EP1344198B1 - Procede et dispositif de traitement de signaux sonores issus d'une source de bruits - Google Patents

Procede et dispositif de traitement de signaux sonores issus d'une source de bruits Download PDF

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Publication number
EP1344198B1
EP1344198B1 EP01991835A EP01991835A EP1344198B1 EP 1344198 B1 EP1344198 B1 EP 1344198B1 EP 01991835 A EP01991835 A EP 01991835A EP 01991835 A EP01991835 A EP 01991835A EP 1344198 B1 EP1344198 B1 EP 1344198B1
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EP
European Patent Office
Prior art keywords
noise
signal
source
sound
signals
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EP01991835A
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German (de)
English (en)
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EP1344198A1 (fr
Inventor
Michael Schliep
Szabolcs TÖRGYEKES
Rolf Witte
Walter Zipp
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Mercedes Benz Group AG
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DaimlerChrysler AG
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    • 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 a noise source, e.g. a moving one Vehicle, a workshop, in a room, e.g. in the neighborhood. Moreover, the invention relates to an arrangement for processing noise signals from a noise source.
  • a noise source e.g. a moving one 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 which the environment, machine, aircraft or Reduce traffic noise and consequently the working environment, living environment and to improve ride comfort.
  • object-side measures for noise reduction for sound reduction of objects, e.g. from street or Rail vehicles, aircraft or machinery, low noise Exhaust and intake systems, largely resonance-free engines or sound-absorbing bodies known.
  • the noise level influencing measures or Environmental conditions such as low noise road or meteorological Environmental conditions are currently being considered to the observance of the noise limits only rudimentarily taken into account.
  • JP 09-167296 A discloses a method of measuring traffic flow described at the sounds of vehicles over Microphones are detected and noise parameters are determined.
  • the object of the invention is therefore to provide a method for processing from noise signals from a noise source specify that one of the most simple and secure Noise source caused noise emission or noise emission is detected and determined.
  • one is for Specify implementation of the method particularly suitable arrangement.
  • the first object is achieved by Method for processing noise signals of a noise source, in which several noise signals are detected locally, by means of a sound analysis based on signal characteristics examined and the noise source underlying parameters be determined.
  • a sound analysis based on signal characteristics examined and the noise source underlying parameters be determined.
  • the noise signals are preferred detected at the same time. In doing so, the procedure can be both closed Spaces, as well as outdoors are used.
  • an identification of critical noises in the Outdoors e.g. from a loud bang, or from time to time fluctuating noises in a room, which e.g. on one Function or operation error or a load of a rotating Machine in a machine hall point, allows.
  • noise analysis Information on possible malfunctions won become.
  • the sound analysis of the signal characteristics of the detected Noise signals and resulting from the determination parameters of the sound or noise signals causing noise source is a documentation of temporal and / or local behavior of the noise source allows.
  • the determined Noise signals and the determined parameters of underlying noise source Measures to reduce noise or noise reduction e.g. can be noise reducing Regulatory and / or control measures be performed directly at the noise source.
  • the invention is based on the consideration that for compliance outdoor noise limits, e.g. in residential areas or near hospitals, or in closed Spaces, e.g. in factory or machine halls, in this Environment detected and monitored sound immission should be. It should not just the sound immission value be detected as local size. Rather, it should be this Sound immission values based sound or noise source determined, located, classified and evaluated. These are advantageously as signal characteristics of or each detected noise signal whose amplitude, frequency and / or phase determined and analyzed. For example based on a level or amplitude comparison of the different ones Location-based noise signals a location-based evaluation the noise source causing these noise signals allows.
  • the sound analysis is based on a time, Frequency and / or level analysis performed. This is for example for a characterizing the respective noise signal Sound spectrum the dependence of the sound pressure level from the frequency by frequency analysis, e.g. one Fast Fourier Transformation (FFT for short) determined. Based on the fast Fourier transformation may be preferred Sample rate, block length or interval of the underlying Sound or noise signal can be determined.
