KR102197812B1 - Noise monitoring system for localization and the method thereof - Google Patents

Abstract

The present invention relates to a noise monitoring system for measuring a noise level by detecting noise-related information around a room in a building, and estimating a generation source and direction of noise, and a method therefor. The noise monitoring system comprises: a noise level measurement unit measuring a sound pressure level (SPL) through a noise signal detected through a microphone array to measure noise level data for the noise signal; a noise source location estimation unit estimating noise source location data for a direction and location of a noise generation source using a difference in arrival time in accordance with arrival time of the noise signal detected by the microphone array; and a communication unit transmitting the noise level data and the noise source location data to an interlocked mobile device.

Description

Noise monitoring system and its method through positioning {NOISE MONITORING SYSTEM FOR LOCALIZATION AND THE METHOD THEREOF}

The present invention relates to a noise monitoring system and method thereof through location designation, and more particularly, to a system and method for measuring noise level by detecting noise-related information around the interior of a building, and estimating the source and direction of noise. It is about.

Due to the high population density, apartment occupancy rates are very high in many countries. Unfortunately, as the number of single-person households increased, the demand for apartments increased significantly, and the houses share floors and walls. At this time, the inevitable problems arising from the high apartment occupancy rate are inter-floor noise between neighboring residents and indoor ambient noise. In many countries, floor noise is a serious social problem that causes arson, violence, and murder. Various governments and WHOs have established and quantitatively defined legal standards related to indoor ambient noise. Legal standards specify different threshold levels of ambient noise in rooms, depending on the type and time of occurrence.

The main challenge in the current situation is the lack of specialized equipment for measuring and recording ambient noise in the room. Currently available noise meters allow users to measure only the noise level. In addition to the noise level, there are more important data such as the location of the noise source and the type of noise that can be used as mood data in case of a dispute, but the existing technology did not consider the location of the noise source.

Therefore, a technique for estimating the noise level and the location and direction of the noise source was required.

Korean Patent Laid-Open Patent No. 10-2015-0144456 (published on Dec. 28, 2015), “An apparatus and method for managing interfloor noise in apartment houses”

An object of the present invention is to propose a noise monitoring system that detects not only a noise level but also a three-dimensional direction of a noise generating source related to indoor ambient noise.

In addition, an object of the present invention is to determine the location of ambient noise indoors by using a multiple monitoring system by transmitting data related to the noise level and the three-dimensional direction of the noise generating source to a smart device.

The noise monitoring system according to an embodiment of the present invention includes a noise level measuring unit for measuring noise level data for the noise signal by measuring a sound pressure level (SPL) through a noise signal detected through a microphone array, and detected by the microphone array. A noise source location estimation unit that estimates the noise source location data for the direction and location of the noise source by using the arrival time difference according to the arrival time of the noise signal, and transmits the noise level data and the noise source location data to an interlocked mobile device. It includes a communication department.

The noise level measurement unit converts the analog audio signal detected through the microphone array into the noise signal, which is digital data, and applies an A-weighted value in the frequency domain after sampling in a fast Fourier transform (FFT) to obtain an effective value (RMS). It is calculated, and the sound pressure level (SPL) of the noise can be calculated by applying a time weight.

The noise level measuring unit may measure the noise level data by using the calculated sound pressure level SPL as a standard measurement unit of noise.

The noise source position estimation unit measures the time difference of arrival (TDoA) according to the arrival time of the noise signal from the pair of microphones in the microphone array including a plurality of microphones, and a direction angle from the difference in arrival time Can be identified.

The noise source location estimation unit may estimate the noise source location data of the three-dimensional direction and location of the noise signal by calculating angle information of an azimuth and altitude based on the difference in arrival time and the direction angle.

The noise source location estimating unit may estimate the noise source location data that minimizes an error by passing through a low pass filter.

The noise source position estimating unit measures all voltage values in each of the plurality of microphones configured in the microphone array at an initial time, and calculates an average value of the voltage values measured in a noise-free environment to determine the offsets of the plurality of microphones. I can.

The communication unit may transmit the noise level data and the noise source location data to the mobile device through Bluetooth Low Energy.

