EP1344198A1 - Verfahren und anordnung zur verarbeitung von geräuschsignalen einer geräuschquelle - Google Patents
Verfahren und anordnung zur verarbeitung von geräuschsignalen einer geräuschquelleInfo
- Publication number
- EP1344198A1 EP1344198A1 EP01991835A EP01991835A EP1344198A1 EP 1344198 A1 EP1344198 A1 EP 1344198A1 EP 01991835 A EP01991835 A EP 01991835A EP 01991835 A EP01991835 A EP 01991835A EP 1344198 A1 EP1344198 A1 EP 1344198A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- noise
- cfl
- signal
- sql
- source
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000012545 processing Methods 0.000 title claims abstract description 26
- 238000004458 analytical method Methods 0.000 claims abstract description 32
- 230000003287 optical effect Effects 0.000 claims description 15
- 238000001514 detection method Methods 0.000 claims description 7
- 238000012544 monitoring process Methods 0.000 claims description 4
- 230000001105 regulatory effect Effects 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 15
- 238000011156 evaluation Methods 0.000 description 11
- 230000008569 process Effects 0.000 description 6
- 230000009467 reduction Effects 0.000 description 5
- 238000004378 air conditioning Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- UHOVQNZJYSORNB-UHFFFAOYSA-N Benzene Chemical compound C1=CC=CC=C1 UHOVQNZJYSORNB-UHFFFAOYSA-N 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 238000005259 measurement Methods 0.000 description 3
- 239000010426 asphalt Substances 0.000 description 2
- 238000010009 beating Methods 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 230000007257 malfunction Effects 0.000 description 2
- 238000003909 pattern recognition Methods 0.000 description 2
- 238000001228 spectrum Methods 0.000 description 2
- 239000004575 stone Substances 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- 101100188972 Caenorhabditis elegans ddo-1 gene Proteins 0.000 description 1
- 101100446326 Caenorhabditis elegans fbxl-1 gene Proteins 0.000 description 1
- 206010039203 Road traffic accident Diseases 0.000 description 1
- 238000010521 absorption reaction Methods 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000033228 biological regulation Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000005474 detonation Methods 0.000 description 1
- 238000004880 explosion Methods 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 239000004071 soot Substances 0.000 description 1
- 238000012731 temporal analysis Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 230000001052 transient effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/015—Detecting movement of traffic to be counted or controlled with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
Definitions
- the invention relates to a method for processing noise signals from a noise source, e.g. a moving vehicle, a workshop, in a room, e.g. in the neighborhood. Furthermore, the invention relates to an arrangement for processing noise signals from a noise source.
- a noise source e.g. a moving vehicle, a workshop
- a room e.g. in the neighborhood.
- the invention relates to an arrangement for processing noise signals from a noise source.
- object-side measures for noise reduction are known which are intended to reduce the machine, aircraft or traffic noise acting on the surroundings and, consequently, to improve the working atmosphere, living environment and driving comfort.
- object-side measures for noise reduction are known which are intended to reduce the machine, aircraft or traffic noise acting on the surroundings and, consequently, to improve the working atmosphere, living environment and driving comfort.
- object-related measures for lowering the noise and the resulting reduction in the noise level are limited. Measures influencing the noise level or environmental conditions, e.g. low-noise roadway or meteorological ambient conditions are currently only partially considered with regard to compliance with the noise limit values.
- stationary, passive measuring devices for recording and monitoring immission values are usually ten, such as from benzene, soot limit values.
- the sound immission value occurring at this location of the measuring device may also be measured.
- Such a passive, location-based sound immission measurement is not suitable for identifying and classifying noise sources that generate the noise level.
- measures to reduce noise beyond those on the property are not possible.
- the object of the invention is therefore to specify a method for processing noise signals from a noise source, in which a noise emission or noise radiation caused by the noise source is detected and determined in a particularly simple and reliable manner.
- an arrangement that is particularly suitable for carrying out the method must be specified.
- the first-mentioned object is achieved according to the invention by methods for processing noise signals from a noise source, in which a plurality of noise signals are recorded in a location-related manner, examined by means of a sound analysis on the basis of signal features, and parameters underlying the noise source are determined.
- Such a common detection of a plurality of noise signals and their local and / or temporal analysis enables the location, identification, classification and evaluation of the noise source generating the noise signals.
- the noise signals are preferably recorded simultaneously. The process can be used both in closed rooms and outdoors. This makes it possible to identify critical noises in the open air, e.g.
- a loud bang, or temporally fluctuating noises in a room which indicate, for example, a functional or operational error or a load on a rotating machine in a machine hall.
- the sound analysis indications of possible malfunctions are obtained.
- a documentation of the temporal and / or local behavior of the noise source is made possible by the sound analysis of the signal characteristics of the detected noise signals and, as a result, based on the determination of parameters of the noise source causing the sound or noise signals.
- measures for noise reduction or noise reduction can be carried out on the basis of the determined noise signals and the determined parameters of the underlying noise source, for example noise-reducing regulation and / or control measures can be carried out directly at the noise source.
