Three-dimensional Sound Source Research Articles

Helmholtz resonator-based acoustic sensors for three-dimensional sound source localization

Helmholtz resonator-based acoustic sensors for three-dimensional sound source localization

Three-Dimensional Sound Source Location Algorithm for Subsea Leakage Using Hydrophone

Three-Dimensional Sound Source Location Algorithm for Subsea Leakage Using Hydrophone

Three-dimensional sound source localization system based on fiber optic sensor array with an adaptive algorithm

Sound Source Localization (SSL) based on microphone arrays nowadays is widely used in the fields of machinery rattle localization, weapon navigation, and robot hearing. However, there is also a need for SSL in some special environments, such as long-distance gas pipelines where there is a risk of leakage. In these environments, arrays built with ordinary microphones can be a safety hazard, which can be compensated by the External Fabry-Perot interferometer (EFPI) fiber-optic sensor's advantages of being uncharged, inexpensive, and highly sensitive. To expand the application areas of microphone array-based SSL techniques, this paper using four EFPI fiber-optic sensors to constructs a 1 m × 1 m × 1 m sensor array, which is used for real-time localization of sound sources based on three-wavelength adaptive intensity demodulation methods and Time Difference Of Arrival (TDOA) localization techniques. An improved method is proposed for the three-wavelength adaptive intensity demodulation method to avoid the occurrence of signal flips. Finally, formulas are provided for this sensor array to quickly calculate the sound source position based on the arrival delay. Several experiments show that the system can achieve sound source localization over a wide range with an average error of less than 3 cm.

Three-dimensional sound source diagnostic using a spherical microphone array from multiple capture positions

Most sound source diagnosis systems based on acoustic images are spatially stationary and unable to combine information from multiple capture positions, resulting in unreliable and partial diagnostics. In this paper it is proposed, developed and validated a measurement method based on a mobile spherical microphone array that generates acoustic images using beamforming from multiple capture positions, called Acoustic Imaging Structure From Motion (AISFM). The tridimensional localization, magnitude and directivity of multiple sound sources may be recovered with or without knowledge of the capture positions. An automatic and unsupervised acoustic image processing algorithm is deployed to facilitate the measurement workflow. An acoustic image correspondence problem is solved in order to eliminate false-positives and false-negatives from the diagnostic and render the AISFM feasible. Sound sources localization uncertainties estimates related to the sources’ magnitude, directivity and extension projected on the acoustic images are used in order to improve the diagnosis. The method and its effectiveness are experimentally validated with a measurement setup comprising five simultaneous sound sources on an anechoic environment.

Multiple Sound Source Localization in Three Dimensions Using Convolutional Neural Networks and Clustering Based Post-Processing

Sound source localization methods are successfully applied for various estimation tasks, such as tracking and detecting objects, aiming cameras, and navigating robots. However, large and usually complex distributed microphone arrays are used for three-dimensional acoustic source localization. This study proposes a convolutional neural network architecture for three-dimensional sound source localization using a single tetrahedral microphone array. A spectrum phase component of a microphone array signal was designed as the input of the model, while the output represents a three-dimensional space. The paper provides extensive experimental results of the given method on a semi-synthetic audio data set and a real-world microphone array. Furthermore, cluster-based post-processing has been shown to increase the accuracy of three-dimensional localization by more than 30%. The experimental results on a synthesized data set using the image source method showed 1.08 m localization uncertainties. The estimate of the investigated sound sources had a mean absolute error of 18.97° and elevation error of 48.49°. An additional advantage of the proposed method is the ability to predict the location of the sound source from a single signal analysis frame. This gives instant localization and is in line with many alternative applications. The proposed solution does not require intensive preprocessing of the audio signals and can be used as a video camera pointing system based on a microphone array. In the future, it would be relevant to investigate the localization performance of more than two sound sources, and the variable acoustic conditions could also be assessed.

Rapid Prediction Method of Fan Broadband Noise Based on A Three-dimensional Sound Source Model