The multi-monitoring system according to another embodiment of the present invention measures noise level data through sound pressure level (SPL) measurement through a noise signal detected through a microphone array, and uses the difference in arrival time according to the arrival time of the noise signal. And a noise monitoring system for estimating noise source position data for the direction and position of the noise source, and a mobile device for displaying the noise level data and the noise source position data received from the noise monitoring system.

Based on the noise level data, the noise source location data, and impact data detected through a piezoelectric element (PZT) sensor array included in the noise monitoring system, the mobile device may display result data on the noise level and the location of the noise source. I can.

The mobile device may determine a noise location for the noise signal through an intersection of two or more lines based on data received from a plurality of noise monitoring systems.

The noise monitoring operation method according to an embodiment of the present invention includes measuring sound pressure level (SPL) through a noise signal detected through a microphone array and measuring noise level data for the noise signal, the noise detected by the microphone array. And estimating noise source location data for a direction and location of a noise source by using the difference in arrival time according to the arrival time of the signal, and transmitting the noise level data and the noise source location data to an interworking mobile device.

The measuring of the noise level data includes converting the analog audio signal sensed through the microphone array into the noise signal, which is digital data, sampling in a fast Fourier transform (FFT) and then applying an A-weight in the frequency domain to an effective value. (RMS) is calculated, and the sound pressure level (SPL) of the noise can be calculated by applying a time weight.

The step of estimating the noise source location data includes measuring the time difference of arrival (TDoA) according to the arrival time of the noise signal from a pair of microphones in the microphone array including a plurality of microphones, and the arrival time You can identify the direction angle from the difference.

In the estimating of the noise source location data, the noise source location data of the three-dimensional direction and location of the noise signal may be estimated by calculating the azimuth and altitude angle information based on the arrival time difference and the direction angle. .

In the transmitting of the mobile device, the noise level data and the noise source location data may be transmitted to the mobile device through Bluetooth Low Energy.

According to an embodiment of the present invention, it is possible to detect not only the noise level but also the three-dimensional direction of a noise generating source related to indoor ambient noise.

In addition, according to an embodiment of the present invention, by transmitting data related to the noise level and the three-dimensional direction of the noise source to the smart device, it is possible to determine the location of ambient noise in the room using a multiple monitoring system.

1 is a block diagram showing a detailed configuration of a noise monitoring system according to an embodiment of the present invention.
2 shows an application example of a noise monitoring system according to an embodiment of the present invention.
3 is a flowchart illustrating a noise level measuring unit measuring a sound pressure level (SPL) according to an embodiment of the present invention.
4 illustrates frames and subframes for reducing uncertainty according to an embodiment of the present invention.
5 is a diagram illustrating an azimuth and altitude output angle according to an embodiment of the present invention.
6 is a diagram illustrating an angle of a direction vector of a noise source according to an embodiment of the present invention.
7 is a flowchart illustrating a microphone fluctuation correction according to an embodiment of the present invention.
8 is a block diagram of a multi-monitoring system according to another embodiment of the present invention.
9 is a flowchart illustrating a method of operating noise monitoring according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. However, the present invention is not limited or limited by the embodiments. In addition, the same reference numerals shown in each drawing denote the same member.

In addition, terms used in the present specification are terms used to properly express preferred embodiments of the present invention, which may vary depending on the intention of viewers or operators, or customs in the field to which the present invention belongs. Accordingly, definitions of these terms should be made based on the contents throughout the present specification.

1 is a block diagram showing a detailed configuration of a noise monitoring system according to an embodiment of the present invention.

Referring to FIG. 1, a noise monitoring system according to an exemplary embodiment of the present invention detects information related to indoor ambient noise in a building, measures a noise level, estimates a source and direction of noise, and transmits it.

To this end, the noise monitoring system 100 according to an embodiment of the present invention includes a noise level measurement unit 110, a noise source position estimation unit 120, and a communication unit 130.

2 shows the appearance of the noise monitoring system 100 according to an embodiment of the present invention. Referring to FIG. 2, the noise monitoring system 100 according to the embodiment of the present invention includes a plurality of microphone arrays on a substrate. (Mic Array) and piezoelectric element sensor array (PZT Array).

The noise monitoring system 100 according to an embodiment of the present invention includes a microphone array in which a plurality of microphones are arranged on a substrate, and measures a noise signal detected in the air at each location of the microphone. At this time, the microphone may be a microphone or a microphone sensor for noise measurement, and the air signal data detected in the air and the arrival time of the air signal data are formed on the front surface of the wall-mounted substrate to measure the air transmitted noise signal. I can.