- the invention is based on the consideration that in order to comply with noise limit values outdoors, for example in residential areas or in the vicinity of hospitals, or in closed rooms, for example in factory or machine halls, the noise emissions occurring in this environment should be recorded and monitored , Not only the sound immission value should be recorded as a local variable. Rather, the sound or noise source on which these sound immission values are based should be determined, located, classified and evaluated. For this purpose, the amplitude, frequency and / or phase are advantageously determined and analyzed as signal characteristics of the or each recorded noise signal. For example, a location-based evaluation of the noise source causing these noise signals is made possible on the basis of a level or amplitude comparison of the various location-related noise signals.
- the noise source is located by means of running time measurement and triangulation.
- conclusions can be drawn about the sound power of the noise source on the basis of the amplitude or the sound intensity level of the respective noise signals.
- At least one of the signal features of the noise signal is expediently stored in the form of a noise pattern.
- the frequency spectrum or the level spectrum of repeatedly occurring noise signals is stored in the form of patterns for later identification or identification of the same future noise signals.
- at least one of the signal features of the noise signal is compared with stored noise patterns. This enables a particularly simple and quick determination and assignment of parameters of the underlying noise source.
- external data in particular meteorological data, optical data, time data, time data
- Possible interference signals e.g. of rain noises from the noise signals detected outdoors.
- the stored signal characteristics, noise signals or noise patterns in connection with the recorded time data, in particular time data can be used for evaluations, e.g. Statistics. This improves the quality of the identification of the underlying noise source. Long-term considerations of local noise emissions outdoors or in a room are also possible.
- optical data for example an image of an object with its surroundings or an image of a room
- Possible absorption or reflection points can be identified on the basis of the optical data and taken into account in the sound analysis.
- the data of the noise source obtained from the image and the parameters that can be derived therefrom, such as type, shape, dimensions and / or state, for example movement can be used to check the plausibility of the acoustically detected noise signals and the ascertained therefrom li N o ⁇ O CL.
- DJ ⁇ hj P- P- ⁇ DJ: r. O p- P- ⁇ DJ o DJ: ⁇ ⁇ d ⁇ P- P- ad: d P- ⁇ o SD: d ⁇ -i ⁇ P- d P rt- P ⁇ od ⁇ t r + ⁇ 3 3 H d hi ⁇ d PP ⁇ ⁇ a O h- 1 li d li ⁇ DJ H ao co ⁇ - Cfl ⁇ ⁇ C ⁇ • H rt ⁇ rt CO DJ: co DJ H, V ⁇ tr tr rt Cfl P- Cfl ad
- P P- ⁇ N as: CO co ⁇ ⁇ ⁇ tr DJ N ad: li ua OH ⁇ d ⁇ to P i DJ ⁇ ⁇ ⁇ ! 1 ⁇ li hi o t ⁇ cn h- 1 ⁇ ⁇ DJ SD: S3 ⁇ d ⁇ ! Li DJ li ⁇ hj a tr DJ: tr ⁇ P- hi O tr DJ: a P- P- ⁇ P- li?
- CD and others d ⁇ d P- h- 1 P ⁇ d and others SD rt H li Cfl SD: H P- and others li; ⁇ ; P ⁇ a ⁇ ⁇ ⁇ tc a p- li 3 rt ⁇ ⁇ P- Cfl DJ ⁇ ⁇ d ⁇ a and others hh d ⁇ d h- 1 ⁇ ⁇ ! Cfl ads: ⁇ hj P- ⁇ ⁇ Hl P- H ⁇ l DJ rt ⁇ dd - 1 li d ⁇ d Cfl P- cn o ⁇ * * ⁇ HQ
- FIG. 1 schematically shows an arrangement for processing noise signals with a plurality of noise sensors and a central data processing unit
- FIG. 6 schematically shows an alternative for the arrangement according to FIG. 1,
- FIG. 7 schematically shows a further alternative for the arrangement according to FIG. 1, and
- FIG. 8 schematically shows a further alternative for the arrangement according to FIG. 1.
- FIG. 1 shows an arrangement 1 for processing noise signals SQ1 to SQ3 from a noise source Gl, G2 or G3.
- a plurality of noise sensors M1 to M7 are arranged at different locations outdoors for the location-based detection of the noise signals SQ1 to SQ3.
- the noise sensor M6 is provided for the location-based detection of noise imitated in a residential area 2.
- the noise sensor M7 or M5 is provided for detecting noise signals SQ2 or SQ1 which are caused by the noise source G2, for example an industrial system 4, or by the noise source Gl, for example a fan of an air conditioning system in a shopping center 6.
- the noise source Gl for example a fan of an air conditioning system in a shopping center 6.
- motorcycle 10 are arranged for the direct detection of the noise signals SQ3 of the noise source G3, for example the engine, along the roadway 8 a plurality of noise sensors Ml to M4.
- the noise sensors Ml to M7 are via a data transmission unit (not shown in more detail) with a central data processing unit 12 for sound analysis of the noise signals SQ1 to SQ3 detected by the noise sensors Ml to M7 and for determining parameters P of a noise source Gl to G3 which is unknown and not identified at the moment of the measurement acquisition connected.
