Method for measuring the low-frequency sound power from a complex sound source based on sound-field correction in a non-anechoic tank

Similar to air reverberation chambers, non-anechoic water tanks are important acoustic measurement devices that can be used to measure the sound power radiated from complex underwater sound sources using diffusion field theory. However,the problem of the poor applicability of low-frequency measurements in these tanks has not yet been solved. Therefore,we propose a low-frequency acoustic measurement method based on sound-field correction(SFC) in an enclosed space that effectively solves the problem of measuring the sound power from complex sound sources below the Schroeder cutoff frequency in a non-anechoic tank. Using normal mode theory, the transfer relationship between the mean-square sound pressure in an underwater enclosed space and the free-field sound power of the sound source is established, and this is regarded as a correction term for the sound field between this enclosed space and the free field. This correction term can be obtained based on previous measurements of a known sound source. This term can then be used to correct the mean-square sound pressure excited by any sound source to be tested in this enclosed space and equivalently obtain its free-field sound power. Experiments were carried out in a non-anechoic water tank(9.0 m × 3.1 m × 1.7 m) to confirm the validity of the SFC method. Through measurements with a spherical sound source(whose free-field radiation characteristics are known),the correction term of the sound field between this water tank and the free field was obtained. On this basis, the sound power radiated from a cylindrical shell model under the action of mechanical excitation was measured. The measurement results were found to have a maximum deviation of 2.9 d B from the free-field results. These results show that the SFC method has good applicability in the frequency band above the first-order resonant frequency in a non-anechoic tank. This greatly expands the potential low-frequency applications of non-anechoic tanks.

An Improved Time-Domain Inverse Technique for Localization and Quantifcation of Rotating Sound Sources

The time-domain inverse technique based on the time-domain rotating equivalent source method has been proposed to localize and quantify rotating sound sources. However, this technique encounters two problems to be addressed: one is the time-consuming process of solving the transcendental equation at each time step, and the other is the difculty of controlling the instability problem due to the time-varying transfer matrix. In view of that, an improved technique is proposed in this paper to resolve these two problems. In the improved technique, a de-Dopplerization method in the time-domain rotating reference frame is frst applied to eliminate the Doppler efect caused by the source rotation in the measured pressure signals, and then the restored pressure signals without the Doppler efect are used as the inputs of the time-domain stationary equivalent source method to locate and quantify sound sources. Compared with the original technique, the improved technique can avoid solving the transcendental equation at each time step, and facilitate the treatment of the instability problem because the transfer matrix does not change with time. Numerical simulation and experimental results show that the improved technique can eliminate the Doppler efect efectively, and then localize and quantify the rotating nonstationary or broadband sources accurately. The results also demonstrate that the improved technique can guarantee a more stable reconstruction and compute more efciently than the original one.

Identification of diesel front sound source based on continuous wavelet transform

Acoustic signals from diesel engines contain useful information but also include considerable noise components To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals. Wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level. Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.

Numerical Calculation of Seafloor Synthetic Seismograms Caused by Low Frequency Point Sound Source

Elastic wave on seafloor caused by low frequency noise radiated from ship is called ship seismic wave which can be used to identify ship target. In order to analyze the wave components and the propagating properties of ship seismic wave, the numerical calculation of synthetic seismograms on seafloor aroused by a low frequency point sound source is carried out using a wave number integration technique combined with inverse Fourier transform. According to the numerical example of hard seafloor, the time series of seismic wave on seafloor are mostly composed of interface waves and normal mode waves. Each normal mode wave has a well defined low cut-off frequency, while the interface wave doesn't have. The frequency dispersion of normal mode wave is obvious when frequency is lower than 100Hz, while the interface wave is dispersive only in the infra-sound frequency range. The time series of seismic wave is dominated by the interface wave when the source frequency is less than the minimal cut-off frequency of normal mode wave.