  • FFT Fast Fourier Transformation
  • the parameters of the noise source whose Type, position and / or condition determined. This is for example on the basis of the sound analysis determined Features of the noise signal, e.g. of the interval, or based the combination of several noise signals the type of noise source, e.g. a siren of an emergency vehicle, or the position of the noise source determined.
  • the noise source is determined by the sound analysis of the noise signals a movement of the noise source or an operating condition the noise source determined.
  • a noise limit When a noise limit is exceeded expediently carried out the sound analysis.
  • a sound limit exceeded noise analysis a PRE trigger to keep a temporary Ring buffer used.
  • At least one of the signal characteristics the noise signal stored in the form of a noise pattern For example, the frequency spectrum or the level spectrum of repetitive noise signals for a later identification or identification of the same future noise signals in the form of patterns deposited.
  • the noise signals and thus the noise source becomes at least one of the signal characteristics of the noise signal compared with stored noise patterns. This is a particularly simple and fast determination and assignment of parameters of the underlying noise source allows.
  • preferably external data especially meteorological data, optical data, time data, Time data, in the sound analysis of the detected noise signals considered.
  • This allows possible interference signals, such as. of rain noise, gathered from the outdoors Noise signals are eliminated.
  • you can the stored signal characteristics, noise signals or Noise patterns associated with the acquired time data, in particular time data, for evaluations, e.g. Statistics, be used.
  • the quality of identification the underlying noise source improved.
  • long-term considerations of local noise immissions outdoors or in a room allows.
  • optical data e.g. on Image of an object with its surroundings or an image of a Jardins, grasped.
  • possible absorption or reflection points identified and at the Sound analysis to be considered.
  • the resulting derivable parameters such as type, shape, dimension and / or Condition, e.g. Movement, to check the plausibility of the acoustic detected noise signals and the determined therefrom Signal characteristics and parameters of the noise source used become.
  • a particularly secure identification and Classification of the noise source or the object or the Event allows.
  • a self-learning system For determining and classifying the signal characteristics of the noise signal and / or the parameter of the noise source advantageously used a self-learning system.
  • self-learning system become different forms of artificial Intelligence, e.g. neural networks, fuzzy logic and / or expert systems used. This is a consideration of blurred values, e.g. of "loud” or "less noisy” rainfall sounds.
  • blurred values e.g. of "loud” or "less noisy” rainfall sounds.
  • classification can be used, e.g. for a consideration of age-related Changes in the parameters of the identified noise source.
  • the deposited Noise patterns using neural networks based on the current or currently detected noise signals of the identified noise source customized.
  • the signal characteristics and / or the parameters a control and / or a control system, a Information system and / or fed to an alarm system.
  • the second object is achieved by an arrangement with a plurality of noise sensors for location-based detection of noise signals and with a central data processing unit for sound analysis of the noise signals based on at least one signal feature and for Determination of at least one characterizing the noise source Parameter.
  • a plurality of noise sensors for location-based detection of noise signals
  • a central data processing unit for sound analysis of the noise signals based on at least one signal feature and for Determination of at least one characterizing the noise source Parameter.
  • noise sensors are directional microphones intended.
  • Various directional microphones provided.
  • acoustic acoustic sensors or noise sensors distributed in different places in the Room or be arranged outdoors.
  • the noise sensors are for the spatial and / or temporal assignment of the noise source with the central data processing unit by means of Data transmission units connected.
  • airborne transducers, structure-borne sound transducers Capture of object or position related acoustic Signals provided.
  • the data processing unit preferably comprises a means for determining the amplitude, frequency and / or phase of or every sound signal.
  • the means in particular for determining the amplitude, phase or frequency spectrum the noise signals. This is for example by the determined pulse sequence of the sound or noise signals one beyond the usual sound detection Identification, classification and evaluation of the noise signals generating noise source possible. For example are sudden energy releases, such as these e.g. occur due to mechanical deformations in an accident, identified by the characterizing sound pulses and classifiable.
  • a means for determining type, position and / or state of the noise source comprises a sound analysis module, for an amplitude, Frequency and / or phase analysis, on.
  • the sound analysis module is used to analyze the noise amplitude and the sound sequence, in particular the sound pulse sequence.