- a data transmission unit not shown in more detail
- a central data processing unit 12 for sound analysis of the noise signals SQ1 to SQ3 detected by the noise sensors Ml to M7 and for determining parameters P of a noise source Gl to G3 which is unknown and not identified at the moment of the measurement acquisition connected.
- wireless or wired systems e.g. Radio systems or data bus systems
- a personal computer of an environmental measuring station monitoring immission values serves, for example, as data processing unit 12.
- Directional microphones, acoustic transducers, airborne or structure-borne noise sensors, for example, are used as noise sensors Ml to M7.
- noise signals SQ1 to SQ4 of the four noise sources Gl to G4 are detected by means of the noise sensor M ⁇ arranged in the residential area 2:
- noise signal SQ2 emanating from the noise source G2, a press shop of the industrial plant 4, a few hundred meters from the residential area,
- the permissible maximum speed on the bypass is, for example, 100 km / h.
- the noise signals SQ1 to SQ4 are received on the noise sensor M ⁇ or control microphone by means of a sound analysis, in particular an amplitude, frequency or phase analysis, for determining parameters P of the noise sources Gl, G2 which generate the noise signals SQ1, SQ2, SQ3 or SQ4 , G3 or G4, in particular for the identification of noise patterns SM1 to SM4 describing the noise sources G1 to G4.
- a noise pattern SM1 to SM4 characterizes characteristic noise levels (or noise level relationships) via the frequency and the time of the associated noise sources Gl to G4.
- the sound analysis of the recorded noise signals SQ1 to SQ4 can be carried out when a permissible or maximum noise limit value is exceeded, in particular a limit value for the noise level, and thus as a function of predeterminable and / or instantaneous acoustic or optical conditions.
- a permissible or maximum noise limit value is exceeded, in particular a limit value for the noise level, and thus as a function of predeterminable and / or instantaneous acoustic or optical conditions.
- the sound analysis can be carried out by means of the data processing system 12 by means of a corresponding signal.
- the arrangement 1 can be implemented both for acoustic and / or optical location / localization, identification, classification and / or evaluation of noise signals SQ1 to SQ4 and / or noise sources Gl to G4.
- a fire can be detected in the case of an optical data acquired by means of the optical system 14.
- a possibly preceding explosion or detonation can be identified by means of at least one of the noise sensors M1 to M7 by noise signals SQ detected at the same time.
- the fan runs at a constant speed and generates stationary single tones that are emitted as airborne sound and thus noise signals SQl.
- These noise signals SQ1 are determined by its speed and the number of its rotor blades.
- the noise pattern SM1 of the fan resulting from the individual tones which are received as noise signals SQ1 is shown in FIG. 2 in the form of a Campbell diagram.
- the Campbeil diagram shows functions of two variables - here levels over frequency and time.
- FIG. 3 shows an example of a noise pattern SM2 that describes the noise source G2.
- the noise source G2 the industrial system 4, for example a press shop for sheet metal processing, presses a molded part every second.
- the noise signal SQ2 generated in this way has a typical pulse character.
- the bandwidth of the associated frequency range extends, for example, from 30 Hz to 6800 Hz.
- the noise pattern SM2 is shown as an example in the form of a Campbell diagram.
- the Campbeil diagram for the press shop is characterized by the characteristic individual pulses or noise signals SQ2, which are parallel to the frequency axis of 30 Hz to 6800 Hz at intervals of one second.
- the line representing the respective individual pulse or the noise signal SQ2 describes the frequency-related volume of the individual pulse according to the texture scaling.
- FIG. 4 shows an example of a noise pattern SM3 that describes the noise source G3.
- the noise source G3 for example a motorcycle 10, turns at walking speed from the residential area 2 into the bypass at point P1 (see FIG. 1).
- the volume of this sweep increases continuously. Due to the circular arrangement of the bypass around the noise sensor M6 or the control microphone in residential area 2 (see Figure 1), the distance between the moving noise or noise source G3 (i.e. the motorcycle 10) and the noise sensor (M6) is approximately constant. Thus there is no frequency shift after the acoustic Doppler effect. Thus, the noise pattern SM3 for the noise source G3 shown in FIG. 4 in the form of a Campbell diagram is linear.
- the Campbell diagram for the motorcycle 10 and thus for the noise source G3 is described by the characteristic course of the sweep due to the change in ignition frequency during the acceleration process.
- the increase in volume during this speed change is described by the texture scaling.
- FIG. 5 shows, by way of example, a further noise pattern SM4 for noise signals SQ6 received by means of the noise sensor M6, which describe a combination of humming and striking noises.
- a stone has jammed, which strikes the asphalt once with each wheel revolution and thereby generates a pulse of the bandwidth 90 Hz to 5 kHz.
- This beating noise is detected by the noise sensor M6 in residential area 2 together with the changing ignition frequency of the high-revving engine.
- the resulting noise pattern SM4 is shown in FIG. 5 in the form of a Campbell diagram.