A plurality of microphones may be arranged on the substrate. For example, the microphones may be arranged in the form of a two-dimensional matrix on the front surface of the substrate, or may be arranged in a multidirectional three-dimensional matrix form, and may be in the form of an array with preset intervals. . Since each of the plurality of microphones arranged on the front surface of the substrate is arranged differently from each other, the time at which the noise generated from the same noise source enters the microphone acquires a different value except when there is no difference in the distance from the noise source. . Accordingly, the incident direction of the noise can be detected from the difference between the distance between the microphones and the noise arrival time from each microphone.

According to the embodiment, the noise monitoring system 100 according to the embodiment of the present invention arranges and installs six microphones in a two-dimensional matrix form, so that the lower side incident from the lower direction is based on the horizontal plane between the first row and the second row. Noise and upper noise incident from the upper direction can be distinguished, and left noise incident from the left direction and right noise incident from the right direction can be distinguished based on the vertical plane of the second row. Accordingly, the noise monitoring system 100 according to an exemplary embodiment of the present invention can more accurately distinguish the direction and position of the noise at 360 degrees. However, in order to more accurately obtain the incident direction of noise, a larger number of microphones may be used, and a smaller number may be used depending on the applied scale and volume, so the number is not limited thereto.

In addition, the noise monitoring system 100 according to an embodiment of the present invention includes a piezoelectric element (PZT) sensor array. The piezoelectric element (PZT) sensor constituting the piezoelectric element sensor array is formed on the back side of a wall-mounted substrate and directly impacts by using the arrival time of the shock signal data and the shock signal data detected by direct impact such as pressure or wall vibration. You can measure the noise.

A plurality of piezoelectric element sensors may be arranged on the substrate. For example, the piezoelectric sensor may be arranged in a two-dimensional matrix form on the back side of a substrate, or may be arranged in a multidirectional three-dimensional matrix form. It can be in the form of (array). Since each of the plurality of piezoelectric element sensors disposed on the back of the substrate is arranged in different positions, the time when a direct impact from the same noise source enters each sensor module is different, except when there is no difference in the distance from the noise source. You get the value.

The piezoelectric element sensor is attached to a ceiling, a wall, a floor, etc. and generates electric charge by a direct impact applied from the outside, and can convert a response from vibration into a voltage signal and output it. Accordingly, the sensor module can receive the shock signal data from the vibration according to the intensity of the direct impact detected at each location, and detect the location and direction of the noise from the difference between the distance between the sensor modules and the noise arrival time at each sensor module. can do.

According to the embodiment, the noise monitoring system 100 according to the embodiment of the present invention arranges and installs four piezoelectric element sensors in the form of a two-dimensional matrix, so that the incident from the lower direction is based on the horizontal plane between the first row and the second row. It is possible to distinguish between the lower noise and the upper noise incident from the upper direction, and the left noise incident from the left direction and the right noise incident from the right direction based on the vertical plane of the second row. Accordingly, the noise monitoring system 100 according to an exemplary embodiment of the present invention can more accurately distinguish the direction and position of the noise at 360 degrees. However, in order to more accurately obtain the incident direction of noise, a larger number of sensor modules may be used, and a smaller number may be used depending on the applied scale and volume, so the number is not limited thereto.

The microphone array and piezoelectric element sensor array of the noise monitoring system 100 according to an exemplary embodiment of the present invention may be connected to an integrated circuit (IC) circuit formed on a substrate to form a patch-type structure. The IC circuit can process the functions of filtering, amplifying, digitizing and processing signals by making full use of the integration technology, and depending on the embodiment, it is an integrated and multifunctional IC sensor that processes signals within a substrate. May be. In this case, the substrate may be a material detachable to the ceiling, wall and floor of the building, and thus the type, shape and shape of the substrate are not limited.

The noise monitoring system 100 according to an embodiment of the present invention uses an ARM 32-bit Cortex-M4 MCU-based STM32F407IG MCU operating at 120 MHz, and a 12-bit analog-to-digital converter (ADC) to convert analog audio signals into digital data. ) Is used. Additionally, the noise monitoring system 100 according to an embodiment of the present invention includes 2MB of additional SRAM to improve computing performance, and includes an external flash memory capable of storing noise data over a long period of time.

