AT521132B1 - Device, system and method for the spatial localization of sound sources - Google Patents

Abstract

A device is described which comprises at least one first microphone (10) which is arranged movably, at least one second stationary microphone (11) and at least one sensor. The microphones can capture the sound waves emitted by acoustic sources and the sensor can capture spatial coordinates of the first microphone. Furthermore, a corresponding method and a system with the mentioned device are described.

Description

description

DEVICE, SYSTEM AND METHOD FOR SPATIAL LOCALIZATION OF NOISE SOURCES

TECHNICAL AREA

The present description relates to a device, a system and a method for the spatial localization of sound sources and is therefore assigned to the field of acoustic measurement technology.

BACKGROUND

Regarding the relevant prior art, reference is made to the publications CN 104459625 A, JP 62-169069 A, and CN 108983148 A.

[0003] The spatial localization of acoustic sound sources is an essential task in the quantification of noise and vibration characteristics of products in the automotive and aerospace sector as well as in the consumer electronics and industrial equipment sectors. This task is called Noise, Vibration, Harshness (NVH) testing in the product development process. In order to develop products that meet both regulatory and customer-relevant requirements with regard to noise limits and sound perception, NVH testing is essential and accordingly products must be measured with the appropriate reliability and accuracy. The location of sound sources is not only limited to products from the above-mentioned industrial sectors, but is also used in other areas, such as measuring ambient noise at the workplace, in public areas to identify sources of acoustic interference or in the acoustic evaluation of sound dimming in buildings. Users of systems for the spatial localization of acoustic sources include manufacturers of products from the above-mentioned industrial sectors, engineering service providers, building acousticians, construction companies and public institutions.

[0004] In particular, the verification of regulatory requirements and desired sound qualities takes place relatively late in the product development process. At this point, product developers need easy-to-use and intuitive tools to help them analyze NVH issues and make decisions about how to meet product specifications. Similar problems can be found in the field of building acoustics in the in-situ verification of structural measures, quality monitoring in the manufacture of products and in the condition monitoring of machines and processes.

So-called acoustic cameras are known from the prior art, with which acoustic sources can be visualized. Such acoustic cameras typically have a microphone array with a large number of microphones, which are arranged on a disc-shaped surface. The structure of such acoustic cameras is often complex and, in particular, a large number of microphones combined with powerful systems for parallel data acquisition and processing are usually required.

The inventor has set himself the task of providing a device for spatial localization and visualization of acoustic sources and their visualization, which can, for example, provide intrinsic technical advantages in image quality compared to the prior art, especially in the area of contrast range , the local resolution and the maximum frequency of the sound sources that can be represented and is also particularly easy to handle and inexpensive to produce due to the reduced technical complexity.

SUMMARY

The above object is achieved by the system according to claim 1, an apparatus according to claim 18 and the method according to claim 10. Various embodiments and further developments are the subject of the dependent claims.

A device is described which comprises at least one first microphone, which is movably arranged, at least one second stationary microphone and at least one sensor. The microphones can capture the sound waves emitted by acoustic sources and the sensor can capture spatial coordinates of the first microphone.

A system with a corresponding device is also described, which comprises a stationary data processing device on which the device is rotatably mounted about the axis of rotation. The data processing device can receive measurement data from the device and display acoustic source strengths of the object to be measured.

A method according to an embodiment comprises the steps: providing a rotatably mounted device with at least one first microphone, which is movably arranged, and at least one second stationary microphone; rotating the device about an axis of rotation with the first microphone rotating and the second microphone remaining fixed; detecting, by the first and second microphones, sound waves emitted from an object to be measured and simultaneously detecting spatial coordinates of the first microphone; Calculation and mapping of source strengths of the sound-emitting object based on the recorded measurement data.

The invention also describes a method and a device for imaging acoustically emitting objects by recording (i) acoustic variables of the sound field with a moving and a stationary sensor, (ii) path coordinates of the moving sensor and (iii) an optical image of the scene to be measured by a camera, as well as the recording of the data in an electronic unit that moves with the sensors and forwarding to a terminal for processing the data and displaying the results as a superimposition of the colour-coded acoustic image with the optically recorded image of the measured object.

The devices described here can be used in a large number of applications, in particular for the verification of regulatory requirements and desired sound qualities of products from the automotive, aerospace, consumer electronics and industrial equipment sectors, but also in the field of building acoustics, quality monitoring in Manufacturing of products and condition monitoring of machines.

The concepts described here for imaging acoustically emitting objects can be useful in various applications, for example because the measuring equipment is small compared to known systems with comparable performance and image quality based on a sensor array and beamforming technologies. The associated cost reduction makes the technology available to a wide range of users. The massive reduction in size and weight facilitates transportability and the reduced complexity reduces the set-up time for the measurement and increases operational reliability.

In some applications, the concepts described here can be used to advantage since, compared to known sensor array and beamforming techniques, the amount of data to be processed is one to two orders of magnitude smaller, and thus the requirements for the hardware to be used for data acquisition and processing are significantly reduced and the result in the form of an image of acoustic sources can be calculated significantly faster.