The fan/compressor broadband noise is an important noise source of civil large bypass ratio turbofan engine.. The empirical method requires massive amounts of test data for support. Adopting the computational aeroacoustic (CAA) method to predict the fan/compressor broadband noise will cost high amounts of computing resources or time. Thus, this study combines flow field calculation with analytical model to study the prediction method of fan/compressor broadband noise, this method can be used for quick and efficient preliminary evaluation and parameter studies. On the basis of the simulation and modeling of the stator – rotor interference phenomenon of fans, rotor wake flow field and the corresponding parameters are obtained. On this basis, the three-dimensional sound source model is used to calculate the blade surface sound source and its propagation under different working conditions. The distribution of sound energy in the duct is obtained. Then, the broadband noise prediction of fan is further acquired. The broadband noise of a typical single-stage TA36 fan is predicted using this method. Study results suggest that (1) turbulence model and turbulence kinetic energy of inlet boundary condition will have an important effect on the prediction results of broadband noise. (2) When the inlet turbulence kinetic energy is small, different turbulence models slightly influence the prediction results of broadband noise; when the inlet turbulence kinetic energy is large, the sound pressure level of sound field obtained by SST model is approximately 5dB larger than that obtained by model. This method can be used in the early stage of fan/compressor design, and the characteristics of blade broadband noise can be rapidly obtained.

Efficient and robust approaches for three-dimensional sound source recognition and localization using humanoid robots sensor arrays

Efficient and robust sound source recognition and localization is one of the basic techniques for humanoid robots in terms of reaction to environments. Due to the fixed sensor arrays and limited computation resources in humanoid robots, there comes challenge for sound source recognition and localization. This article proposes a sound source recognition and localization framework to realize real-time and precise sound source recognition and localization system using humanoid robots’ sensor arrays. The type of the audio is recognized according to the cross-correlation function. And steered response power-phase transform function in discrete angle space is used to search the sound source direction. The sound source recognition and localization framework presents a new multi-robots collaboration system to get the precise three-dimensional sound source position and introduces a distance weighting revision way to optimize the localization performance. Additionally, the experiment results carried out on humanoid robot NAO demonstrate that the proposed approaches can recognize and localize the sound source efficiently and robustly.

Evaluation of localization precision by proposed quasi-spherical nested microphone array in combination with multiresolution adaptive steered response power

Abstract Multiple sound source localization in noisy and reverberant conditions is one of the important challenges in the speech signal processing. The aim of this article is three-dimensional sound source localization in undesirable scenarios. For the localization algorithms, the spatial aliasing is one of the destructive factors in reducing the accuracy. Firstly, a 3D quasi-spherical nested microphone array (QSNMA) is proposed for eliminating the spatial aliasing. Since the speech signal has the windowed-disjoint orthogonality property, the speech information differs in terms of the frequency bands. Then, the Gammatone filter bank is introduced for the speech subband processing. In the following, the multiresolution steered response power (SRP) algorithm is adaptively implemented on subbands with the phase transform (PHAT)/maximum likelihood (ML) weighted functions based on the levels of the noise and reverberation. The peaks of the multiresolution adaptive SRP (MASRP) algorithm are extracted in each subband based on the number of speakers for continuous time frames. Finally, the distribution of these peaks are calculated in each subband and they are merged by the use of weighted averaging method. The final 3D speakers locations are estimated by extracting the peaks in the final distribution. The proposed QSNMAMASRP(PHAT/ML) algorithm is evaluated on real and simulated data for 2 and 3 simultaneous speakers in noisy and reverberant conditions. The proposed method is compared with SRP-PHAT, spectral source model-deep neural network, and spherical harmonic temporal extension of multiple response model sparse Bayesian learning algorithms on different range of signal-to-noise ratio and reverberation time. The mean absolute estimation error, averaged standard deviation for absolute estimation error, and computational complexity results show the superiority of the proposed method.

DATASET FOR EVALUATION OF THE PERFORMANCE OF THE METHODS OF SOUND SOURCE LOCALIZATION ALGORITHMS USING TETRAHEDRAL MICROPHONE ARRAYS

For the development and evaluation of a sound source localization and separation methods, a concise audio dataset with complete geometrical information about the room, the positions of the sound sources, and the array of microphones is needed. Computer simulation of such audio and geometrical data often relies on simplifications and are sufficiently accurate only for a specific set of conditions. It is generally desired to evaluate algorithms on real-world data. For a three-dimensional sound source localization or direction of arrival estimation, a non-coplanar microphone array is needed.Simplest and most general type of non-coplanar array is a tetrahedral array. There is a lack of openly accessible realworld audio datasets obtained using such arrays. We present an audio dataset for the evaluation of sound source localization algorithms, which involve tetrahedral microphone arrays. The dataset is complete with the geometrical information of the room, the positions of the sound sources and the microphone array. Array audio data was captured for two tetrahedral microphone arrays with different distances between microphones and one or two active sound sources. The dataset is suitable for speech recognition and direction-of-arrival estimation, as the signals used for sound sources were speech signals.