In addition, other components such as humidity, temperature sensor, and Bluetooth module configured in the noise monitoring system 100 according to an embodiment of the present invention may be used to connect a mobile device. Floor noise measurement function and sound positioning function around the room are part of the designed device, and output information (eg, noise level data and noise source location data) of the original data can be transmitted to a mobile device and displayed in real time. As shown in (b), it may be displayed through a display.

Referring to FIG. 1, the noise level measurement unit 110 of the noise monitoring system 100 according to an embodiment of the present invention measures a sound pressure level (SPL) through a noise signal detected through a microphone array, Measure level data.

Hereinafter, a noise level measuring unit 110 according to an embodiment of the present invention will be described in more detail with reference to FIGS. 3 and 4.

3 is a flowchart illustrating a flow diagram of a noise level measuring unit for measuring a sound pressure level (SPL) according to an exemplary embodiment of the present invention, and FIG. 4 illustrates a frame and a subframe for reducing uncertainty according to an exemplary embodiment of the present invention. .

The noise level measurement unit 110 of the noise monitoring system 100 according to an embodiment of the present invention measures a sound pressure level (SPL) through a noise signal detected through a microphone array to measure noise level data for a noise signal. Measure

The noise level measurement unit 110 converts the analog audio signal detected through the microphone array into a noise signal, which is digital data, and applies an A-weighted value in the frequency domain after sampling in a fast Fourier transform (FFT) to obtain an effective value (RMS). Is calculated, and the sound pressure level (SPL) of the noise can be calculated by applying a time weight. Here, the noise level measurement unit 110 may measure noise level data by using the calculated sound pressure level SPL as a standard measurement unit of noise.

More specifically, the analog audio signal is sensed through the microphone array and converted into an analog voltage signal. At this time, the sensitivity of the microphone is -45dB and the operating voltage is 2V. The analog voltage signal is sampled through an ADC and converted to digital data, and a fast Fourier transform (FFT) is performed on the digitized samples. In the frequency domain, A-weighting is applied to take into account different human perceptions of different frequency levels.

Thereafter, the RMS value (RMS) of the noise signal is calculated, time weight is applied to smooth the displayed data, and finally the sound pressure level (SPL) of the noise is calculated.

Here, the sound pressure level (SPL) is used as a standard measurement unit of noise, and is defined by an equation such as [Equation 1] below.

[Equation 1]

Here, Po represents the reference sound pressure in the air with a value of 20 μPa. The reference sound pressure is considered to be the lower limit of human hearing, which is 0 dB at the sound pressure level (SPL).

Referring to FIG. 3, the analog audio signal sensed through the microphone 310 constituting the microphone array is amplified by the amplifier 320.

The amplified voltage signal by the amplifier 320 is sampled (Sampling, 330) in the 12-bit ADC of the sensor board. The sampling rate is 200 kHz in the noise monitoring system 100 according to the proposed embodiment of the present invention. It uses a much higher sampling rate than the conventional audio sampling rate (44.1kHz), and is used because it requires a sufficient sampling frequency to compensate for very short distances between microphones.

Thereafter, the noise level measurement unit 110 applies an A-weighting 350 in the frequency domain after sampling using a Fast Fourier Transform (FFT).

The A-weight 350 is applied to account for different sensitivities of hearing for different frequencies of sound. Through the following [Equation 2] and [Equation 3], the noise level measurement unit 110 calculates an appropriate value of A(f) for each frequency component and applies the A-weighted value 350 to the frequency domain.

[Equation 2]

[Equation 3]

Accordingly, the noise level measurement unit 110 follows the A-weighting value 350 and then the time-weighting 370 applied to the time series of the A-weighted signal's root mean square (RMS, 360) voltage. Calculate.

For example, if the data change rate is too fast, the displayed data cannot be read. Therefore, the time weight 370 is required to smooth the displayed output data. At this time, the time weight 370 is also referred to as an exponential average, and serves as a low pass filter to remove high frequency noise. In the noise monitoring system 100 according to an embodiment of the present invention, the time weight of the RMS voltage is expressed by an equation such as [Equation 4] below.