  • the data processing unit comprises a means of monitoring a noise limit.
  • a noise limit e.g. one maximum permissible noise limit by at least one the detected noise signals for a monitored area or a room to be monitored is an event-driven one Sound analysis allows.
  • a permanent Sound analysis for the area or area concerned Space to be executed.
  • a data storage for the deposit is at least one of the signal characteristics of the noise signal in the form of a Noise pattern provided.
  • a means for comparison at least one of the signal characteristics of the noise signal with stored noise patterns for determination and assignment of parameters of the underlying noise source intended is a particularly easy and fast identification of sound sequences characterizing respective noise sources and thus a quick identification of the noise source allows.
  • an agent intended to analyze the parameters which the parameters Based on the sound analysis in several iteration steps for Detection of significant aspects or patterns within of a sound, such as of significant frequency patterns.
  • an optical system for detection provided by optical data.
  • the taking of a picture the environment of the distributed noise sensors in a room or outdoors based on the optical system allows a supplementary determination of the noise source or a Plausibility check to the identified by the sound analysis Noise source.
  • absorption or reflective surfaces identified and in the sound analysis the noise signals are taken into account. Further is in a room to be monitored, e.g. a workshop, one Room or building security, i. a burglar alarm, both optically and acoustically enabled.
  • the noise signals influencing Data is preferably a capture unit for capture provided by meteorological data.
  • a capture unit for capture provided by meteorological data.
  • Preferably is also a means of identification and classification the signal characteristics of the noise signal and / or the parameter of the noise source based on a self-learning Systems provided.
  • artificial intelligence e.g. neural networks and / or fuzzy logic, used.
  • the identification, localization and Classification of the noise signals and / or the underlying Noise source in stationary, cyclic or transient takes place on the basis of fuzzy values and their logical Connections.
  • an external control and / or regulation system intended.
  • Through the sound analysis executed detection and evaluation of the noise signals can For example, external safety systems are activated become.
  • the noise signals for noise-reducing Control and / or regulating systems are used.
  • the advantages achieved by the invention are in particular in that for a permanent monitoring of sound and Noise emissions and for a secure identification of noise-causing noise sources, objects or events recorded several noise signals location-related and such analyzed by means of a sound analysis based on signal characteristics be that at least one of the noise source underlying Parameter is determined.
  • a parameter of the noise-emitting noise source e.g. a humming sound of a rotating machine in one Engine hangar or a bang by a traffic accident is an application of the arrangement both in closed rooms, e.g. in factories or production halls, or in the surrounding area, e.g. along a highway, given.
  • a parameter of the noise-emitting noise source e.g. a humming sound of a rotating machine in one Engine hangar or a bang by a traffic accident is an application of the arrangement both in closed rooms, e.g. in factories or production halls, or in the surrounding area, e.g. along a highway, given.
  • FIG. 1 shows an arrangement 1 for processing noise signals SQ1 to SQ3 a noise source G1, G2 or G3.
  • a noise source G1, G2 or G3 For location-based detection of the noise signals SQ1 to SQ3 are a plurality of noise sensors M1 to M7 at different ones Places arranged outdoors. For example, is to location-based detection of mimicking in a residential area 2 Noise of the sound sensor M6 provided.
  • the noise sensor M7 or M5 provided.
  • motorcycles 10 are for direct detection of the noise signals SQ3 of the noise source G3, e.g. of the engine, along the Roadway 8 a plurality of noise sensors M1 to M4 arranged.
  • the noise sensors M1 to M7 are not closer by one illustrated data transmission unit with a central data processing unit 12 for sound analysis of the means of Noise sensors M1 to M7 detected noise signals SQ1 to SQ3 and to determine parameter P at the moment of Meter reading unknown and unidentified noise source G1 to G3 connected.
  • a data transmission unit for example, wireless or wired systems, e.g. Radio systems or data bus systems provided.
  • noise sensors M1 to M7 are for example directional microphones, acoustic transducers, airborne or structure-borne sound sensors, used.