BRIEF DESCRIPTION OF ILLUSTRATIONS

The invention is explained in more detail below with reference to the examples shown in the figures. The illustrations are not necessarily to scale, and the invention is not limited to only the aspects illustrated. Rather, emphasis is placed on presenting the principles on which the invention is based. About the pictures:

Figure 1 illustrates an example of a method for calculating an image of acoustically emitting objects based on a block diagram

Measurement of acoustic quantities and measured properties of the sensor movement.

Figure 2 shows a first embodiment of a device in a front view (left, including block diagram of the electronics unit), and in a sectional view (right).

Figure 3 shows an alternative embodiment of the device in a front view (left, including block diagram of the electronics unit), a sectional view (middle) and a rear view (right, without housing cover and drive).

DETAILED DESCRIPTION

The present invention addresses the problem of the spatial localization of acoustic sources and is referred to in the literature as the "Direction of Arrival" (DoA) problem. It should be noted that the DoA problem and associated solutions can be relevant in almost any situation where the underlying physics is characterized by the propagation of waves, e.g. radar, sonar, seismology, wireless communications, radio astronomy, medical imaging , acoustics, etc. In the case of acoustics, the task is to reconstruct the direction or position of acoustic sources in relation to the position and orientation of the observing measuring system based on the measurement of physical variables of the sound field (e.g. using microphones).

The measuring equipment and methods described here are combined in commercially available solutions with a video camera, a data recorder connected to sensors and a computer for implementing algorithms for reconstructing the acoustic image, see e.g. the system description in publication WO 2004/068085 A2.

The following physical variables and associated sensor technologies are considered in commercially available solutions for sound source localization: pressure (omnidirectional pressure microphone); Speed of sound (hot-wire microphone), sound intensity (two-microphone technology); refractive index air (laser Doppler vibrometer); Transverse Velocity of Reflecting Surfaces (Laser Doppler Vibrometer). The scientific literature also describes the measurement of the transverse velocity of an optically reflecting and acoustically transparent membrane using a laser Doppler vibrometer for the spatial localization of acoustic sources. Usually, the physical quantities recorded with the various sensor technologies are converted electrically, recorded digitally with corresponding one- or multi-channel data acquisition systems, pre-processed and finally fed into the actual measurement process.

For further consideration, the methods are divided into a first group with several stationary, time-synchronized sensors (e.g. microphones), which is referred to in the literature as a sensor array, and a second group of methods with one or more moving, time-synchronized sensors make sense. Depending on the application, sensor arrays can have one, two or three-dimensional geometric configurations, e.g. linear, annular, cruciform, spiral, spherical, regularly or randomly distributed in a plane or volume. A variant in the form of a wheel with laterally offset spokes is described in publication US Pat. No. 7,098,865 B2 (original publication DK 174558 B1). The configuration of an array with regard to the distances between the sensors and the spatial extent of the array (aperture) is decisive for the achievable local resolution, the suppression of artefacts and the maximum detectable frequency content of the acoustic sources to be measured in all of the following methods.

Beamforming refers to a signal processing technique that corrects the time offset due to the different runtime from the acoustic source to the respective sensor in the array based on the focus point in question in a first step and sums all time-corrected signals in a second step. The output signal of the beamforming algorithm

is thus amplified in its amplitude when acoustic signals come from the direction of the focus point under consideration or weakened when they come from other directions. Beamforming thus corresponds to spatial filtering of acoustic signals. The algorithmic linking of sensor signals in the manner described is also referred to as "Delay and Sum" or "Steered Response Power" (SRP) algorithm.

The first step in the signal processing of the sensor signals, namely the temporal correction related to the focus point, can be replaced by a filter in order to optimize the ratio of received signal power to signal noise. The associated methods are called "superdirective beamforming" and "adaptive beamforming". The method can also be applied to moving acoustic sources, e.g. passing trains, automobiles or rotating objects in mechanical engineering.

Acoustic holography in the near field (NAH - Near field Acoustic Holography) of sound-emitting objects generates an image of sound sources on a surface based on measurements with a sensor array with a chessboard-like arrangement of the sensors in a source-free area, the array being transverse to the Direction of propagation of the sound is aligned and should cover the majority of the radiating area. In the case of measurement with pressure microphones, the acoustic pressure in the source plane is determined by inverse Fourier transformation of the (two-dimensional) spatial Fourier transformation of the acoustic pressure distribution in the measurement plane (hologram plane) multiplied by a function that describes the phase shift from the hologram plane to any parallel , source-free planes describes. This calculation method makes it possible to reconstruct sound velocity and acoustic intensity using the Euler equation. The so-called patch NAH method addresses the problem of measuring large areas and structures, with the area to be measured being divided into smaller areas (patches). An extension of the NAH method is the NAH-based boundary element method (IBEM (Inverse Boundary Element Method) based NAH), in which the Helmholtz integral theory is applied to calculate the effect of acoustic sources on an envelope on points inside the volume under consideration . An approximation of the above methods is known in the literature as the "Helmholtz Equation, Least Squares" (HELS) method, where the acoustic field is approximated by allowable basis functions with a merit function related to the least square error.

