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US 2019/0103087 A1Published application
System for spectral shaping of vehicle noise cancellation
AssigneeGM Global Technology Operations LLC
InventorsFrank C. VALERI, Christopher A. STIRLEN, Timothy J. ROGGENKAMP
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Abstract
The present disclosure is directed to a system and a method for spectral shaping of vehicle noise cancellation. In an example implementation, the method includes determining a center frequency of an expected tonal peak within a selected noise band based upon vehicle data, generating a noise cancellation signal using a weighted shaping filter to shape the noise band, and outputting the noise cancellation signal to smooth the expected tonal peak.
Claims20
A vehicle noise shaping system, comprising:
- a tonal noise monitoring module that is configured to:
- determine a center frequency of an expected tonal peak within a selected noise band based upon vehicle data, and
- determine whether at least one of (1) a difference between a decibel value of the expected tonal peak within the selected noise band and a root mean square value of the selected noise band and (2) a ratio between the decibel value of the expected tonal peak within the selected noise band and the root mean square value of the selected noise band exceeds a predetermined threshold;
- a noise shaping module that is configured to use a weighted shaping filter to generate a noise cancellation signal when at the least one of the difference and the ratio exceeds the predetermined threshold to shape the noise band;
- and
- an audio output module that is configured to output the noise cancellation signal to smooth the expected tonal peak when the at least one of the difference and the ratio exceeds the predetermined threshold.
3 more elements
A system comprising:
- an active noise cancellation module that is configured to receive an environmental noise signal within a vehicle cabin and to generate a noise cancellation signal based upon the environmental noise signal;
- and
- a tonal noise cancellation module in communication with the active noise cancellation module, the tonal noise cancellation module including:
- a tonal noise monitoring module that is configured to:
- determine a center frequency of an expected tonal peak within a selected noise band based upon the environmental noise signal;
- determine whether at least one of (1) a difference between a decibel value of the expected tonal peak within the selected noise band and a root mean square value of the selected noise band and (2) a ratio between the decibel value of the expected tonal peak within the selected noise band and the root mean square value of the selected noise band exceeds a predetermined threshold;
- a noise shaping module that is configured to use a weighted shaping filter to generate the noise cancellation signal to shape the noise band when the at least one of the difference and the ratio exceeds the predetermined threshold to shape the noise band;
- and
- an audio output module that is configured to output the noise cancellation signal to smooth the expected tonal peak when the at least one of the difference and the ratio exceeds the predetermined threshold.
6 more elements
A method comprising:
- determining a center frequency of an expected tonal peak within a selected noise band based upon vehicle data;
- determining whether at least one of (1) a difference between a decibel value of the expected tonal peak within the selected noise band and a root mean square value of the selected noise band and (2) a ratio between the decibel value of the expected tonal peak within the selected noise band and the root mean square value of the selected noise band exceeds a redetermined threshold;
- generating a noise cancellation signal using a weighted shaping filter to shape the noise band when at least one of the difference and the ratio exceeds the predetermined threshold;
- and
- outputting the noise cancellation signal to smooth the expected tonal peak when the at east one of the difference and the ratio exceeds the predetermined threshold.
2 more elements
(canceled)
Dependencies are inferred from the claim text.