  • noise signals SQ1 to SQ4 by means of a sound analysis, in particular an amplitude, frequency or phase analysis, to determine parameters P of the noise signals SQ1, SQ2, SQ3 or SQ4 generating Sound source G1, G2, G3 and G4, in particular for identification from the noise sources G1 to G4 descriptive noise patterns SM1 to SM4, examined.
  • a noise pattern SM1 to SM4 characterizes characteristic noise levels (or noise levels) over the frequency and the Time of the associated noise sources G1 to G4.
  • the sound analysis of the detected noise signals SQ1 to SQ4 if a permissible or maximum noise limit is exceeded, in particular a limit value for the noise level, and thus depending on predefinable and / or current acoustic or optical conditions become.
  • a permissible or maximum noise limit is exceeded, in particular a limit value for the noise level, and thus depending on predefinable and / or current acoustic or optical conditions become.
  • an optical System 14 captured image which is a critical situation e.g. a traffic accident or an accident in the press plant, e.g. a fire, by a corresponding signal the sound analysis by means of the data processing system 12 be executed.
  • an event-driven Sound analysis can be the arrangement 1 for both an acoustic and / or optical location / localization, identification, Classification and / or evaluation of noise signals SQ1 to SQ4 and / or noise sources G1 to G4 are performed.
  • noise signals detected SQ by means of at least one of the noise sensors M1 to M7 may be one preceding explosion or detonation can be identified.
  • the fan runs at a constant speed Speed and thereby generates stationary single tones that as Airborne sound and thus noise signals SQ1 are emitted.
  • These noise signals SQ1 are characterized by its speed and the Number of its rotor blades determined.
  • That through the single tones, which are received as noise signals SQ1, resulting Noise pattern SM1 of the fan is in Figure 2 in the form of a Campbell diagram shown.
  • the Campbell chart shows while functions of two variables - here level above Frequency and time.
  • FIG. 3 shows by way of example a description of the noise source G2 Noise pattern SM2 shown.
  • the noise source G2 the industrial plant 4, e.g. a press shop for Sheet metal processing, presses a molding every second. That here generated noise signal SQ2 has a typical pulse character on. The bandwidth of the associated frequency range runs, for example, from 30 Hz to 6800 Hz.
  • the noise pattern SM2 is exemplary in the form of a Campbell diagram shown.
  • the Campbell diagram for the press shop is characterized by the characteristic single pulses or noise signals SQ2 shaped parallel to the frequency axis of 30 Hz to 6800 Hz at intervals of one second.
  • the representing the respective single pulse or the noise signal SQ2 Line describes the frequency-related volume of the single pulse according to texture scaling.
  • FIG. 4 shows by way of example a noise pattern SM3 describing the noise source G3.
  • B. for a 4-cylinder 4-stroke engine as a sweep ( changing sound) with the second engine order (double engine speed) as a frequency.
  • 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 the residential area 2 (see Figure 1), the distance between the moving noise or noise source G3 (ie the motorcycle 10) and the noise sensor (M6) is approximately constant. Thus, no frequency shift occurs after the acoustic Doppler effect. Thus, the noise pattern SM3 shown in FIG. 4 in the form of a Campbell diagram runs linearly for the noise source G3.
  • the Campbell diagram for the motorcycle 10 and thus for the noise source G3 is described by the characteristic curve of the sweep as a result of the ignition frequency change during the acceleration process.
  • the increase in volume during this speed change is described by texture scaling.
  • FIG. 5 shows by way of example a further noise pattern SM4 for noise signals SQ6 which are received by means of the noise sensor M6 and which describe a combination of buzzing and striking noises.
  • a stone has been clamped, which hits the asphalt once every revolution of the wheel and thereby generates a pulse of the bandwidth 90 Hz to 5 kHz.
  • This beating noise together with the changing firing frequency of the high-revving engine, is detected by the M6 noise sensor in residential area 2.
  • the resulting noise pattern SM4 is shown in Figure 5 in the form of a Campbell diagram.
  • the noise pattern SM4 comprises overlapping the noise source G3 suspect extremelyde noise signals SQ3 and SQ4, ie, the engine and the driving noise.
