Method and arrangement for processing noise signal from a noise source

• US 20040081322A1
• Filed: 12/01/2003
• Published: 04/29/2004
• Est. Priority Date: 12/22/2000
• Status: Abandoned Application

• Current Assignee: Daimler AG (Mercedes-Benz Group AG)
• Original Assignee: Daimler AG (Mercedes-Benz Group AG)
• Inventors: Schliep, Michael, Törgyekes, Szaboles, White, Rolf, Zipp, Walter
• Application Number:
  US10/451,415
• Publication Number:
  US 20040081322A1
• Time in Patent Office: Days
• US Class Current: 381/57
• CPC Class Codes: G08G 1/015 with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors

Abstract

For locating, identifying and classifying noise sources inside and outside spaces, the invention provides a method for processing noise signals of a noise source, in which a plurality of noise signals (SQ1 to SQ4) are detected in a location-related manner and examined by means of a sound analysis on the basis of signal features in such a way that parameters underlying the noise source (G1 to G4) are determined.

Claims

1. A method for processing noise signals (SQ1 to SQ4) of a noise source (G1 to G4),

characterized in that a plurality of noise signals (SQ1 to SQ4) are detected in a location-related manner and examined by means of a sound analysis on the basis of signal features and parameters underlying the noise source (G1 to G4) are determined.

2. The method as claimed in claim 1,

characterized in that the amplitude, frequency and/or phase of the noise signal (SQ1 to SQ4) is determined as signal features of said noise signal.

3. The method as claimed in claim 1 or 2,

characterized in that the sound analysis is performed on the basis of a time, frequency and/or level analysis.

4. The method as claimed in one of claims 1 to 3,

characterized in that the type, position and/or state of the noise source (G1 to G4) is determined as parameters of said noise source.

5. The method-as claimed in one of claims 1 to 4,

characterized in that the sound analysis is performed in the event of a noise limit value being exceeded.

6. The method as claimed in claim 5,

characterized in that the sound analysis performed on account of a noise limit value being exceeded is used [lacuna] a trigger for maintaining a temporary ring memory.

7. The method as claimed in one of claims 1 to 6,

characterized in that at least one of the signal features of the noise signal (SQ1 to SQ4) is stored in the form of a noise pattern (SM1 to SM4).

8. The method as claimed in one of claims 1 to 7,

characterized in that at least one of the signal features of the noise signal (SQ1 to SQ4) is compared with stored noise patterns (SM_a to SM_z) for the determination and assignment of parameters of the underlying noise source (G1 to G4).

9. The method as claimed in one of claims 1 to 8,

characterized in that external data, in particular meteorological data, optical data, time data, operating parameters, are taken into account.

10. The method as claimed in one of claims 1 to 9,

characterized in that a self-learning system is used for the determination and classification of the signal features of the noise signal (SQ1 to SQ4) and/or the parameters of the noise source (G1 to G4).

11. The method as claimed in one of claims 1 to 10,

characterized in that the signal features and/or the parameters are fed to an open-loop and/or a closed-loop control system.

12. An arrangement (1) for processing noise signals (SQ1 to SQ4) of a noise source (G1 to G4),

characterized in that provision is made of a plurality of noise sensors (M1 to M7) for the location-related detection of noise signals (SQ1 to SQ4) and a central data processing unit (12) for the sound analysis of the noise signals (SQ1 to SQ4) on the basis of at least one signal feature and for the determination of at least one parameter characterizing the noise source (G1 to G4).

13. The arrangement as claimed in claim 12,

characterized in that directional microphones are provided as noise sensors (M1 to M7).

14. The arrangement as claimed in claim 12 or 13,

characterized in that a means for determining amplitude, frequency and/or phase of the noise signal (SQ1 to SQ4) is provided.

15. The arrangement as claimed in one of claims 12 to 14,

characterized in that a means for determining type, position and/or state of the noise source (G1 to G4) is provided.

16. The arrangement as claimed in one of claims 12 to 15,

characterized in that a means for monitoring a noise limit value is provided.

17. The arrangement as claimed in one of claims 12 to 16,

characterized in that a data memory for storing at least one of the signal features of the noise signal (SQ1 to SQ4) in the form of a noise pattern (SM1 to SM4) is provided.

18. The arrangement as claimed in one of claims 12 to 17,

characterized in that a database comprising a noise pattern library is provided.

19. The arrangement as claimed in one of claims 12 to 18,

characterized in that provision is made of a means for comparing at least one of the signal features of the noise signal (SQ1 to SQ4) with stored noise patterns (SM_a to SM_z) for the determination and assignment of parameters of the underlying noise source (G1 to G4).

20. The arrangement as claimed in one of claims 12 to 19,

characterized in that an optical system for detecting optical data is provided.

21. The method as claimed in one of claims 12 to 20,

characterized in that a recording unit for detecting meteorological data is provided.

22. The arrangement as claimed in one of claims 12 to 21,

characterized in that provision is made of a means for determining and classifying the signal features of the noise signal (SQ1 to SQ4) and/or the parameters of the noise source (G1 to G4) on the basis of a self-learning system.

23. The arrangement as claimed in one of claims 12 to 22,

characterized in that an external open-loop and/or a closed-loop control system is provided.

24. The arrangement as claimed in one of claims 12 to 23,

characterized in that provision is made of a means for analyzing the parameters (P) on the basis of the sound analysis in a plurality of iteration steps for identifying significant aspects within a noise.