Free-Field TDOA-AOA Sound Source Localization Using Three Soundfield Microphones

Accurate source localization is an important problem in many research areas as well as practical applications in wireless communications and acoustic signal processing. This paper presents a passive three-dimensional sound source localization (SSL) method that employs a geometric configuration of three soundfield microphones. Two methods for estimating the angle of arrival (AOA) and time difference of arrival (TDOA) are proposed based on Ambisonics A and B format signals. The closed-form solution for sound source location estimation based on two TDOAs and three AOAs is derived. The proposed method is evaluated by simulations and physical experiments in our anechoic chamber. Simulations demonstrate that the estimation method can theoretically obtain Cramer-Rao lower bound for a small Gaussian noise present in AOA and TDOA observations. Investigation on the uncertainty of TDOA and AOA measurements depending on the length of measurement interval is also conducted. Experimental results in terms of RMSE indicate that the proposed solution can be used to accurately find a 3D position of the sound source in free-field environment. Performance evaluation regarding the number of estimation steps shows that higher accuracy can be achieved by longer observations of stationary sound source.

Two and Three-Dimensional Sound Source Localization with Beamforming and Several Deconvolution Techniques

Two and Three-Dimensional Sound Source Localization with Beamforming and Several Deconvolution Techniques

Localization and identification of three-dimensional sound source with beamforming based acoustic tomography

Beamforming based commercial planar microphone array could only localize and identify the sound source when the distance between source and array is known. This paper presents a beamforming based acoustic tomography (BBAT) method to locate and identify the source in 3D space, say, the BBAT method can not only locate the source in X-Y plane that is parallel to the array, but also the depth Z of the source. In this method, the sound field is reconstructed on the virtual planes at different distances along depth direction (Z direction). The maximum response of sound field on every virtual reconstruction plane is tracked, where the largest value among those maximum responses appears at Z direction is the depth of the source. The location of source at X and Y directions can then be easily identified based on beamforming principle, which is utilized by commercial planar array. The BBAT method is evaluated theoretically by simulation of monopole source, the experimental evaluation is done as well in anechoic chamber. The results from both simulation and experiment indicate that this method is capable to locate and identify sound source in 3D space. However, it cannot recognize the sound source located in front of the planar array or behind because of the genetic limitation of 2D planar array in identification of source depth.

Microphone arrays application in three-dimensional sound source localisation

This article describes the problems of use of spatial microphone arrays in sound source location. Questions concerning modelling of planar (2-D) and spatial (3-D) directional characteristics of microphone arrays are discussed. Typical algorithms used in SSL system are also described. The paper describes options to use a single point surround microphone to determine a direction of the sound source localisation. A 'soundfield' microphone with four transducers (capsules) characterised by cardioid directivity pattern. A unique mechanical design of the transducer results in its omnidirectional directivity pattern. The microphone enables 3-D sound acquisition in so called A-format. Upon further processing of signal it is possible to determine, e.g., a direction of a sound source within space. The conducted experiments prove that a simple calculation algorithm is in particular feasible for a real time operation, and application of the soundfield microphone significantly simplifies mechanical design of the SSL system.

APPLICATIONS OF THE GREEN FUNCTIONS IN THE STUDY OF ACOUSTIC PROBLEMS IN OPEN AND CLOSED SPACES

This paper presents a set of analytical solutions (Green functions) for the steady state response of a homogenous acoustic three-dimensional space subjected to a point harmonic load or a spatially sinusoidal harmonic line load. The propagation medium is modelled with plane surfaces placed so as to reproduce spaces that vary from a simple half-space to a rectangular parallelepiped closed space. The final expressions are implemented to evaluate first the pressure field inside a rectangular parallelepiped room, whose walls allow different absorption coefficients. Then, the acoustic scattering of a three-dimensional sound source by an infinitely long rigid barrier in the vicinity of a tall building is evaluated using the boundary-element method (BEM), making use of the analytical solution for a spatially sinusoidal line source. The use of these Green functions allows the required BEM discretization to be limited to the surface of the barrier, avoiding the discretization of the tall building and ground. The calculations are performed in the frequency domain and time signatures are obtained by means of inverse Fourier transforms. Complex frequencies are used to attenuate the response at the end of the time frame, which is taken into account by rescaling the time response.

全方位センサと3次元音響を利用した視覚障害者用歩行誘導システム(<特集>最新のスポーツ工学 : 用具と施設を中心に)

We tried to develop a walking guide system that consists of a head mounted omni-vision sensor and a three-dimensional sound processor for the visually impaired. The system detects a position of a colored panel and presents three-dimensional sound source as if the panel sounds. Through the experiments using hanging colored panel, it is clear that the system is able to guide the subjects to arbitrary position in the room.