  • the oblique line between the frequencies f1 and f2 describes the changing firing frequency of the high-revving engine and thus the noise signal SQ3.
  • the lines running parallel to the frequency axis describe the beating noises of the stone on the asphalt and thus the noise signal SQ4.
  • the detected Noise signals SQ1 to SQ4 by means of a sound analysis examined on the basis of signal characteristics such that this Underlying noise source G1 to G4 are assigned and the noise source G1 to G4 underlying parameters P, such as Fan in operation or motorcycle 10 drives or stands, be determined.
  • the sound analysis in dependence from a noise level detected at the noise sensor M6, the has exceeded a noise limit.
  • the Data processing unit 12 includes for limit value monitoring a corresponding agent, e.g. a corresponding one implemented in software function block.
  • the sound analysis can be carried out on the basis of various analyzes, eg time, frequency and / or level analyzes.
  • the sound analysis includes algorithms that the respective noise signal SQ1 to SQ4 for characteristic signal characteristics such. B. fixed frequencies (fan), short broadband pulses (press shop) and Sweeps (accelerating motorcycle) examine. Such an algorithm is z.
  • the characteristic signal characteristics 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 5 detected by the noise sensors M1 to M7 SM4 is done. This comparison makes it possible to assign the sound signals SQ1 to SQ4 detected in the microphone M6 to the source of noise G1 to G4.
  • the detected noise signals SQ1 to SQ4 of the measuring points or noise sensors M1 to M7 as time data deposited in a ring buffer.
  • a threshold or noise limit z. B. on the microphone M6 in residential area 2
  • characteristic Noise or signal characteristics are determined by the Sound analysis according to the graphic aspects in the Campbell diagram analyzed.
  • a pixel in the Campbell diagram (depending on Resolution of the Fast Fourier Transform (FFT)) a volume value of an analyzed frequency and time bandwidth within the coverage areas.
  • Graphical connections (compare noise patterns SM1 to SM4 in FIGS.
  • noise signals SQ1 to SQ4 of other noise sensors M1 to M7 eg. Near-field microphones, directional microphones
  • concrete causers Sound sources G1 to G4 are assigned.
  • a preferred evaluation of detected noise signals SQ1 to SQ4 is e.g. As the fast Fourier transform (called FFT for short) of the microphone signals and the calculation of the so-called A-weighted sound pressure level.
  • a sound or pattern analysis can be several independent Processes include, as evaluation criteria For example, apply different block lengths of the FFT. This exemplary choice of the value of a rating criterion can be from the current process itself or from external specifications depend.
  • the data processing unit 12 to a means for analyzing the parameter P using the Sound analysis the parameter analysis in several iteration steps is done to significant aspects or noise patterns SM1 to SM4 within a detected noise signal Recognize SQ1 to SQ4, e.g. Frequency and Volume of a buzzer, bandwidth, volume and time Distance of a repeated beating noise.
  • the input signal can be analogous to the acoustic pattern recognition also an optical pattern recognition (over time) done.
  • an unillustrated optical is in addition System for capturing optical data of the environment or a room provided. Based on the comparison of the analyzes can describe correlations of causes and effects, be evaluated and saved.
  • Another use case can z. B. in a specific detection specification special Operations exist. This can be z. B. the targeted search after high-revving motorcycles or arriving commercial vehicles be whose occurrence from the detected noise signals SQ1 to SQ4 is filtered out.
  • Another application is e.g.
  • the noise-critical activity nevertheless admitted become.
  • the consideration of data from external systems such as. of optical, meteorological or navigation systems, in sound analysis based on input variables, e.g. Limit value overruns, and / or quality characteristics be determined and controlled.
  • FIG. 6 shows an embodiment of the arrangement 1 for a spatial and temporal assessment of noise sources G1 to G4.
  • the arrangement 1 comprises five noise sensors M1 to M5, which are at a measuring point, e.g. close to each other on one Lamppost on a carriageway or on a carrier in one Factory building, arranged.
  • Four of the five noise sensors M1 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 ball characteristic, on.