[0026] Time difference of arrival (TDOA) denotes a two-stage method in which, in a first step, the time delay between sensor signals of respectively locally adjacent sensor pairs is determined by means of cross-correlation for a sensor array. Knowing the pairs of time delays and the local position of the sensors, curves or surfaces are generated and the intersection of the curves or surfaces is determined as the estimated position of the sound source as a result of an optimization problem.

The Multiple Signal Classifier (MUSIC) algorithm belongs to the group of subspace (subspace) methods and enables the identification of multiple, harmonic acoustic sources (narrow-band sources) with high spatial resolution. Based on a column-wise linear mapping consisting of so-called "steering" vectors, which map the signals from several a priori defined spatial sources at a certain point in time to the measurement signals of a sensor array at a certain point in time, the cross-correlation matrix of the sensor signals is broken down into mathematical Subspaces and eigenvalue calculation calculates the spatial spectrum of the source distribution. The peaks in the spectrum correspond to the directions from which the sound of the sources parameterized in the model arrives. ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique) is an adaptation of the subspace method mentioned above with the aim of reacting less sensitively to variations in position, gain and phase errors of the sensors.

The time-synchronized, spatial sampling of the sensor signals of a sensor array in circular form induces a Doppler effect in the synthesized signal. The discrete-time TeagerKaiser operator can be used to analyze the modulations and, in the plane case, to calculate the direction of the incoming sound analytically. The localization of several

Sources and thus the calculation of the spatial spectrum of the source distribution is realized by determining a probability density function based on the evaluation of individual time segments. Alternatively, the Center of Gravity algorithm can be used to reduce noise sensitivity and limitations in the actual usable frequency range.

In the publication US Pat. No. 9,357,293 B2, a frequency domain method based on the sampling of microphone signals from virtually moving sub-apertures of a linear array with a large number of sensors is presented. Due to the movement of the sub-apertures at different speeds along the array, different signal overlays are generated depending on the frequency and the position of the acoustic sources. This information about the different mixing and signal energies in the frequency spectrum with different movements of the subapertures can be used to finally infer the position of acoustic sources at a certain frequency.

In what is known as “light refractive tomography”, the change in the refractive index of the medium in which the sound field propagates is calculated using a laser scanning vibrometer along the laser beam, which is reflected on a rigid reflector. The alignment of the laser beam is transversal to the direction of propagation of the sound field. As an extension, computer tomographic methods can be used to reconstruct the sectional image of the acoustic field in the plane in which the change in refractive index is calculated.

Methods with one or more moving sensors for utilizing the Doppler effect are discussed below.

By a priori known movement of an acoustic sensor on a circular path, a single acoustic source positioned in space with constant frequency and amplitude is localized by means of phase lock loop (PLL) demodulation of the phase modulation of the observed signal.

[0033] According to publication US Pat. No. 2,405,281 A, the direction from which dominant acoustic or electromagnetic waves arrive can be identified based on the Doppler effect by means of a sensor moving on a circular path. Here, the measured bandwidth of the Doppler history of a harmonic source is at its maximum when the plane of rotation of the sensor is orthogonal to the receiving direction of the source. Further publications on the identification of individual, dominant acoustic sources by moving one or more microphones using the Doppler effect are EP 2 948 787 A1 and EP 2 304 969 B1.

The application of beamforming for the spatial filtering of a sensor array (with evenly distributed sensors) incident sound waves has the limitation that the maximum detectable (critical) frequency of acoustic sources is defined by the distance between two adjacent sensors of an array . The attempt to localize acoustic sources beyond this frequency leads to the generation of so-called "ghost images" in the reconstructed acoustic image and is also referred to in the literature as the spatial aliasing effect. The use of a sensor array with a fixed arrangement of sensors beyond the critical frequency and the associated suppression of spatial aliasing artifacts can be realized by spatial movement of the sensor array. The point spread function of the imaging system consisting of a sensor array moving on a circular path with constant angular velocity can be simulated using a delay and sum algorithm and the suppression of aliasing artifacts can be verified experimentally with a single harmonic sound source.

As already mentioned at the beginning of this section, methods for locating sources or reflecting structures are also worth mentioning, which are not directly applied in acoustics, but whose underlying physics is characterized by the propagation of waves. For example, a synthetic aperture radar (SAR) can provide an image of a surface by using the electromagnetic field emitted by a

moving transmitter with known position is generated, is sampled. The movement of the transmitter relative to the surface induces a Doppler effect in the collocated receiver. By correlating the measured Doppler history, i.e. the time course of the Doppler frequency of the echo of an object from initially positive values to negative values, with so-called replicas (i.e. Doppler histories generated for each distance based on the knowledge of the movement of the transmitter as a result of point-like reflectors), an image of the scanned surface reconstructed with high resolution.

The basic idea of the new concepts described here is to reduce the outlay on measuring equipment for acquiring sound field information to a minimum while at the same time improving the quality of the spatial imaging of acoustic sources, in particular with regard to the contrast range, the local resolution and the maximum frequency that can be represented. Measurement methods that require a sensor array have the inherent disadvantage of using a large number of sensors in order to achieve a usable spatial resolution with an acceptable contrast range and a sensible upper limit frequency.