- the noise pattern SM4 comprises overlapping noise signals SQ3 or SQ4, which characterize the noise source G3, ie the engine and the driving noise.
- the sloping line between the frequencies fl and f2 describes the changing ignition frequency of the high-revving engine and thus the noise signal SQ3.
- the lines running parallel to the frequency axis describe the striking noise of the stone on the asphalt and thus the noise signal SQ4.
- the recorded noise signals SQ1 to SQ4 are examined by means of a sound analysis based on signal features in such a way that they are assigned to the underlying noise source Gl to G4 and the parameters P underlying the noise source Gl to G4, such as fans in operation or motorcycle 10 or stands.
- the sound analysis is carried out as a function of a noise level detected on the noise sensor M6 that has exceeded a noise limit value.
- the data processing unit 12 includes a corresponding means for limit value monitoring, for example a corresponding function block implemented in software.
- the sound analysis can be carried out on the basis of various analyzes, for example time, frequency and / or level analyzes.
- the sound analysis includes algorithms that the relevant noise signal SQl to SQ4 according to characteristic signal features, such as. B. Fixed frequencies (fans), short broadband pulses (press shop) and sweeps (accelerating motorcycle).
- Such an algorithm is e.g. B. the method described below for identifying characteristic signal features of the noise signals SQ1 to SQ4 of an underlying noise pattern SM1 to SM.
- the characteristic signal features of the noise pattern SM1 to SM4 are used as identification criteria for the respective noise pattern SM1 to SM4, on the basis of which a comparison with noise patterns SM a to SM Z stored in a database of the data processing unit 12 and with noise patterns SM1 to M7 detected using the noise sensors Ml to M7 is used SM4 is done. This comparison enables an assignment of the noise recorded in the M6 microphone signals SQl to SQ4 to the causing noise source Gl to G4.
- the recorded noise signals SQ1 to SQ4 of the measuring points or noise sensors M1 to M7 are stored in a ring memory as time data. If a threshold or noise limit is exceeded, e.g. B. on the microphone M6 in residential area 2, the content of the ring buffer is stored with a predefinable lead time before the noise limit value is exceeded.
- Characteristic noise or signal characteristics are analyzed using sound analysis in accordance with the graphic aspects in the Campbell diagram.
- a pixel in the Campbell diagram (depending on the resolution of the Fast Fourier Transform (FFT)) corresponds to a volume value of an analyzed frequency and time bandwidth within the detection ranges.
- Graphical correlations cf. noise pattern SM1 to SM4 in FIGS.
- noise sources Gl to G4 correspond to acoustic signal features which, based on the database comparison and the comparison with other noise signals SQl to SQ4 of other noise sensors Ml to M7 (e.g. near-field microphones, directional microphones), are specific causes.
- the noise sources Gl to G4 are assigned.
- a preferred evaluation of detected noise signals SQ1 to SQ4 is e.g. B. the Fast Fourier Transformation (FFT for short) of the microphone signals and the calculation of the so-called A-weighted sound pressure level.
- FFT Fast Fourier Transformation
- Relevant evaluation criteria of the FFT are, for example, sampling rate (fixed, e.g. at 25 kHz) or block length. If frequencies close to each other are to be resolved to identify a noise pattern SM1 to SM4, a different block length should be selected than in the case of pulses that follow one another in time (in accordance with the principle of the noise pattern SM1 to SM4).
- a sound or pattern analysis can include several independent processes that use different block lengths of the FFT, for example, as evaluation criteria.
- This exemplary choice of the value of an evaluation criterion can depend on the running process itself or on external requirements.
- the data processing unit 12 preferably has a means for analyzing the parameters P on the basis of the sound analysis, the parameter analysis being carried out in a plurality of iteration steps in order to recognize significant aspects or noise patterns SM1 to SM4 within a detected noise signal SQ1 to SQ4, such as e.g. Frequency and volume of a humming tone, bandwidth, volume and time interval of a repeated beating noise.
- the evaluation criteria of the sound analysis can be changed based on input variables.
- optical pattern recognition can also be carried out as an input signal.
- an optical system (not shown) for recording optical data of the surroundings or a room is additionally provided.
- Another application can e.g. B. consist in a specific recognition specification of special processes. This can e.g. B. the targeted search for high-speed motorcycles or starting commercial vehicles, the occurrence of which is filtered out from the recorded noise signals SQ1 to SQ4.
- noise-critical maintenance work if it cannot be carried out under normal weather and traffic conditions because of the night's rest, noise-critical activity can still be permitted in the event of a loud background noise such as pounding rain or heavy traffic (as a result of a diversion due to an accident).
- the consideration of the data from external systems such as optical, meteorological or navigation systems, can be determined and controlled in the sound analysis on the basis of input variables, for example limit value violations, and / or quality features.
- Figure 6 shows an embodiment for the arrangement 1 for a spatial and temporal evaluation of noise sources Gl to G4.
- the arrangement 1 comprises five noise sensors Ml to M5, which are arranged at a measuring point, for example, one above the other on a lamppost on a roadway or on a support in a workshop.