Sound Source Localization Based on SRP-PHAT Spatial Spectrum and Deep Neural Network

Microphone array-based sound source localization(SSL)is a challenging task in adverse acoustic scenarios.To address this,a novel SSL algorithm based on deep neural network(DNN)using steered response power-phase transform(SRP-PHAT)spatial spectrum as input feature is presented in this paper.Since the SRP-PHAT spatial power spectrum contains spatial location information,it is adopted as the input feature for sound source localization.DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features.SRP-PHAT at each steering position within a frame is arranged into a vector,which is treated as DNN input.A DNN model which can map the SRP-PHAT spatial spectrum to the azimuth of sound source is learned from the training signals.The azimuth of sound source is estimated through trained DNN model from the testing signals.Experiment results demonstrate that the proposed algorithm significantly improves localization performance whether the training and testing condition setup are the same or not,and is more robust to noise and reverberation.

A Particle Filter Based Compressive Sensing Method for Tracking Moving Wideband Sound Sources

Tracking moving wideband sound sources is one of the most challenging issues in the acoustic array signal processing which is based on the direction of arrival(DOA) estimation. Compressive sensing(CS) is a recent theory exploring the signal sparsity representation, which has been proved to be superior for the DOA estimation. However, the spatial aliasing and the offset at endfire are the main obstacles for CS applied in the wideband DOA estimation. We propose a particle filter based compressive sensing method for tracking moving wideband sound sources. First, the initial DOA estimates are obtained by wideband CS algorithms. Then, the real sources are approximated by a set of particles with different weights assigned. The kernel density estimator is used as the likelihood function of particle filter. We present the results for both uniform and random linear array. Simulation results show that the spatial aliasing is disappeared and the offset at endfire is reduced. We show that the proposed method can achieve satisfactory tracking performance regardless of using uniform or random linear array.

A FAST SEARCH METHOD OF STEERED RESPONSE POWER WITH SMALL-APERTURE MICROPHONE ARRAY FOR SOUND SOURCE LOCALIZATION

The Steered Response Power(SRP)method works well for sound source localization in noisy and reverberant environment.However,the large computation complexity limits its practical application.In this paper,a fast SRP search method is proposed to reduce the computational complexity using small-aperture microphone array.The proposed method inspired by the SRP spatial spectrum includes two steps:first,the proposed method estimates the azimuth of the sound source roughly and determines whether the sound source is in far field or near field;then,different fine searching operations are performed according to the sound source being in far field or near field.Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computation complexity of the proposed method with those of the conventional SRP-PHAT algorithm.The results show that,the proposed method has a comparative accuracy with the conventional SRP algorithm,and achieves a reduction of 93.62%in computation complexity compared to the conventional SRP algorithm.

Microphone Array-Based Sound Source Localization Using Convolutional Residual Network

Microphone array-based sound source localization(SSL)is widely used in a variety of occasions such as video conferencing,robotic hearing,speech enhancement,speech recognition and so on.The traditional SSL methods cannot achieve satisfactory performance in adverse noisy and reverberant environments.In order to improve localization performance,a novel SSL algorithm using convolutional residual network(CRN)is proposed in this paper.The spatial features including time difference of arrivals(TDOAs)between microphone pairs and steered response power-phase transform(SRPPHAT)spatial spectrum are extracted in each Gammatone sub-band.The spatial features of different sub-bands with a frame are combine into a feature matrix as the input of CRN.The proposed algorithm employ CRN to fuse the spatial features.Since the CRN introduces the residual structure on the basis of the convolutional network,it reduce the difficulty of training procedure and accelerate the convergence of the model.A CRN model is learned from the training data in various reverberation and noise environments to establish the mapping regularity between the input feature and the sound azimuth.Through simulation verification,compared with the methods using traditional deep neural network,the proposed algorithm can achieve a better localization performance in SSL task,and provide better generalization capacity to untrained noise and reverberation.

Simulating Underwater Plasma Sound Sources to Evaluate Focusing Performance and Analyze Errors

Focused underwater plasma sound sources are being applied in more and more fields. Focusing performance is one of the most important factors determining transmission distance and peak values of the pulsed sound waves. The sound source’s components and focusing mechanism were all analyzed. A model was built in 3D Max and wave strength was measured on the simulation platform. Error analysis was fully integrated into the model so that effects on sound focusing performance of processing-errors and installation-errors could be studied. Based on what was practical, ways to limit the errors were proposed. The results of the error analysis should guide the design, machining, placement, debugging and application of underwater plasma sound sources.