Both in beamforming and in acoustic holography, the local resolution is described by the aperture size of the array and the maximum frequency that can be displayed and the field of view by the distance between the sensors. An improvement in the local resolution thus requires an increase in the number of sensors on the measuring surface.

The TDOA method only allows the identification of the most dominant source, and the MUSIC/ESPRIT methods show limitations in the number of identifiable sources, the upper limit of which is determined by the number of sensors used. For both TDOA and MUSIC/ESPRIT, measuring a sound field with an unknown number of acoustic sources can lead to misinterpretations. The DREAM (Discrete Representation Array Modelling) method requires several runs in order to characterize the signal spectrum of the acoustic sources in a first step and to finally determine the size and velocities of the subaperture of a linear array in a second step. Due to the sequential procedure for determining the configuration, the method cannot be used to measure individual acoustic events without a priori information.

The light refractive tomography method mentioned presents the metrologist with the challenge of creating a vibration-free environment for the laser scanning vibrometer and the rigid reflector, since the change in the refractive index of the medium due to the sound field is typically several orders of magnitude below the vibration level of the causative source lies. As with beamforming and acoustic holography, an array of Laser Doppler vibrometers along the perimeter of the slice image to be reconstructed is necessary to achieve useful spatial resolution. Due to the complexity of the measuring equipment used, the outlay in terms of measuring equipment for realizing an array with laser Doppler vibrometers is orders of magnitude higher than for arrays with pressure or sound velocity sensors.

The methods that use the demodulation of a phase modulation of the observed signal of a sensor moving in a circular motion usually only work for the identification of a harmonic source with constant amplitude and frequency or a dominant, stationary source.

1 illustrates in a block diagram an example of a signal processing method that can be used in the exemplary embodiments described here to determine an image of sound-emitting objects (so-called acoustic images in which the sound pressure is e.g. color-coded). The exemplary embodiments described in more detail below each use a sensor (e.g. microphone) with a known, fixed position M, and one or more sensors moved along a circular path. In the present example, a moving microphone is considered whose, for example, circular or spiral-shaped movement is described by the time-dependent position M;(t). However, the trajectory M;(t) does not necessarily have to run along a circular path or a spiral path. In the case of circular or spiral trajectories, however, the instantaneous position M;(t) can be determined comparatively easily

determined using an angle sensor (angle of rotation encoder).

The following variables are considered as input variables of the method: (i) a reconstruction point R described by spatial coordinates in relation to a coordinate system whose origin is at location M i of the stationary sensor; (ii) the sensor signals of the moving first sensor (microphone signal p-(t)) and the stationary second sensor (microphone signal p,(£); (I) the movement M,;(t) of the first moving sensor described by spatial coordinates related to the coordinate system whose origin is at the location of the stationary sensor; (iv) the observation period T, which is defined by the complete scanning of the aperture (e.g. one revolution with a sensor guided on a circular path) and the temporal windowing of the time signals for the transformation determined in the frequency domain, and (v) the observed frequency band [F i , F i ,].

In a first step, the time signal np, (ε) of the moving sensor at time t = 0 is propagated back in time to the reconstruction point R with the value tz, = d(R, M4)« = -0/c (back in time shifted), where d(R, M;) denotes the distance between the reconstruction point R and the position of the moving sensor and c denotes the propagation speed of disturbances in the medium under consideration (speed of sound). In a second step, the time signal p i (t + t i ) is shifted in time by a time-varying fractional delay filter with a variable time delay 271-6 i . The time-variable time delay ö, = ti + öt(M,) designates the time difference that the acoustic disturbance in the medium under consideration requires from the reconstruction point R to the location M, of the moving sensor. ort is a function of the position of the moving microphone M i . In a third step, as in the first step, the time signal is propagated back in time to the reconstruction point R (by the value 7.1). The resulting time signal A1(t) now represents an acoustic signal, which is radiated from a virtual sound source (acoustic monopole) at the reconstruction point R, and this time signal 5, (t) is then finally, in a fourth step, transferred to the location M, of the fixed sensor with time lag tT2 = d(R,M,)/c forward propagated (shifted forward in time), where d(R,M,) denotes the distance between the reconstruction point R and the position of the fixed sensor. For a source that is actually radiating at the reconstruction point R, the time-variable Doppler shifts caused by the movement Mı of the first sensor are compensated. The resulting time signal p i (£) is thus - for a radiating source in the reconstruction point R, the local mapping of the time signal p i (t) of the moving sensor to the position M i of the stationary sensor. Time signal contributions from sources that are actually radiating away from the reconstruction point R undergo additional Doppler shifts that vary over time.

With the time signals p, (t) and p, (t) is now in the frequency domain, the coherence estimation Cp.5: (f) on the basis of the spectral power density functions P"".(f) and Pzz-(f) and the spectral cross power density function P z (f) determined, where

[Pop ML Pa (Pop Ef

The estimated coherence Cn-(f) can now be multiplied by the spectral power density function P01 (f) and thus by integration for an observed frequency band -

defined by a lower frequency Fi and an upper frequency F, of the considered frequency band - according to

Q=SE Pop PC Pdf

be evaluated. The measure Q defined in this way corresponds to the contribution of the source radiating from the reconstruction point R in the frequency band [F i , F i ] to the signal power measured at the location M i of the fixed sensor. This contribution is related to the signal power at the reference point M (location of the stationary microphone) and can be specified in dB, for example.