- Four of the five noise sensors Ml to M4 have a horizontal directional characteristic in all four directions.
- One of the five noise sensors M5 has a vertical directional characteristic, in particular a spherical characteristic.
- a noise signal SQ1 to SQ4 that exceeds the noise limit value is detected by means of the noise sensor M5 with a spherical characteristic.
- At least one signal feature of the noise signal SQ1 to SQ4, for example level, frequency, phase, is examined and identified.
- the noise pattern SM1 to SM4 determined in the process is compared for equality with the noise signals SQ1 to SQ4 received by means of the four directional microphones or noise sensors Ml to M4, so that on the basis of those noise sensors Ml to M4 with the same noise pattern. ter SMl to SM4 and the strongest level the direction can be determined.
- FIG. 7 shows a further embodiment of the arrangement 1 with a plurality of noise sensors Ml to M5.
- the noise sensors Ml to M5 are arranged as microphones with a vertical omnidirectional characteristic on an examination site of an industrial plant. Alternatively, these can also be used in a closed room, e.g. be arranged in a workshop of the industrial plant 4.
- Noise signals SQ1 to SQ4 of the same noise source Gl to G4, e.g. the noise signal SQ1 of a passing vehicle 14 or the noise signal SQ2 of the industrial plant 4 is received by the noise sensors Ml to M5, which are arranged at different locations depending on the sound path covered and the resulting sound propagation time at different times. Based on the given position of the noise sensors Ml to M5 and the determined sound path or sound propagation time for the respective noise sensor Ml to M5, the position of the noise or sound source Gl or G2, i.e. of the vehicle 14 or the industrial plant 4.
- the arrangement 1 comprises six noise sensors Ml to M6.
- the noise sensors Ml to M6 are designed as microphones with omnidirectional characteristics.
- the noise sensors Ml to M6 are arranged at different measuring points in the examination area.
- the noise sensors Ml to M4 are arranged along the carriageway 8.
- the noise sensor M5 is arranged in the vicinity of the industrial plant 4.
- the noise sensor M6 is arranged in the residential area 2. In the operation of the arrangement 1, a noise exceeding the noise limit value is detected by means of the noise sensor M6. That this Noise signal SQl on which the noise signal is based is compared with the noise patterns SM1 received by the other noise sensors Ml to M4 or noise pattern SM2 received by the noise sensor M5.
- an assessment of the detected noise signal SQ1 and thus also an assessment of the noise source Gl is given.
- a combination of frequency and level analysis taking into account external influences or data, such as eliminating interference or other noise signals such as rain noise, enables a statement to be made about the state of the noise source Gl, for example the vehicle 14 accelerating or braking.
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
- Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
- Soundproofing, Sound Blocking, And Sound Damping (AREA)
- Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
Abstract
Description
Claims
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE10064756 | 2000-12-22 | ||
| DE10064756A DE10064756A1 (de) | 2000-12-22 | 2000-12-22 | Verfahren und Anordnung zur Verarbeitung von Geräuschsignalen einer Geräuschquelle |
| PCT/EP2001/014623 WO2002052522A1 (de) | 2000-12-22 | 2001-12-12 | Verfahren und anordnung zur verarbeitung von geräuschsignalen einer geräuschquelle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| EP1344198A1 true EP1344198A1 (de) | 2003-09-17 |
| EP1344198B1 EP1344198B1 (de) | 2004-07-14 |
Family
ID=7668796
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| EP01991835A Expired - Lifetime EP1344198B1 (de) | 2000-12-22 | 2001-12-12 | Verfahren und anordnung zur verarbeitung von geräuschsignalen einer geräuschquelle |
Country Status (8)
| Country | Link |
|---|---|
| US (1) | US20040081322A1 (de) |
| EP (1) | EP1344198B1 (de) |
| JP (1) | JP4167489B2 (de) |
| BR (1) | BR0116418A (de) |
| DE (2) | DE10064756A1 (de) |
| ES (1) | ES2223950T3 (de) |
| MX (1) | MXPA03005620A (de) |
| WO (1) | WO2002052522A1 (de) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102020110659A1 (de) | 2020-04-20 | 2021-10-21 | Bayerische Motoren Werke Aktiengesellschaft | Betreiben eines Fahrzeugs sowie Fahrzeug und System |