  • a the Noise limit exceeding noise signal SQ1 to SQ4 is by means of the noise sensor M5 with omnidirectional characteristic detected.
  • Based on the sound or pattern analysis of the data processing unit 12 becomes at least one signal feature of the noise signal SQ1 to SQ4, e.g.
  • the sound pattern determined during this process SM1 to SM4 will be using the four directional microphones or noise sensors M1 to M4 receiving noise signals SQ1 to SQ4 compared to equality, thereby using that Noise sensor M1 to M4 with the same noise pattern SM1 to SM4 and the strongest level determines the direction can be.
  • FIG. 7 shows a further embodiment of the arrangement 1 with several noise sensors M1 to M5.
  • the noise sensors M1 to M5 are microphones with a vertical omnidirectional characteristic on an inspection site of an industrial plant arranged evenly distributed. Alternatively, these can also in a closed room, e.g. in a workshop of the Industrial plant 4, be arranged.
  • Noise signals SQ1 to SQ4 of the same noise source G1 to G4, e.g. the noise signal SQ1 of a passing vehicle 14 or the noise signal SQ2 Industrial Plant 4 is located locally various locations arranged noise sensors M1 to M5 as a function of the traveled sound path and the resulting sound transit time to different Receive times. Based on the given position of the noise sensors M1 to M5 and the determined sound path or sound propagation time for the respective noise sensor M1 to M5 becomes the position of the noise or sound source G1 or G2, i. the vehicle 14 or the industrial plant 4, determined.
  • the arrangement 1 comprises six noise sensors M1 to M6.
  • the noise sensors M1 to M6 are as microphones with Ball characteristic executed.
  • the noise sensors M1 to M6 are at different measuring points in the study area arranged.
  • the noise sensors M1 to M4 are along the Roadway 8 arranged.
  • the noise sensor M5 is in close range the industrial plant 4 arranged.
  • the noise sensor M6 is located in the residential area 2.
  • the noise limit Exceeding noise detected. That this sound signal SQ1 underlying noise pattern SM1 is with the one received by the other noise sensors M1 to M4 Noise patterns SM1 or received by the sound sensor M5 Noise pattern SM2 compared.
  • Noise patterns SM1 (M1 to M4) SM1 (M6) of different Noise sensors M1 to M4 or M6 is an identification and classification of the noise source SQ1 allows.
  • Based A level analysis is also an evaluation of the detected noise signal SQ1 and thus also an evaluation of the noise source G1 given.
  • a combined Frequency and level analysis taking into account external Influences or data, such as under elimination of Noise or other noise such as rain, one Statement about the state of the noise source G1, e.g. the Vehicle 14 accelerates or brakes, allows.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Measurement Of Mechanical Vibrations Or Ultrasonic Waves (AREA)
  • Investigating, Analyzing Materials By Fluorescence Or Luminescence (AREA)
  • Measurement Of Velocity Or Position Using Acoustic Or Ultrasonic Waves (AREA)
  • Soundproofing, Sound Blocking, And Sound Damping (AREA)

Claims (22)

  1. Procédé de traitement de signaux de bruits (SQ1 à SQ4) d'une source de bruits (G1 à G4), dans lequel plusieurs signaux de bruits (SQ1 à SQ4) sont détectés en relation avec le lieu, examinés au moyen d'une analyse sonore à l'aide de caractéristiques de signal, et des paramètres sur lesquels repose la source de bruits (G1 à G4) sont déterminés, caractérisé en ce que l'analyse sonore est réalisée lors du dépassement d'une valeur seuil de bruits.
  2. Procédé selon la revendication 1, caractérisé en ce qu'en tant que caractéristiques du signal de bruits (SQ1 à SQ4), son amplitude, sa fréquence et/ou phase sont déterminées.
  3. Procédé selon la revendication 1 ou 2, caractérisé en ce que l'analyse sonore est réalisée par une analyse temporelle, de fréquence et/ou de niveau.
  4. Procédé selon l'une quelconque des revendications 1 à 3, caractérisé en ce qu'en tant que paramètres de source de bruits (G1 à G4), son type, sa position et/ou son état sont déterminés.
