyre, wherein the tyre includes at least one sonic wear gauge emitting, based on a predetermined radial wear threshold, an acoustic footprint noise that includes a plurality of acoustic footprint elementary frequency components, the wear-detection method including steps of;

acquiring an acoustic signal that includes the acoustic footprint noise,

enumerating a plurality of series of elementary frequency components, each enumerated series of the enumerated plurality of series forming at least a part of the elementary frequency components of the acoustic signal,

selecting an acoustic footprint series from among the enumerated plurality of series, wherein the acoustic footprint series forms at least part of a Dirac comb,

determining a local confidence index of the acoustic footprint series, and

emitting a tyre wear alert, when a confidence index, which is determined based the local confidence index, is in absolute value at least one of greater than, less than, and equal to a predetermined threshold associated with the confidence index; and

enabling the code instructions to be accessed via a telecommunication network.