[Equation 4]

Here, α represents the smoothing coefficient, and 0 <α <1. A lower value of α may indicate a smoother display, and a value of α is given as [Equation 5] below.

[Equation 5]

Here, ΔT represents the sampling rate of data, and τ represents time as a constant.

Two types of time constants are often used to indicate the sound pressure level (SPL), for example, F(Fast, 125ms) and S(Slow, 1sec). Both time constants can be implemented in the proposed sound pressure level (SPL) measurement unit.

As a final step, the noise level measurement unit 110 calculates 380 a sound pressure level (SPL) of the noise signal through Equation 6 below.

[Equation 6]

Here, V _REF represents the output RMS voltage when the pressure level of the noise signal is equal to the reference sound pressure Po. V _REF is determined by the microphone sensitivity and the gain of the amplifier circuit.

The sound pressure level (SPL) calculation in positioning takes about 10 milliseconds. However, this is too short and may contain many errors. In order to make such an error, the noise monitoring system 100 according to an embodiment of the present invention uses a weighted moving average and a subframe average for a frame as shown in FIG. 4.

The subframe consists of 100 measurement values and an average value used to calculate a weighted moving average value in the frame. The actual sound pressure level (SPL) can be calculated as shown in [Equation 7] below.

[Equation 7]

At this time, the measured actual sound pressure level (SPL) and location information are transmitted to the mobile device through the communication unit 130 at 1 second intervals.

Referring back to FIG. 1, the noise source position estimation unit 120 of the noise monitoring system 100 according to an embodiment of the present invention uses the difference in arrival time according to the arrival time of the noise signal detected by the microphone array. Estimate noise source location data for direction and location.

Hereinafter, the noise source position estimation unit 120 according to an embodiment of the present invention will be described in more detail with reference to FIGS. 5 to 7.

5 is a diagram illustrating an azimuth and altitude output angle according to an embodiment of the present invention, FIG. 6 is a diagram illustrating an angle of a noise source direction vector according to an embodiment of the present invention, and FIG. 7 It shows a flow chart for correcting a microphone fluctuation according to an embodiment of the present invention.

The noise source location estimation unit 120 of the noise monitoring system 100 according to an embodiment of the present invention uses the difference in arrival time according to the arrival time of the noise signal detected by the microphone array, and the location of the noise source relative to the direction and location of the noise source. Estimate the data.

In a microphone array including a plurality of microphones, the noise source position estimation unit 120 measures a time difference of arrival (TDoA) according to the arrival time of the noise signal from the pair of microphones, and calculates a direction angle from the difference in arrival time. Can be identified. Accordingly, the noise source location estimating unit 120 may calculate the azimuth and altitude angle information based on the arrival time difference and the direction angle to estimate the noise source location data of the three-dimensional direction and location of the noise signal.

Referring to FIG. 5, the noise source position estimation unit 120 measures a Time Difference of Arrival (TDoA) through at least two pairs of microphones among the microphone arrays, and measures the estimated time difference of arrival. The direction angle is identified in Arrival; TDoA). Accordingly, the noise source position estimation unit 120 may estimate two output angles representing an azimuth and a direction (or height, elevation) in the local Cartesian coordinates.

In the local Cartesian coordinates, the angles of the noise source direction vectors with respect to the x-axis, y-axis, and z-axis are as shown in FIG. 6.

Referring to FIG. 6, α, β, and γ represent the direction angles of the noise source vector with respect to the x, y, and z axes, respectively, and φ and θ represent the azimuth and elevation, respectively. At this time, the present invention attempts to identify the azimuth angle φ and elevation θ at the direction angles α and β.

Accordingly, the values of α and β in the estimated Time Difference of Arrival (TDoA) in each microphone pair are calculated through the following [Equation 8] and [Equation 9].

[Equation 8]

[Equation 9]

Here, the relationship between the direction cosines of the noise direction vectors is as shown in [Equation 10] below.

[Equation 10]

In addition, the relationship between the elevation θ and the z-axis direction angle γ is as shown in [Equation 11] below.

[Equation 11]

Thus, the expression derived for altitude through [Equation 10] and [Equation 11] is the same as [Equation 12].

[Equation 12]

Here, the tangent of the azimuth is expressed as [Equation 13] below, and the expression of the azimuth angle is expressed as [Equation 14] below.