  5. Procédé selon l'une quelconque des revendications 1 à 4, caractérisé en ce que dans l'analyse sonore réalisée à la suite du dépassement d'une valeur seuil de bruits, un déclencheur (trigger) est utilisé pour conserver une mémoire temporaire à rotation circulaire.
  6. Procédé selon l'une quelconque des revendications 1 à 5, caractérisé en ce qu'au moins l'une des caractéristiques de signal du signal de bruits (SQ1 à SQ4) est déposée sous la forme d'un motif de bruits (SM1 à SM4).
  7. Procédé selon l'une quelconque des revendications 1 à 6, caractérisé en ce qu'au moins l'une des caractéristiques de signal du signal de bruits (SQ1 à SQ4) est comparée à des motifs (SMa à SMz) de bruits stockés pour déterminer et affecter des paramètres de la source de bruits (G1 à G4) d'origine.
  8. Procédé selon l'une quelconque des revendications 1 à 7, caractérisé en ce que des données externes sont prises en compte, en particulier des données météorologiques, des données optiques, des données temporelles, des paramètres d'exploitation.
  9. Procédé selon l'une quelconque des revendications 1 à 8, caractérisé en ce qu'un système à auto-apprentissage est utilisé pour déterminer et classer les caractéristiques de signal du signal de bruits (SQ1 à SQ4) et/ou les paramètres de la source de bruits (G1 à G4).
  10. Procédé selon l'une quelconque des revendications 1 à 9, caractérisé en ce que les caractéristiques de signal et/ou les paramètres sont acheminés vers un système de commande et/ou de régulation.
  11. Dispositif (1) de traitement de signaux de bruits (SQ1 à SQ4) d'une source de bruits (G1 à G4), dans lequel sont prévues une pluralité de capteurs de bruits (M1 à M7) pour détecter, en relation avec le lieu, des signaux de bruits (SQ1 à SQ4) et une unité centrale de traitement de données (12) pour l'analyse sonore des signaux de bruits (SQ1 à SQ4) au moyen d'au moins une caractéristique de signal et pour déterminer au moins un paramètre caractérisant la source de bruits (G1 à G4) caractérisé en ce qu'un moyen de surveillance d'une valeur seuil de bruits est prévu.
  12. Dispositif selon la revendication 11, caractérisé en ce que des microphones directionnels sont prévus en tant que capteurs de bruits (M1 à M7).
  13. Dispositif selon la revendication 11 ou 12 caractérisé en ce qu'un moyen de détermination de l'amplitude, de la fréquence et/ou la phase du signal de bruits (SQ1 à SQ4) est prévu.
  14. Dispositif selon l'une quelconque des revendications 11 à 13, caractérisé en ce qu'un moyen de détermination du type, de la position et/ou de l'état de la source de bruits (G1 à G4) est prévu.
  15. Dispositif selon l'une quelconque des revendications 11 à 14, caractérisé en ce qu'une mémoire de données est prévue pour stocker au moins l'une des caractéristiques de signal du signal de bruits (SQ1 à SQ4) sous la forme d'un motif de bruits (SM1 à SM4).
  16. Dispositif selon l'une quelconque des revendications 11 à 15, caractérisé en ce qu'une base de données comprenant une bibliothèque de motifs de bruits est prévue.
  17. Dispositif selon l'une quelconque des revendications 11 à 16, caractérisé en ce qu'un moyen de comparaison d'au moins l'une des caractéristiques de signal du signal de bruits (SQ1 à SQ4) à des motifs stockés de bruits (SMa à SMz) pour déterminer et affecter des paramètres de la source de bruits (G1 à G4) d'origine est prévu
  18. Dispositif selon l'une quelconque des revendications 11 à 17, caractérisé en ce qu'un système optique est prévu pour la détection de données optiques.
  19. Dispositif selon l'une quelconque des revendications 11 à 18, caractérisé en ce qu'une unité d'enregistrement est prévue pour la détection de données météorologiques.
