METHOD AND SYSTEM FOR SOURCE SELECTIVE REAL-TIME MONITORING AND MAPPING OF ENVIRONMENTAL NOISE

• US 20150110276A1
• Filed: 12/17/2012
• Published: 04/23/2015
• Est. Priority Date: 04/03/2012
• Status: Active Grant

• Current Assignee: Budapesti Muszaki Es Gazdasagtudomanyi Egyetem
• Original Assignee: Budapesti Muszaki Es Gazdasagtudomanyi Egyetem
• Inventors: Gereb, Gabor
• Granted Patent: US 9,510,123 B2
• Time in Patent Office: Days
• US Class Current: 381/56
• CPC Class Codes: G01H 3/125 for representing acoustic field distribution using optical means G01H9/002; sonar systems for imaging G01S7/56, G01S15/89; acoustic holography G03H3/00
• CPC Class Codes: H04R 29/008 Visual indication of individual signal levels visual indication of stereophonic sound image H04S7/40

Abstract

A method for source selective real-time monitoring and mapping of environmental noise, comprising the steps of  identifying sources in the area;  designing places for the monitoring stations;  creating a data collecting and data processing centre;  measuring the noise impact, and observation of the sources with the sensors;  defining the noise propagation;  assemblying the monitoring stations including a sound measuring device, a computing unit and a communication unit;  determining the resultant noise impact prevailing in the respective measurement points;  determining the sources dominant in the individual moments on the basis of the data of the sensors;  determining the average noise impact of the respective sources for a longer period;  obtaining an average noise impact;  extending the measurement into a noise impact map;  calculating the effective noise impact of every noise source in every point of the area for every period;  producing the effective noise impact map of the respective periods.

Claims

1. A method for source selective real-time monitoring and mapping of environmental noise, comprising the steps of

surveying the area (k11), in the course of which the sources (d11) must be identified which affect the noise impact (d31) prevailing in the respective points of the area (k11);

designing, in view of the sources (d11), one or several measurement point(s) (d13) where the monitoring stations (F1) will be placed;

after the installation of one or several monitoring station(s) (F1), creating a data collecting and data processing centre (F2),

measuring the noise impact in the measurement points (d13), and observation of the respective sources (d11) with the sensors (M2, M3, K1, É

1);

characterised in that

as the case may be, the sources (d11) are grouped and they are treated together in subsequent separations;

the noise propagation conditions of the area (k11) are defined by noise modelling, during which the noise impact (d31) differences prevailing between the respective points of the area (k11) are determined for each source (d11),

the one or several measurement point(s) where the monitoring stations (F1) are placed are designated in view of the combined knowledge of sources (d11) and noise propagation conditions (d12);

in the course of the above, measurement points (d13) are defined so that each of the previously determined sources (d11) cause a significant noise impact in at least one measurement point (d13);

subsequently, the monitoring stations (F1) are assembled so that

a calibrated sound pressure level measuring device, a computing unit capable of the pre-processing of the data and a communication unit capable of the transmission of the data are assigned to each monitoring station (F1), and

it is ensured that the sources (d11) contributing to the resultant noise impact (d31) in a dominant way be known at every moment and in every cycle;

following the installation of one or several monitoring station(s) (F1), during the creation of a data collecting and data processing centre (F2)

firstly, the resultant noise impact (d31) prevailing in the respective measurement points is determined by the summary of the data of one or several sound pressure level measuring devices,

secondly, the sources (d11) dominant in the individual moments in time are determined on the basis of the data of the one or several sensors located on the one or several stations,

during which the dominance of the sources (d11) is inferred to based on the specific parameter combinations, by putting all the data of the sensors (É

) into a single parameter space, and a decision is taken;

then on the basis of the resultant noise impact (d31) known for the respective moments and the also known source dominance, the average noise impact (d36) of the respective sources (d11) is determined selectively for a longer period;

during which the noise impact measured at a given moment in time is assigned to the noise source (d11) identified by the previous decision, and the datum is stored in the summing unit of the noise source (d11),

at the end of a predefined period, the summing units are aggregated, the sum is divided over the entire period, and the average noise impact (d36) is obtained;

hence the specific average noise impact of every noise source (d11) is known for every period;

then the measurement is extended into a noise impact map (d38),

so that, since the noise impact (d36) of every noise source (d11) is known for every period, and during installation, the noise impact difference between the points of the area (k11) have been determined also for every noise source (d11), the effective noise impact of every noise source (d11) in every point of the area (k11) is calculated for every period,

subsequently, those impacts are summarised in every point, every period, for all the noise sources (d11), and on the basis of the resultant noise impact levels, the effective noise impact map (d38) of the respective periods is produced.

2. The method according to claim 1, characterised in that the noise impact (d36) is measured continuously in the measurement points and the respective sources (d11) are observed continuously by the sensors (É

).

3. The method according to claim 1 characterised in that the periodical noise impact of the respective sources (d11) is determined and the noise impact map (d38) is calculated.

4. The method according to claim 1 characterised in that the noise impact map (d38) is updated in real time, by period, and the previous data are stored.

5. The method according to claim 1 characterised in that a posteriori statistical analysis is performed on the basis of the previously stored data.

6. The method according to claim 1 characterised in that the data collected in the measurement point are extended a posteriori into a noise impact map (d38) by using the noise impact difference values.

7. The method according to claim 1 characterised in that the noise sources (d11) are identified on the basis of their spatial location, with a direction-sensitive microphone system (M2, M3), based on their frequency and time characteristics and on visual signals.

8. The method according to claim 1 characterised in that the noise impact maps (d38) valid in the specific periods are produced by assigning different colours to the resultant noise impact levels.

9. The method according to claim 1 characterised in that, during installation, the identifier of the noise source (d11) which is dominant at the given moment is loaded manually, simultaneously with the measurement, and the sample series obtained that way is associated with the data of sensors (É

) and the system of decision-making rules is developed.

10. A system for source selective real-time monitoring and mapping of environmental noise, comprising:

one or several measurement points comprising an environmental noise detecting monitoring station (F1);

a communication device transmitting the data collected by the (F1) monitoring station;

a processing device receiving the data transmitted by the communication device;

where the processing device is equipped with a storage means for storing the received and the processed data, respectively;

display means associated with the processing device;

characterised in that

the monitoring station (F1) detecting environmental noise comprises (E) sensors monitoring the noise sources in a selective way;

the monitoring station (F1) detecting environmental noise comprises a calibrated sound pressure level measurement device, a computing unit capable of the pre-processing of the data and a communication unit capable of forwarding the data;

the processing unit is designed as a processing unit which determines the average noise impact of the respective sources based on the resultant noise impact known for the specific moments in time and the also known source dominance for a longer period in a selective way, and in the meantime it assigns the nose impact measured at a given moment to a noise source (d11) identified on the basis of a previous decision and stores the datum in the summing unit of the noise source (d11).