[Equation 13]

[Equation 14]

Accordingly, if only two pairs of microphones are used to identify altitude, the ambiguity between the z> 0 plane and the z <0 plane can be avoided. Furthermore, one additional pair of microphones can be used along the z-axis to allow for full three-dimensional spatial positioning. The noise source location estimation unit 120 determines whether the noise source is in the space z> 0 or the space z <0 through the time difference of arrival (TDoA) code of the microphone pair 3 (mic 4 and 5).

Thus, considering this problem, the elevation is expressed as follows.

[Equation 15]

Accordingly, the noise source position estimation unit 120 can determine the azimuth and altitude within a very short time.

However, since there may be various errors in accurately determining the location of the noise source, the noise source location estimating unit 120 may estimate noise source location data that minimizes the error by passing through a low pass filter.

The noise source position estimating unit 120 measures all voltage values in each of the plurality of microphones configured in the microphone array at an initial time, and calculates an average value of the voltage values measured in a noise-free environment to calculate the offset of the plurality of microphones. You can decide.

Specifically, in most cases, sensors and microphones have a problem of sensor-to-sensor change. That means that all microphones have different features and outputs, despite having the same readout circuit. This difference causes some errors in determining the Time Difference of Arrival (TDoA) derived by cross-correlation.

Accordingly, the noise source position estimation unit 120 may correct the microphone-to-microphone fluctuation at an initial time through the flowchart shown in FIG. 7. Referring to FIG. 7, the noise source location estimation unit 120 measures all voltage values from all microphones by the noise monitoring system 100 at an initial time (read Voltages from all Mic.), and calculates an average value in a noise-free environment. Calculate Average Value. The mic-to-mic variation can then be corrected by determining the offsets from all mics from the average value (Calculate offsets from all Mic. Using Avg.).

Referring back to FIG. 1, the communication unit 130 of the noise monitoring system 100 according to an embodiment of the present invention transmits noise level data and noise source location data to an interlocked mobile device.

The communication unit 130 may transmit noise level data and noise source location data to the mobile device through Bluetooth Low Energy.

For example, the communication unit 130 may be a wireless data transport device or a wireless transmission device, and the communication module includes at least one of the interlayer noise measurement device 100 and an external server, a wall pad, and a mobile device. It may be configured to implement any wired and/or wireless communication interface so that information exchange with one can be performed. In this case, the communication unit 130 may transmit/receive data and control commands with different transmission bandwidths, and uses low-power Bluetooth technology (BLE) according to coverage.

The mobile device according to an embodiment of the present invention may be a portable terminal device possessed by a user, and may be a device in which an application related to the noise monitoring system 100 according to an embodiment of the present invention is installed. For example, the mobile device may be at least one of a smartphone, a desktop PC, a mobile terminal, a PDA, a notebook computer, a tablet PC, and a wearable device. Furthermore, the mobile device may include a display in the form of a touch screen capable of receiving a user's selection input and performing an operation of a predetermined set of functions through a screen including a touch-sensing area. Since the device may include a physical button or a virtual button, the type and shape are not limited thereto.

The noise monitoring system 100 according to an embodiment of the present invention may further include a control unit 140.

The control unit 140 may wake-up the noise level measurement unit 110 to control the measurement of noise when a preset threshold value is exceeded using an event detector or a sound level meter algorithm. .

In addition, based on the noise level data and the noise source location data analyzed through the noise level measurement unit 110 and the noise source location estimation unit 120, when exceeding a specific threshold value, among the warning alarm and alarm message At least one or more output information may be controlled to be transmitted to the mobile device through the communication unit 130.

8 is a block diagram of a multiple monitoring system according to another embodiment of the present invention.

A multiple monitoring system according to another embodiment of the present invention represents data transmission and reception between a plurality of noise monitoring systems 810 and a mobile device 820.

The noise monitoring system 810 measures noise level data through sound pressure level (SPL) measurement through a noise signal detected through a microphone array, and uses the difference in arrival time according to the arrival time of the noise signal to determine the direction of the noise source and Estimate the noise source location data for the location.

At this time, since the noise monitoring system 810 has been described with reference to FIGS. 1 to 7 above, it will be omitted below.

The mobile device 820 displays noise level data and noise source location data received from the noise monitoring system 810.