Families Citing this family (31)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2003015456A2 (en) * | 2001-08-10 | 2003-02-20 | Seti Média Inc. | Sound pollution surveillance system and method |
| DE10250739A1 (de) | 2002-10-31 | 2004-05-13 | Bayerische Motoren Werke Ag | Verfahren zur Bewertung von Störgeräuschen |
| DE10358375B4 (de) * | 2002-12-12 | 2014-01-23 | Robert Bosch Gmbh | Verfahren zur Geräuschklassifikation |
| DE10349479B3 (de) * | 2003-10-21 | 2005-07-14 | Siemens Ag | Vorrichtung zur Lokalisierung von Verkehrsunfällen |
| JP4569437B2 (ja) * | 2005-08-31 | 2010-10-27 | 日本精工株式会社 | 異常診断装置 |
| US8248226B2 (en) * | 2004-11-16 | 2012-08-21 | Black & Decker Inc. | System and method for monitoring security at a premises |
| DE102004062029A1 (de) | 2004-12-23 | 2006-07-13 | Robert Bosch Gmbh | Überwachung einer Mehrkolbenpumpe |
| US7881939B2 (en) * | 2005-05-31 | 2011-02-01 | Honeywell International Inc. | Monitoring system with speech recognition |
| US20070031237A1 (en) * | 2005-07-29 | 2007-02-08 | General Electric Company | Method and apparatus for producing wind energy with reduced wind turbine noise |
| US8531286B2 (en) * | 2007-09-05 | 2013-09-10 | Stanley Convergent Security Solutions, Inc. | System and method for monitoring security at a premises using line card with secondary communications channel |
| WO2010037387A2 (en) * | 2008-09-30 | 2010-04-08 | Vestas Wind Systems A/S | Control of wind park noise emission |
| US8983677B2 (en) * | 2008-10-01 | 2015-03-17 | Honeywell International Inc. | Acoustic fingerprinting of mechanical devices |
| US20100082180A1 (en) * | 2008-10-01 | 2010-04-01 | Honeywell International Inc. | Errant vehicle countermeasures |
| US9928824B2 (en) | 2011-05-11 | 2018-03-27 | Silentium Ltd. | Apparatus, system and method of controlling noise within a noise-controlled volume |
| ES2834442T3 (es) * | 2011-05-11 | 2021-06-17 | Silentium Ltd | Sistema y método de control del ruido |
| US20170307435A1 (en) * | 2014-02-21 | 2017-10-26 | New York University | Environmental analysis |
| US10401517B2 (en) | 2015-02-16 | 2019-09-03 | Pgs Geophysical As | Crosstalk attenuation for seismic imaging |
| DE102015119594A1 (de) * | 2015-11-13 | 2017-05-18 | Albert Orglmeister | Verfahren zur Eliminierung von thermischen Störungen bei der Infrarot- und Video-Brandfrüherkennung |
| US10694107B2 (en) * | 2015-11-13 | 2020-06-23 | Albert Orglmeister | Method and device for eliminating thermal interference for infrared and video-based early fire detection |
| US11959798B2 (en) * | 2017-04-11 | 2024-04-16 | Systèmes De Contrôle Actif Soft Db Inc. | System and a method for noise discrimination |
| EP3625525B1 (de) * | 2017-05-16 | 2022-02-09 | Signify Holding B.V. | Rausch-flussüberwachung und schall-lokalisation mittels intelligenter beleuchtung |
| DE102018200878B3 (de) * | 2018-01-19 | 2019-02-21 | Zf Friedrichshafen Ag | Detektion von Gefahrengeräuschen |
| US20210010855A1 (en) * | 2018-05-11 | 2021-01-14 | Nec Corporation | Propagation path estimation apparatus, method, and program |
| EP3879938B1 (de) * | 2020-03-11 | 2024-10-16 | Tridonic GmbH & Co KG | Leuchtenraster |
| CN111721401B (zh) * | 2020-06-17 | 2022-03-08 | 广州广电计量检测股份有限公司 | 一种低频噪声分析系统及方法 |
| CN112729528B (zh) * | 2020-12-07 | 2022-09-23 | 潍柴动力股份有限公司 | 一种噪声源识别方法、装置及设备 |
| JP7557824B2 (ja) * | 2021-06-25 | 2024-09-30 | 富士フイルム株式会社 | 医用画像処理装置、医用撮像装置、及び、医用画像におけるノイズ低減方法 |
| JP7459857B2 (ja) * | 2021-12-10 | 2024-04-02 | トヨタ自動車株式会社 | 異音解析装置および方法 |
| DE102022003089A1 (de) | 2022-08-23 | 2024-02-29 | Mercedes-Benz Group AG | Signalausgabevorrichtung und Kraftfahrzeug mit einer solchen Signalausgabevorrichtung |
| IT202400000186A1 (it) * | 2024-01-08 | 2025-07-08 | Tecnojest S R L | Sistema per la rilevazione e il monitoraggio del rumore in spazi ampi |
| DE102024003393A1 (de) | 2024-10-17 | 2026-01-22 | Mercedes-Benz Group AG | Lärmkarten-Validierung mittels Außenmikrophone eines Fahrzeugs |
Family Cites Families (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4424511A (en) * | 1980-10-30 | 1984-01-03 | Alberts Jr Fred L | Noise monitor |
| US4346374A (en) * | 1981-01-05 | 1982-08-24 | Groff James W | Classroom noise alarm |
| US4806931A (en) * | 1988-01-25 | 1989-02-21 | Richard W. Clark | Sound pattern discrimination system |
| US4876721A (en) * | 1988-03-03 | 1989-10-24 | Martin Marietta Energy Systems, Inc. | Method and device for identifying different species of honeybees |
| US6760451B1 (en) * | 1993-08-03 | 2004-07-06 | Peter Graham Craven | Compensating filters |