Co f) =

[0046] While FIG. 1 shows the reconstruction of the acoustic source strength in a reconstruction

point R in space, this concept can be extended to an arbitrarily shaped surface by local discretization of the surface into a large number of reconstruction points and calculation of the acoustic source strengths in the respective discrete reconstruction points. Finally, the image of the calculated source strengths in the reconstruction points can be superimposed on an optically recorded image of the measurement scene (e.g. using a camera) in order to enable local assignment. In one exemplary embodiment, the surface on which the reconstruction points lie can be an image plane which, for example, lies at right angles to an axis of rotation about which the moving microphone rotates and which lies at a defined, specifiable distance from the stationary microphone.

FIG. 2 shows a system for locating and imaging acoustic sources and their strength in a measurement scene with one or more sound sources. The system comprises a device, which is designed as a movable frame construction 100, and a stationary data processing device connected thereto, which can be a mobile device 20 (mobile device) with a camera 21 (e.g. a smartphone or a tablet PC). Other types of data processing devices capable of receiving and sending data over a wired or wireless communication link and displaying images may also be used.

According to one embodiment, the frame structure 100 is rotatably mounted about a (stationary) axis 54 (axis 54 with axis of rotation A). The above-mentioned stationary microphone 11 (position Mn) is arranged in the center of the rotary movement, i.e. on the rotary axis A, whereas several (e.g. electronically multiplexed) microphones 10 are arranged along a longitudinal axis of the frame construction 100. The aforementioned longitudinal axis of the frame construction 100 is at right angles to the axis of rotation A, which is why the microphones 10 move on a circular path about the axis of rotation A when the frame construction 100 rotates about the axis 54 . An electronic unit 40 to which the microphones 10 and 11 are connected can also be arranged in the frame construction 100 . Instead of a rigid axle 54, a rotatable shaft with the axis of rotation A can also be used.

For power supply, the electronic unit 40 can have a battery 49, which supplies the remaining components of the electronic unit with a supply voltage. The charging unit 44 is used to charge the battery 49. However, other forms of voltage supply are also possible. According to the example shown in Fig. 2, the electronics unit 40 further comprises (i) a (e.g. magnetic or optical) rotation angle encoder 16 for determining the angular position of the frame structure 100 with respect to the rotation axis A, (ii) a microphone amplifier 41 for the analog preamplification of the sensor signals p,(t) and p,(t) of the stationary microphone 10 and the moving microphone 11, (iii) a data acquisition device (analog-to-digital converter 42, memory 46) for digitizing and storing the sensor signals of the microphones 10 , 11 and the rotation angle encoder 16, (iv) an electronic multiplexer 45 for selecting the moving microphone 10 connected to a data acquisition device and (v) a module 47 for wireless transmission of the acquired data to the mobile device 20 for the purpose of further processing the Measurement data or analysis by the user. A microcontroller 43 controls the multiplexer 45, the analog/digital converter 42, the data flow and the data transmission. Other sensor systems can also be used to detect the spatial coordinates M, (t) of the moving microphones, such as systems comprising an angular velocity sensor and a three-axis acceleration sensor or motion tracking systems for directly detecting the movement.

The mobile device 20 with an integrated camera 21 is aligned with its optical axis parallel to the axis of rotation A, wirelessly receives the digitized measurement data from the electronics unit 40 and sends them, for example, via a wireless network connection to a cloud computing service for calculation the acoustic imaging according to the method described above with reference to FIG. 1 and superimposes the result calculated (by the cloud computing service) with the optical image captured by the camera 21 of the measurement scene with the sound sources contained therein. The calculations are outsourced to a cloud computing service in order, among other things, to relieve the power consumption of the mobile device,

To store data continuously and sustainably in the case of long-term measurements, to simplify the accessibility of the data for other users with the appropriate access rights, and to enable the web-based integration of the sensor into any measuring and control systems. The computing power does not necessarily have to be outsourced to a cloud computing service, rather the calculations can also be carried out by any other computer connected to the mobile device 20 (e.g. a workstation).

The rotation of the frame structure 100 can be done via a manual or an electric drive 30 (electric motor). As an alternative, a drive by a mechanical spring mechanism would also be possible. In the example shown, the power transmission of the drive 30 is implemented via a drive wheel 31 which is rigidly connected to the frame construction 100 and is rotatably mounted on the axle 54 . The axle 54 and the drive 30 are stationary and are mounted on the bracket 22, for example. The drive wheel 31 is driven, for example, via a pinion 32 on the motor shaft of the electric motor. A controller for controlling the electric motor 30 including the battery or a connection for an external electrical energy supply is integrated into the holder 22 . The holder 22 can, for example, be arranged on a tripod (such as is also used for cameras, for example).