The mobile device 820 stores result data on the noise level and the location of the noise source based on the noise level data and the location data of the noise source, and the impact data detected through the piezoelectric element (PZT) sensor array included in the noise monitoring system 810. Can be displayed. In addition, the mobile device 820 may determine a noise location for a noise signal through an intersection of two or more lines based on data received from the plurality of noise monitoring systems 810.

More specifically, the noise monitoring system 810 calculates only the azimuth angle of the noise and the angle with respect to the altitude. In addition, in order to determine the location of ambient noise in the room, a multi-monitoring system according to another embodiment of the present invention connected to the mobile device 820 is used.

For example, the location of the noise may be identified through the intersection of two or more lines, and the mobile device 820 may be used as a server for user convenience. Each indoor ambient noise monitoring system 810 transmits noise level data and noise source location data related to each noise to the mobile device 820 through BLE. At this time, the application of the mobile device 820 accesses the insole of the noise monitoring system 810 because it must simultaneously communicate with several systems through a different approach from the existing BLE application.

Depending on the embodiment, the Android application attempts to search for the noise monitoring system 810 within communication range, and may then display the results on the mobile device 820. Accordingly, the user has to select several systems to obtain location information of the noise source, and when a device is selected, the address of the device is inserted into the connection queue to establish a connection. After a successful connection, the application can begin reading, writing and plotting.

9 is a flowchart illustrating a method of operating noise monitoring according to an embodiment of the present invention.

The method of FIG. 9 is carried out by the noise monitoring system according to the embodiment of the invention shown in FIG. 1.

In step 910, the sound pressure level (SPL) is measured through the noise signal detected through the microphone array to measure noise level data for the noise signal.

Step 910 converts the analog audio signal sensed through the microphone array into a noise signal, which is digital data, and calculates an RMS value (RMS) by applying an A-weighted value in the frequency domain after sampling in a fast Fourier transform (FFT). By applying the weight, the sound pressure level (SPL) of the noise can be calculated.

Accordingly, in step 910, noise level data may be measured using the calculated sound pressure level SPL as a standard measurement unit of noise.

In step 920, the noise source location data for the direction and location of the noise source is estimated by using the difference in arrival time according to the arrival time of the noise signal detected by the microphone array.

In step 920, in a microphone array including a plurality of microphones, a time difference of arrival (TDoA) according to an arrival time of a noise signal from a pair of microphones may be measured, and a direction angle may be identified from the difference in arrival time. Accordingly, in step 920, based on the difference in arrival time and the direction angle, the azimuth and altitude angle information may be calculated to estimate the noise source position data of the three-dimensional direction and position of the noise signal.

However, since there may be various errors in accurately determining the location of the noise source, step 920 may estimate the noise source location data that minimizes the error by passing through a low pass filter.

In addition, step 920 may measure all voltage values from each of the plurality of microphones configured in the microphone array at an initial time, and calculate an average value of the voltage values measured in a noise-free environment to determine the offsets of the plurality of microphones. .

In step 930, noise level data and noise source location data are transmitted to the linked mobile device.

In operation 930, noise level data and noise source location data may be transmitted to the mobile device through Bluetooth Low Energy.

The apparatus described above may be implemented as a hardware component, a software component, and/or a combination of a hardware component and a software component. For example, the devices and components described in the embodiments are, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a Field Programmable Gate Array (FPGA). , A programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions, such as one or more general purpose computers or special purpose computers. The processing device may execute an operating system (OS) and one or more software applications executed on the operating system. In addition, the processing device may access, store, manipulate, process, and generate data in response to the execution of software. For the convenience of understanding, although it is sometimes described that one processing device is used, one of ordinary skill in the art, the processing device is a plurality of processing elements and/or a plurality of types of processing elements. It can be seen that it may include. For example, the processing device may include a plurality of processors or one processor and one controller. In addition, other processing configurations are possible, such as a parallel processor.