| US5452364A (en) * | 1993-12-07 | 1995-09-19 | Bonham; Douglas M. | System and method for monitoring wildlife |
| US5619616A (en) * | 1994-04-25 | 1997-04-08 | Minnesota Mining And Manufacturing Company | Vehicle classification system using a passive audio input to a neural network |
| JPH09167296A (ja) * | 1995-12-15 | 1997-06-24 | Fuji Facom Corp | 道路上の交通流パラメータ計測方法 |
| JPH103479A (ja) * | 1996-06-14 | 1998-01-06 | Masaomi Yamamoto | 動物等の意思翻訳方法および動物等の意思翻訳装置 |
| US5878367A (en) * | 1996-06-28 | 1999-03-02 | Northrop Grumman Corporation | Passive acoustic traffic monitoring system |
| SE516798C2 (sv) * | 1996-07-03 | 2002-03-05 | Thomas Lagoe | Anordning och sätt för analys och filtrering av ljud |
| JP2939940B2 (ja) * | 1996-07-09 | 1999-08-25 | 日本電気株式会社 | ファン音消音装置 |
| US5844983A (en) * | 1997-07-10 | 1998-12-01 | Ericsson Inc. | Method and apparatus for controlling a telephone ring signal |
-
2000
- 2000-12-22 DE DE10064756A patent/DE10064756A1/de not_active Withdrawn
-
2001
- 2001-12-12 BR BR0116418-0A patent/BR0116418A/pt not_active IP Right Cessation
- 2001-12-12 ES ES01991835T patent/ES2223950T3/es not_active Expired - Lifetime
- 2001-12-12 MX MXPA03005620A patent/MXPA03005620A/es active IP Right Grant
- 2001-12-12 DE DE50102884T patent/DE50102884D1/de not_active Expired - Lifetime
- 2001-12-12 WO PCT/EP2001/014623 patent/WO2002052522A1/de not_active Ceased
- 2001-12-12 US US10/451,415 patent/US20040081322A1/en not_active Abandoned
- 2001-12-12 EP EP01991835A patent/EP1344198B1/de not_active Expired - Lifetime
- 2001-12-12 JP JP2002553745A patent/JP4167489B2/ja not_active Expired - Fee Related
Non-Patent Citations (1)
| Title |
|---|
| See references of WO02052522A1 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102020110659A1 (de) | 2020-04-20 | 2021-10-21 | Bayerische Motoren Werke Aktiengesellschaft | Betreiben eines Fahrzeugs sowie Fahrzeug und System |
Also Published As
| Publication number | Publication date |
|---|---|
| WO2002052522A1 (de) | 2002-07-04 |
| JP4167489B2 (ja) | 2008-10-15 |
| DE10064756A1 (de) | 2002-07-04 |
| MXPA03005620A (es) | 2004-03-18 |
| US20040081322A1 (en) | 2004-04-29 |
| DE50102884D1 (de) | 2004-08-19 |
| BR0116418A (pt) | 2003-12-30 |
| JP2004517309A (ja) | 2004-06-10 |
| ES2223950T3 (es) | 2005-03-01 |
| EP1344198B1 (de) | 2004-07-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| EP1344198A1 (de) | Verfahren und anordnung zur verarbeitung von geräuschsignalen einer geräuschquelle | |
| DE10064754A1 (de) | Verfahren und Anordnung zur Bestimmung eines Geräuschsignals einer Geräuschquelle | |
| DE102012107445B4 (de) | 2Verfahren zur Klassifizierung von fahrenden Fahrzeugen | |
| DE10136981A1 (de) | Verfahren und Vorrichtung zur Ermittlung eines stationären und/oder bewegten Objektes | |
| DE102008021362B3 (de) | Verfahren und Vorrichtung zum Erkennen eines Zustandes einer zu untersuchenden geräuscherzeugenden Maschine | |
| EP3381024A1 (de) | Klassifizieren eines oder mehrerer reflektionsobjekte | |
| EP0860712A2 (de) | Vorrichtung und Verfahren zur umgebungsadaptiven Klassifikation von Objekten | |
| DE102018208464A1 (de) | Verfahren zur Funktionsprüfung eines Radarsensors sowie zur Durchführung des Verfahrens geeignete Einrichtung | |
| AT410923B (de) | Verfahren und vorrichtung zur erkennung eines schadhaften wälzlagers von rädern eines schienenfahrzeuges | |
| DE102019217794A1 (de) | Verfahren zur Ermittlung von Verkehrsinformationen | |
| DE102015120533B4 (de) | Einrichtung und Verfahren zur akustischen Verkehrsdatenerfassung | |
| EP4107545A1 (de) | Verfahren zum schätzen einer eigengeschwindigkeit | |
| DE602004008735T2 (de) | Einrichtung und Verfahren zur Erkennung von Flachstellen bei Räder, Exzentrizitätten bei Achslagern und Schaden bei den Schienen in einem Eisenbahnsystem | |
| DE102020109580B4 (de) | Verfahren zur überwachung einer energieerzeugungsanlage und/oder zur lokalisierung von komponenten der energieerzeugungsanlage | |
| EP3329332B1 (de) | Verfahren zur ermittlung von stützpunkten eines versuchsplans | |
| EP3257719B1 (de) | Verfahren zur detektion der entgleisung eines schienenfahrzeugs | |
| DE102020116507A1 (de) | Verfahren zur Ermittlung einer Zielgröße | |
| DE10322617A1 (de) | Verfahren und Vorrichtungen zum Erkennen von einem Gegenstand auf einer Fahrbahnoberfläche | |
| EP1372826B1 (de) | Verfahren und vorrichtung zur beurteilung der funktionsfähigkeit einer einrichtung zur reduzierung des ozongehaltes von luft | |