SOUND SOURCE LOCALIZATION OF DIGITAL HEARING AIDS USING WAVELET BASED MULTIVARIATE STATISTICAL METHOD

The letter proposed a sound source localization method of digital hearing aids using wavelet based multivariate statistics with the Generalized Cross Correlation (GCC) algorithm. Haar wavelet is used to decompose GCC sequences and extract four wavelet characteristics. And then, Hotelling T2 statistical method is used to fuse the four wavelet characteristics. The statistical value is used to judge the number of sound sources and obtain corresponding time delay estimation which is used to localize the position of sound source. The experimental results show that the proposed method has better robustness in an environment with severe noise and reverberation. Meanwhile, the complexity of al-gorithm is moderate, which is available for sound source localization of hearing aids.

Sound Source Measurement of a Semi-Circular Cylinder in a Uniform Flow by Particle Image Velocimetry

In this paper, the measurement of an aerodynamic sound source for a semi-circular cylinder in a uniform flow is described using Particle Image Velocimetry (PIV). This experimental technique is based on vortex sound theory, where the time derivative of vorticity is evaluated with the aid of two sets of standard PIV systems. The experimental results indicate that the sound source for the semi-circular cylinder is located around the shear layer near the edge of the semi-circular cylinder. The sound source intensity and the area are reduced in the semi-circular cylinder compared with those of a circular cylinder. This result indicates that the aerodynamic sound of the semi- circular cylinder is smaller than that of the circular cylinder, which supports the microphone measurement result.

Development of a System for Location Finding of Low-Level Sound Source by Using Human Acoustic System with Stochastic Resonance

The purpose of this study is to develop a system that enables location finding of a small sound. The location finding of a small sound has some difficulties such as high computational costs or disturbances from the ambient noises and reflected waves. The proposed system is composed of a biologically-inspired system which uses a hearing mechanism based on the human ear and a mechanism for perceiving weak signals that uses stochastic resonance. The location finding mechanism in the proposed system is based on the time-lag detecting architecture. On the other hand, the stochastic resonance mechanism can pick up the small sound source in the ambient noises. Using this proposed system, we implemented the location finding of small sounds through numerical simulations and hardware experiments. Good results were obtained for the small sound source location finding.

An Analytic Model of Subminiature Auditory Sensation System for Sound Source Localization

It is reported that some types of insects have a remarkable ability to detect the direction of an incident sound even though its acoustic sensory organs are in very close proximity each other. Maybe the ears are jointed by a cuticular structure with which the separated motions can be coupled mechanically and thus be magnified. In this paper, a detailed model is setup to describe the principle of this type of localization using a mechanical coupled structure. The transfer functions and the responses of the model in terms of time and frequency are analyzed to describe the mechanism of its ability of directional hearing. This analytical model provides a method to design the experimental model for the predetermined incident sound pressure, and the analysis of this model shows that this structure have the ability to determine the direction of the incident stimulus.

The effect of right versus left long-term single-sided deafness on sound source localization

Purpose: To analyze the effect of right versus left long-term single-sided deafness(SSD) on sound source localization(SSL), discuss the necessity of intervention and treatment for SSD patients, and analyze the therapeutic effect of long-term unilateral cochlear implantation(UCI) from the perspective of SSL.Methods: This study included 25 patients with SSD, 11 patients with UCI, and 30 participants with normal hearing(NH). Their SSL ability was tested by obtaining their average root mean square(RMS) error values of SSL test.Results: The results showed that the RMS error value of SSD, UCI and NH groups were 52.26 ± 20.25°, 69.84 ±12.14° and 4.27 ± 2.66°, respectively. The ability of SSL was better in the SSD-L group than that in the SSD-R group, and no significant difference existed in the SSD-R and the UCI group.Conclusion: When bilateral deafness patients select unilateral treatment, right-side cochlear implantation may be more beneficial in terms of SSL, which means that the central auditory cortex in long-term SSD patients is affected differently based on which side their deafness occurs.