In one embodiment, the housing 13 (i.e., the outer shell) of the framework 100 may have a cross section (normal to the longitudinal axis of the framework 100) that is in the shape of an aerodynamic airfoil 12 . This has the advantage that no aeroacoustic sources are caused by the rotational movement of the frame construction 100 or their occurrence is at least greatly reduced. In the present exemplary embodiment, four microphones 10 are arranged on the frame construction 100 and rotate with the frame construction 100 . As mentioned, the microphone 11 is located at a position on the axis of rotation and therefore does not change its position. The microphones 10, 11 are arranged along the longitudinal axis of the frame construction 100, whereby a distance between two adjacent microphones can be the same in each case (which does not necessarily have to be the case). In the example shown, the moving microphones 10 are arranged on one side of the frame construction 100, while the electronics unit 40 and a balancing mass 17 are arranged on the other side of the frame construction 100. The balancing mass 17 can be dimensioned and positioned in such a way that the frame construction 100, which is asymmetrical per se, has no imbalance when it rotates about the axis of rotation A. Even with a symmetrical design of the frame construction, a balancing mass 17 will generally be necessary since the masses of the components fastened to the frame construction 100 are not symmetrical in relation to the axis of rotation.

According to the example shown in FIG. 2, the microphones 10, 11 can be fastened to the frame construction 100 via an elastic mounting 15. The elastic mounting 15 can help to mechanically decouple the microphones 10, 11 from the frame construction 100 and to prevent the transmission of vibrations, which are caused, for example, by the drive 30 or the rotary bearing 50, to the microphones. In other words, the elastic, damping mounting of the microphones 10, 11 causes an interruption of the structure-borne noise path to the microphones. In the example shown, wind protection elements 14 can be provided on the housing 13 of the frame construction 100, which cover the microphones 10, 11 in order to suppress the coupling of wind noise and signals from other aeroacoustic sources into the sensor signals as a result of the movement of the frame construction 100. Depending on the application, these wind protection elements 14 are optional.

In summary, the function of the embodiment shown in FIG. 2 can be described as follows: When the frame structure 100 rotates about the axis A, the stationary microphone 11 does not change its position, while the other microphones 10 follow a circular path. The microphones 10, 11 capture the sound waves emitted by acoustic sources in the form of a sound pressure, while the rotation angle encoder 16 captures the spatial coordinates of the moving microphones 10. The spatial coordinates are due to the angular position of the frame construction 100 and the (fixed) position of the microphones 10 relative to the frame construction

100 defined. The sensor signals obtained are received by the electronics unit 40 , digitized and sent to the mobile device 20 . As explained above, this can itself calculate the source strengths of the sound sources present on the measured object from the measurement data received, or outsource the calculation to an external computing unit. The camera 21 captures an optical image of the object to be measured (or multiple objects) on which the calculated source strengths can be superimposed in order to obtain a visual representation and assignment of the acoustic sources and their source strength to the optical camera image. For example, the optical image can be recorded in black and white and the source strength can be color-coded in the image.

FIG. 3 shows a further embodiment of a system for locating and imaging acoustic sources on an object to be measured. The system according to FIG. 3 differs from the system according to FIG is mounted to be displaceable radially (along its longitudinal axis). The distance between the microphone 10 and the axis of rotation (and thus the radius of the circular movement of the microphone 10) can thus be varied. Other arrangements of the microphones, in particular with a plurality of slidably mounted microphones 10, are also possible.

By changing (increasing or decreasing) the radial distance between the microphone 10 and the axis of rotation A while the frame structure 200 rotates, the microphone 10 effectively performs a helical movement about the axis of rotation A. An adjustability of the distance between the microphone 10 and the axis of rotation A (i.e. the position of the microphone 10 relative to the frame construction 200 can be achieved, for example, by a cable pull device 60. A cable 61 can be connected to a microphone holder 65, which is mounted on the frame construction 200 in a linearly displaceable manner. For this purpose, the frame construction 200 For example, have two guide rods 62, which are essentially parallel to the longitudinal axis of the frame construction and along which the microphone holder 65 can slide.Thus, the guide rods 62 together with the microphone holder form a linear guide for the microphone 10. The cable 61 is in the example shown several pulleys 63 so as guided around a disk 66 rigidly connected to the axis 54 . In the example shown, the cable runs partially through one of the (hollow) guide rods 62 .

When the frame construction 200 rotates about the stationary axis 54, the cable 61 is unwound on the circumference of the disc 66, which leads to a displacement of the microphone holder 65 and consequently to an approximately spiral movement of the microphone 10, with a measured angular position of the frame construction clearly the radial position of the moving microphone 10 can be assigned; with each full revolution of the frame structure, the microphone is displaced by a distance corresponding to the circumference of the disk 65. As in the previous example, the frame construction has a housing 213 which surrounds the cable pulling device 60 consisting of cable 61, deflection rollers 63, disk 65, guide rods 62 and microphone holder 65 and which has an elongated opening (slot) for the microphone 10. For the rest, the example shown in Fig. 3 is the same as the previous example from Fig. 2.