| DE112023002380T5 (de) | Verfahren und system zum erzeugen eines fahrzeugkilometerstandes | |
| DE102018218308B4 (de) | Verfahren zum Erfassen einer Luftqualität, Kraftfahrzeug und Servereinrichtung | |
| EP1280118B1 (de) | Verfahren zur Feststellung von Strassenverkehrszuständen | |
| DE102019215821A1 (de) | Verfahren zur Schwingungsanalyse eines mit Kraftfahrzeugen befahrbaren Bauwerks | |
| EP0792439B1 (de) | Verfahren und einrichtung zur erfassung und auswertung von auf bestimmte physikalische vorgänge zurückzuführenden signalverläufen | |
| Benedetti et al. | Drive‐by frequencies extraction by means of synchrosqueezed wavelet transform |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
| 17P | Request for examination filed |
Effective date: 20030624 |
|
| AK | Designated contracting states |
Kind code of ref document: A1 Designated state(s): AT BE CH CY DE DK ES FI FR GB GR IE IT LI LU MC NL PT SE TR |
|
| RIC1 | Information provided on ipc code assigned before grant |
Ipc: 7G 08G 1/015 A Ipc: 7G 08G 1/04 B |
|
| GRAP | Despatch of communication of intention to grant a patent |
Free format text: ORIGINAL CODE: EPIDOSNIGR1 |
|
| GRAS | Grant fee paid |
Free format text: ORIGINAL CODE: EPIDOSNIGR3 |
|
| GRAA | (expected) grant |
Free format text: ORIGINAL CODE: 0009210 |
|
| AK | Designated contracting states |
Kind code of ref document: B1 Designated state(s): DE ES FR GB IT SE |
|
| REG | Reference to a national code |
Ref country code: GB Ref legal event code: FG4D Free format text: NOT ENGLISH |
|
| REF | Corresponds to: |
Ref document number: 50102884 Country of ref document: DE Date of ref document: 20040819 Kind code of ref document: P |
|
| REG | Reference to a national code |
Ref country code: IE Ref legal event code: FG4D Free format text: GERMAN |
|
| GBT | Gb: translation of ep patent filed (gb section 77(6)(a)/1977) |
Effective date: 20040914 |
|
| REG | Reference to a national code |
Ref country code: SE Ref legal event code: TRGR |
|
| REG | Reference to a national code |
Ref country code: ES Ref legal event code: FG2A Ref document number: 2223950 Country of ref document: ES Kind code of ref document: T3 |
|
| REG | Reference to a national code |
Ref country code: IE Ref legal event code: FD4D |
|
| ET | Fr: translation filed | ||
| PLBE | No opposition filed within time limit |
Free format text: ORIGINAL CODE: 0009261 |
|
| STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT |
|
| 26N | No opposition filed |
Effective date: 20050415 |
|
| REG | Reference to a national code |
Ref country code: FR Ref legal event code: CA Ref country code: FR Ref legal event code: CD |
|
| PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: FR Payment date: 20110104 Year of fee payment: 10 |
|
| PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: SE Payment date: 20101214 Year of fee payment: 10 Ref country code: GB Payment date: 20101221 Year of fee payment: 10 |
|
| PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: DE Payment date: 20101222 Year of fee payment: 10 Ref country code: IT Payment date: 20101227 Year of fee payment: 10 |
|
| PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: ES Payment date: 20101223 Year of fee payment: 10 |
|
| REG | Reference to a national code |
Ref country code: SE Ref legal event code: EUG |
|
| GBPC | Gb: european patent ceased through non-payment of renewal fee |
Effective date: 20111212 |
|
| REG | Reference to a national code |
Ref country code: FR Ref legal event code: ST Effective date: 20120831 |
|
| REG | Reference to a national code |
Ref country code: DE Ref legal event code: R119 Ref document number: 50102884 Country of ref document: DE Effective date: 20120703 |
|
| PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: GB Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20111212 Ref country code: SE Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20111213 Ref country code: DE Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20120703 |
|
| PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: IT Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20111212 |
|
| PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: FR Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20120102 |
|
| REG | Reference to a national code |
Ref country code: ES Ref legal event code: FD2A Effective date: 20130704 |
|
| PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: ES Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20111213 |