  20. Dispositif selon l'une quelconque des revendications 11 à 19, caractérisé en ce qu'un moyen est prévu pour déterminer et classer les caractéristiques de signal du signal de bruits (SQ1 à SQ4) et/ou les paramètres de la source de bruits (G1 à G4) à l'aide d'un système à auto-apprentissage.
  21. Dispositif selon l'une quelconque des revendications 11 à 20, caractérisé en ce qu'un système externe de commande et/ou de régulation est prévu.
  22. Dispositif selon l'une quelconque des revendications 11 à 21, caractérisé en ce qu'un moyen d'analyse des paramètres (P) par une analyse sonore en plusieurs étapes d'itération pour reconnaítre des aspects significatifs au sein d'un bruit est prévu.
EP01991835A 2000-12-22 2001-12-12 Procede et dispositif de traitement de signaux sonores issus d'une source de bruits Expired - Lifetime EP1344198B1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
DE10064756A DE10064756A1 (de) 2000-12-22 2000-12-22 Verfahren und Anordnung zur Verarbeitung von Geräuschsignalen einer Geräuschquelle
DE10064756 2000-12-22
PCT/EP2001/014623 WO2002052522A1 (fr) 2000-12-22 2001-12-12 Procede et dispositif de traitement de signaux sonores issus d'une source de bruits

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EP1344198A1 EP1344198A1 (fr) 2003-09-17
EP1344198B1 true EP1344198B1 (fr) 2004-07-14

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US (1) US20040081322A1 (fr)
EP (1) EP1344198B1 (fr)
JP (1) JP4167489B2 (fr)
BR (1) BR0116418A (fr)
DE (2) DE10064756A1 (fr)
ES (1) ES2223950T3 (fr)
MX (1) MXPA03005620A (fr)
WO (1) WO2002052522A1 (fr)

Families Citing this family (29)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2003015456A2 (fr) * 2001-08-10 2003-02-20 Seti Média Inc. Systeme et procede de surveillance de la pollution sonore
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 (fr) * 2008-09-30 2010-04-08 Vestas Wind Systems A/S Maîtrise des émissions sonores d’une ferme éolienne
US20100082180A1 (en) * 2008-10-01 2010-04-01 Honeywell International Inc. Errant vehicle countermeasures
US8983677B2 (en) * 2008-10-01 2015-03-17 Honeywell International Inc. Acoustic fingerprinting of mechanical devices
US9928824B2 (en) 2011-05-11 2018-03-27 Silentium Ltd. Apparatus, system and method of controlling noise within a noise-controlled volume
EP2707871B1 (fr) * 2011-05-11 2020-09-09 Silentium Ltd. Système et procédé de contrôle du bruit
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
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
DE102015119594A1 (de) * 2015-11-13 2017-05-18 Albert Orglmeister Verfahren zur Eliminierung von thermischen Störungen bei der Infrarot- und Video-Brandfrüherkennung
US11959798B2 (en) * 2017-04-11 2024-04-16 Systèmes De Contrôle Actif Soft Db Inc. System and a method for noise discrimination
JP7241030B2 (ja) * 2017-05-16 2023-03-16 シグニファイ ホールディング ビー ヴィ インテリジェント照明を用いたノイズフロー監視及び音位置特定
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
EP3879938A1 (fr) * 2020-03-11 2021-09-15 Tridonic GmbH & Co KG Réseau de luminaires
DE102020110659A1 (de) 2020-04-20 2021-10-21 Bayerische Motoren Werke Aktiengesellschaft Betreiben eines Fahrzeugs sowie Fahrzeug und System
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
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

Family Cites Families (13)

* Cited by examiner, † Cited by third party
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

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MXPA03005620A (es) 2004-03-18
BR0116418A (pt) 2003-12-30
DE10064756A1 (de) 2002-07-04
WO2002052522A1 (fr) 2002-07-04
ES2223950T3 (es) 2005-03-01
JP4167489B2 (ja) 2008-10-15
EP1344198A1 (fr) 2003-09-17
JP2004517309A (ja) 2004-06-10
DE50102884D1 (de) 2004-08-19
US20040081322A1 (en) 2004-04-29

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