Claims (34)

patent claims 1. A system that features the following: a device comprising: at least a first microphone (10) that is movably arranged and designed to capture acoustic sources in a measurement scene, a second stationary microphone (11) that is designed to do so to detect acoustic sources in the measurement scene, and at least one position sensor (16) which is designed to detect the position of the first microphone (10); and a computing unit designed to calculate an acoustic source strength at one or more reconstruction points based on the sensor signals of the first microphone (10) and the second microphone (11) and further based on the detected position of the first microphone (10). . The system of claim 1, wherein the device is mounted to rotate about an axis of rotation (A), the second microphone (11) being located on the axis of rotation (A) such that it does not change its position during rotation varies, and wherein the device is in the form of an aerodynamically shaped wing. The system of claim 1, wherein the device is mounted to rotate about an axis of rotation (A), the second microphone (11) being located on the axis of rotation (A) such that it does not change its position during rotation where the reconstruction points lie in a plane perpendicular to the axis of rotation (A). 4. The system according to any one of claims 1 to 3, further comprising: an electronics unit (40) configured to receive sensor signals provided by the first microphone (10), the second microphone (11) and the position sensor (16). become to process. 5. The system according to claim 2, further comprising: a balancing mass (17) which is arranged in the device in such a way that it is not unbalanced when rotated about the axis of rotation (A). 6. The system according to any one of claims 1 to 5, wherein the device has a first part and a second part, the first part being displaceably mounted relative to the second part, the first microphone (10) on the first part and the second Microphone (11) is arranged on the second part. 7. The system of any one of claims 1 to 6, further comprising: a bracket to which the device is mounted; a device (20) that can be attached to the holder and is designed to receive measurement data based on the sensor signals from the device and to visualize measurement results based on the measurement data. The system of claim 7, further comprising: wherein the computing unit is contained within or coupled to the device (20) via a communication link. 9. The system according to claim 8, wherein the processing unit is formed by a cloud computing service. A method, comprising: moving a first microphone (10) relative to a fixed reference position at which a second microphone (11) is located; Capturing the sensor signals supplied by the first microphone (10) and the second microphone (11) and simultaneously capturing a position signal which indicates the position of the first 11. 12. 13. 14 15 16 Austrian AT 521 132 B1 2022-12-15 th microphone (10) indicates relative to the reference position; Calculating an acoustic source strength at one or more reconstruction points based on the sensor signals from the first microphone (10) and the second microphone (11) and further based on the detected position signal. The method of claim 10, further comprising: acquiring an optical image having one or more sound sources; Overlaying the acoustic source strengths calculated for the one or more reconstruction points with the optically captured image. Method according to one of Claims 8 or 9, further comprising: sending the recorded measurement data to a computing unit, in particular to a cloud computing service, via a communication link, wherein the calculation of the acoustic source strength at the one or more reconstruction points is carried out by the computing unit. A method according to any one of claims 10 to 12, further comprising calculating the acoustic source strength: Determining a contribution from virtual sound sources that are virtually located in the reconstruction points (R) to the measured signal power of the sensor signal (p"(t)) of the second microphone (11) based on the sensor signals (pn, (t), p"( t)) the first and second microphones (10, 11) and the measured position of the first microphone (10) relative to the fixed reference position (Mn). The method of claim 13, further comprising: capturing an image with a camera having a fixed position relative to the first microphone (11); assigning the reconstruction points (R) to corresponding pixels of the image; and Displaying the image, the pixels assigned to the reconstruction points (R) being colored based on the contribution calculated for the respective reconstruction point (R) of the virtual sound source located in the respective reconstruction point (R). The method according to claim 13 or 14, wherein, for each reconstruction point (R), determining the contribution of a virtual sound source comprises: Transforming the sensor signal (p, (£)) of the first microphone (10) into a transformed first sensor signal (5; (t)) in which the influence of the Doppler effect caused by the movement of the second microphone (10) is at least is approximately compensated; calculating the coherence (Cnn3;(f)) between the sensor signal (p,(t)) of the second microphone (11) and the transformed first sensor signal (5; (t)); and Calculating the contribution of the virtual sound source located in the respective reconstruction point (R) based on the measured signal power of the sensor signal (p,(£)) of the second microphone (11) for a definable frequency band ([F,(F,]). The method of claim 15, wherein transforming the first sensor signal (p1(0)) comprises: Back propagation of the sensor signal (p,(t)) of the first microphone (10) into the respective reconstruction point (R) by a period of time that depends on the distance between the first microphone (10) at any start time of a measurement and the reconstruction point (R) depends; filtering the back-propagated sensor signal (p,(t)) of the first microphone (10) with a time-variant fractional delay filter by a period of time which represents the time that an acoustic signal needs from the reconstruction point to the first microphone (10); Back propagation of the filtered sensor signal into the reconstruction point (R) by a period of time that depends on the distance between the first microphone (10) at any start time of a measurement and the reconstruction point (R), the resulting back propagated filtered sensor signal (5, (£ t)) one of a in the respective recon 17 18 19 20 21 22 23 Austrian AT 521 132 B1 2022-12-15 virtual sound source located at the construction point (R); Forward propagation of the back-propagated filtered sensor signal (5, (t)) to the reference position by a period of time that depends on the distance between the reference position and the reconstruction point (R). The method according to claim 15 or 16, wherein calculating the