The software may include a computer program, code, instructions, or a combination of one or more of these, configuring the processing unit to behave as desired or processed independently or collectively. You can command the device. Software and/or data may be interpreted by a processing device or to provide instructions or data to a processing device, of any type of machine, component, physical device, virtual equipment, computer storage medium or device. , Or may be permanently or temporarily embodyed in a transmitted signal wave. The software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the embodiment, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -A hardware device specially configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of the program instructions include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

As described above, although the embodiments have been described by the limited embodiments and drawings, various modifications and variations are possible from the above description by those of ordinary skill in the art. For example, the described techniques are performed in a different order from the described method, and/or components such as a system, structure, device, circuit, etc. described are combined or combined in a form different from the described method, Alternatively, even if substituted or substituted by an equivalent, an appropriate result can be achieved.

Therefore, other implementations, other embodiments, and claims and equivalents fall within the scope of the claims to be described later.

Claims (16)

A noise level measuring unit measuring sound pressure level (SPL) through a noise signal detected through a microphone array to measure noise level data for the noise signal;
A noise source location estimating unit for estimating noise source location data with respect to the direction and location of the noise source using a difference in arrival time according to the arrival time of the noise signal detected by the microphone array; And
Including a communication unit for transmitting the noise level data and the location data of the noise source to an interlocked mobile device,
The noise level measuring unit
The analog audio signal sensed through the microphone array is converted into the noise signal, which is digital data, sampled in a fast Fourier transform (FFT), and then an A-weighted value is applied in the frequency domain to calculate an RMS value (RMS), and the time weight is calculated. Applying to calculate the sound pressure level (SPL) of the noise, and measure the noise level data using the calculated sound pressure level (SPL) as a standard measurement unit of noise,
The noise level measuring unit
The time weight, which is an exponential average, is used as a low pass filter to remove high frequency noise, and the sound pressure level is calculated by using a weight moving average and a sub-frame average for a frame in positioning,
The noise source location estimation unit
At an initial time, voltage values are measured from all microphones configured in the microphone array, an average value of the voltage values measured in a noise-free environment is calculated, and an offset of all the microphones is determined from the calculated average value to determine microphone-to-microphone. A noise monitoring system, characterized in that for correcting fluctuations in the. delete delete The method of claim 1,
The noise source location estimation unit
In the microphone array including a plurality of microphones, noise for measuring the time difference of arrival (TDoA) according to the arrival time of the noise signal from the pair of microphones, and identifying a direction angle from the difference in arrival time Monitoring system. The method of claim 4,
The noise source location estimation unit
A noise monitoring system for estimating the noise source position data of the three-dimensional direction and position for the noise signal by calculating angle information of azimuth and altitude based on the difference in arrival time and the direction angle. The method of claim 5,
The noise source location estimation unit
A noise monitoring system, characterized in that estimating the location data of the noise source that minimizes an error by passing through a low pass filter. delete The method of claim 1,
The communication unit
A noise monitoring system for transmitting the noise level data and the noise source location data to the mobile device through Bluetooth Low Energy. Noise level data is measured through sound pressure level (SPL) measurement through the noise signal detected through the microphone array, and the noise source location data for the direction and location of the noise source using the difference in arrival time according to the arrival time of the noise signal A noise monitoring system to estimate; And
Including a mobile device for displaying the noise level data and the noise source location data received from the noise monitoring system,
The noise monitoring system
The analog audio signal sensed through the microphone array is converted into the noise signal, which is digital data, sampled in a fast Fourier transform (FFT), and then an A-weighted value is applied in the frequency domain to calculate an RMS value (RMS), and the time weight is Apply to calculate the sound pressure level (SPL) of the noise, measure the noise level data using the calculated sound pressure level (SPL) as a standard measurement unit of noise, and remove the high frequency noise by the time weight, which is an exponential average. It is used as a low pass filter, and the sound pressure level is calculated using a weighted moving average and a subframe average for a frame in positioning,
At an initial time, voltage values are measured from all microphones configured in the microphone array, an average value of the voltage values measured in a noise-free environment is calculated, and an offset of all the microphones is determined from the calculated average value to determine microphone-to-microphone. Characterized in that to correct for fluctuations in, multiple monitoring system. The method of claim 9,
The mobile device is
Based on the noise level data, the noise source location data, and impact data detected through a piezoelectric element (PZT) sensor array included in the noise monitoring system, a multiple monitoring system for displaying result data on the noise level and the noise source location . The method of claim 10,
The mobile device is
Based on the data received from the plurality of noise monitoring systems, characterized in that to determine the noise position for the noise signal through the intersection of two or more lines, multiple monitoring system. delete delete delete delete delete

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