Accelerated steered response power method for sound source localization via clustering search

The steered response power-phase transform (SRP-PHAT) sound source localization algorithm is robust in a real environment. However, the large computation complexity limits the practical application of SRP-PHAT. For a microphone array, each location corresponds to a set of time differences of arrival (TDOAs), and this paper collects them into a TDOA vector. Since the TDOA vectors in the adjacent regions are similar, we present a fast algorithm based on clustering search to reduce the computation complexity of SRP-PHAT. In the training stage, the K-means or Iterative Self-Organizing Data Analysis Technique (ISODATA) clustering algorithm is used to find the centroid in each cluster with similar TDOA vectors. In the procedure of sound localization, the optimal cluster is found by comparing the steered response powers (SRPs) of all centroids. The SRPs of all candidate locations in the optimal cluster are compared to localize the sound source. Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computational load of the proposed method with those of the conventional SRP-PHAT algorithm. The results show that the proposed method is able to reduce the computational load drastically and maintains almost the same localization accuracy and robustness as those of the conventional SRP-PHAT algorithm. The difference in localization performance brought by different clustering algorithms used in the training stage is trivial.

Target localization and parameters estimation by sonar system with explosions as underwater sound sources

Underwater target localization and parameters(azimuth and range) estimation by the method of utilizing explosions as underwater sound sources are described in this paper.The narrow beam reverberation model of the target echo signal is researched to estimate the target azimuth in reverberation background.Estimation errors of target azimuth and range are studied and proved to approximately meet Gauss distribution.Then the variance formula of target range error is deduced.Simulation experiments are applied to research the target range error and its standard deviation,and a series of measures to improve the estimation accuracy of target range are proposed.It is confirmed by the data processing results of simulations and lake experiments that the proposed method can accurately locate underwater target at a long distance on the condition of a certain underwater explosion range error.

Research on acoustic holography method for identification of sound sources

This paper presents the method named acoustic holography which can be used to identify noise sources. A new formula of holography reconstruction is obtained, based on the Kirchhoff integral formula. Some simulating tests are carried out using the new formula. The comparison with other reconstruction formulas proves that the new formula is more effective. By using acoustic holography method, some interesting results about the noise of a vehicle are shown. The results proves that acoustic holography is an effective method for the identification of the complex noise sources.

Distributed sound source localization algorithm with sound velocity calibration in windy environments

A new sound source localization method with sound speed compensation is proposed to reduce the wind influence on the performance of conventional TDOA （Time Difference of Arrival） algorithms. First, the sound speed is described as a set of functions of the unknown source location, to approximate the acoustic velocity field distribution in the wind field. Then, they are introduced into the TDOA algorithm, to construct nonlinear equations. Finally, the particle swarm optimization algorithm is used to estimate the source location. The simulation results show that the proposed algorithm can significantly improve the localization accuracy for different wind velocities, source locations and test area sizes. The experimental results show that the proposed method can reduce localization errors to about 40% of the original error in a four nodes localization system.

A head-related transfer function model for fast synthesizing multiple virtual sound sources

A head-related transfer function （HRTF） model for fast and real-time synthesizing multiple virtual sound sources is proposed. A head-related impulse response （HRIR, time- domain version of HRTF） is first decomposed by a two-level wavelet packet and then represented by a model composed of subband filters and reconstruction filters. The coefficients of the subband filters are the zero interpolation of the wavelet coefficients of the HRIR. The coefficients of the reconstruction filters can be calculated from the wavelet function. The model is simplified by applying a threshold method to reduce the wavelet coefficients. The calculated results indicate that for a model with 30 wavelet coefficients, the error of reconstructed HRIR is about 1%. And the result of a psychoacoustic test shows that a model with 35 wavelet coefficients is perceptually indistinguishable from the original HRIR. When multiple virtual sound sources are synthesized simultaneously, the computational cost of the proposed model is much less than the traditional HRTF filters.

A study on the random array generation method for moving sound source identification

Based on the problem that the generating method of random array structure is inefficient, a method is proposed to generate the random target arrays by using coaxial circu- lar array in the polar coordinates in the premise that the array angular resolution of source identification is guaranteed. According to the principle of moving sound source identification, this work deduces the basic non-equidistance coaxial circular rings＇ radius, and generates target random arrays which were suitable for moving sound source identification through array partitioning, condition filtering in the polar coordinates and simulation evaluation. Finally, numerical simulation and moving car sound source identification test have been done. The analytical results show that using this method to generate random array is effective. Compared with the traditional regular arrays, the target random array has more accurate moving sound source identification performance.