contribution of the virtual sound source located in the respective reconstruction point (R) comprises: Integration of the product of coherence (C";-(f)) and spectral power density (Pop. (f)) of the sensor signal (p,(t)) of the second microphone (11) via the predefinable frequency frequency band ([F,, F,]). A device for the spatial localization of acoustic sources on any surface by recording measured values of the acoustic field with two microphones (10, 11), characterized in that a first microphone (10) moves on a track and a second microphone (11) is stationary, the associated acoustic signals being transmitted to a unit that moves with the first moving microphone (10), consisting of a sensor system for recording the spatial coordinates of the first moving microphone (10), a data recording device for the data from the two microphones (10, 11) , the sensors (16) for detecting the spatial coordinates of the first moving sensor (10), and an electrical power supply (49), to a data processing device (20) with a display and operating surface for controlling the measurement and display of Results in the form of an overlay of the image of the measurement scene captured by a camera (21) and the reconstructed image Formation of acoustic sources are forwarded and wherein the first moving microphone (10), the second stationary microphone (11) and the moving unit are integrated into a frame construction (100, 200). The device according to claim 18, characterized in that the frame construction (100, 200) is rotatably mounted about a spatially fixed axis (54) and thus a controlled rotation of the frame construction (100, 200) takes place. A device according to claim 19, characterized in that that the frame construction (100, 200) is coupled to a drive (30) and thus an automatic rotation of the frame construction (100, 200) about the spatially fixed axis (54) is created. A device according to claim 19, characterized in that that the first moving microphone (10) is selected from an array of microphones distributed along the frame structure (100, 200) depending on the time and/or angular position of the frame structure (100, 200) by an electronic multiplexer (45) controlled by the data acquisition device and thus an approximate spiral movement of the first moving microphone (10) can be realized. A device according to claim 19, characterized in that that the first moving microphone (10) slides on a radially aligned rail embedded in the frame construction (200), whose radial movement is synchronized with the movement of the frame construction (200) about the spatially fixed axis (54) and thus a spiral movement of the first moving microphone (10) is induced when the frame structure (200) moves. A device according to Claim 18, characterized in that the first moving microphone (10) and the second stationary microphone (11) are essentially acoustically decoupled from the frame structure (100, 200) in terms of structure-borne noise 24 25 26 27 28 29 30 31 Austrian AT 521 132 B1 2022-12-15 and thus drive, movement or wind noise influence the metrological dynamics to a negligible extent. A device according to claim 18, characterized in that that the first moving microphone (10) and the second stationary microphone (11) are provided with a windscreen (14) in order to suppress aeroacoustic noise from the moving frame construction (100, 200) and to influence the metrological dynamics only to a negligible extent . A device according to claim 18, characterized in that that the surface of the frame construction (100, 200) is aerodynamically shaped in the direction of movement in order to suppress aeroacoustic noise of the moving frame construction and to influence the metrological dynamics only to a negligible extent. A device according to claim 18, characterized in that that the sensor system for detecting the spatial coordinates of the first moving microphone (10) is implemented by a rotation angle sensor (16) for measuring the rotation angle relative to the rigid axis of rotation (54). Device according to Claim 18, characterized in that that the sensor system for detecting the spatial coordinates of the first moving microphone (10) is implemented by an at least uniaxial angular velocity sensor aligned collinear with the axis of rotation (54) of the frame construction (100, 200) and a three-axial acceleration sensor. Device according to Claim 18, characterized in that the sensor system for detecting the spatial coordinates of the first moving microphone (10) is implemented by a motion tracking system. Device according to Claim 18, characterized in that that the distance between the first moving microphone (10) and the center of rotation of the frame structure (200) can be varied in order to improve the local resolution, especially in the case of acoustic sources with low frequencies. Device according to Claim 18, characterized in that that the data from the moving data acquisition device integrated into the frame construction (100, 200) is transmitted wirelessly to a personal computer, laptop or mobile device for further processing or visualization. Method for the reconstruction of the acoustic source strength at any point in space by estimating the coherence between the time signal of a first stationary acoustic sensor and a transform of the time signal of a second moving sensor, characterized in that the time signal of the second moving acoustic sensor is transformed to the reconstruction point by time shift, taking into account the propagation speed in the medium under consideration, the resulting signal serves as an excitation for an acoustic monopole source in the reconstruction point, is time-shifted with a time-delay profile that is inverted by the DC component with respect to the time-dependent time delay between the reconstruction point and the position of the second moving acoustic sensor, and is finally mapped to the location of the first stationary acoustic sensor by a constant time shift, the coherence function thus determined in the frequency domain defining a measure of the contribution of the source radiating from a reconstruction point in relation to the level measured at the location of the stationary sensor. 32. Method according to claim 31, characterized in that the coherence estimation in the frequency domain is evaluated at a specific frequency or is integrated in a defined frequency band in order to enable analyzes of the acoustic source distribution in the frequency domain. 33. The method as claimed in claim 32, characterized in that the reconstruction of the acoustic source strength is carried out at a plurality of points in space, so that the acoustic source strengths can be imaged on a surface of any shape. 34. The method as claimed in claim 33, characterized in that the mapping of the acoustic source strengths is superimposed on an optically recorded image of the measurement scene in order to enable local allocation. 3 sheets of drawings