Acoustic Impulse Response Research Articles

A Novel Feature Selection Based on VMD and Information Gain for Pipe Blockages

Targeting the challenge of determining the degree of blockage in buried pipelines and the difficulty of effectively extracting blockage features, a blockage detection method integrating variational mode decomposition (VMD) and information gain is proposed. Acoustic impulse response signals were obtained by deconvolving the output signals of the system, which were then subjected to VMD to obtain 12 components in different frequency ranges. Next, information gain (IG) was introduced to characterize the 12 components quantitatively, through which the components containing rich information about the pipe conditions were selected out. Meanwhile, sound pressure level conversion was performed on the selected components to amplify any changes in the sound field. Finally, the root mean square entropy (RMSE) was calculated to constitute the feature eigenvectors, which were input into Random Forests (RF) classifier for defect identification of pipeline. As the experimental results demonstrate, the proposed method is capable of determining the degree of blockage effectively in the running state. Meanwhile, it can also eliminate the interference of functional parts such as lateral connections during the identification process, thereby improving the identification accuracy. The present study has shown both theoretical significance and application value in the field of defect detection and recognition.

Linear microphone array for acoustic impulse response measurements using reciprocal method: Effects of microphone holder

Linear microphone array for acoustic impulse response measurements using reciprocal method: Effects of microphone holder

Reconstruction of waves traveling in a nonlinear granular chain from acoustic measurements

This paper presents a method for reconstructing transient waves traveling in a discrete granular chain from acoustic pressure measurements made in the resulting sound field. A transient vibro-acoustic model is developed, based on the acoustic impulse response of an accelerating sphere, which superposes acoustic radiation from each bead of a granular chain using a convolution integral. We assume straight-line radiation of the acoustic pressure and constant position of the granular chain during propagation of a primary traveling wave. The continuous convolution integral is discretized to obtain the transfer matrix of the acoustic field response that correlates to vibrational motion of a discrete granular chain. To overcome ill-posedness in inverse processing, Tikhonov regularization with appropriate parameter-choice methods is applied. Acoustic field pressures are sampled with a linear microphone array conformal to the geometry of a granular chain at various standoff distances. It is found that the amplitude and speed of the primary traveling wave in a discrete granular chain can be reconstructed from acoustic field responses. The accuracy of reconstruction and the parameter sensitivity are examined with finite element analysis results as benchmarks. For acoustic field pressures contaminated by white noise, root-mean-square error analysis demonstrates that reasonably good reconstruction accuracy can still be achieved when the ill-conditioning of the convolution matrix and the matching of acoustic field pressures are balanced well. This study provides a useful approach to measure and visualize pulse transmission through a discrete granular medium in a time-efficient and cost-effective manner.

Evaluation of watermelon ripeness using self-developed ripening detector

Currently the evaluation of watermelon ripeness is performed manually by tapping the surface of fruit or by visually evaluating from its appearance. However, these evaluations are subjective and inconsistent, therefore, it is necessary to develop and use a reliable instrument for this purpose. This study aimed to develop a ripening detector apparatus based on acoustic impulse response and to be used for evaluating the ripeness stage of watermelon. In this study, five different maturity ages of watermelon, namely 39, 43, 47, 51, and 55 days after planting were evaluated. The acoustic responses were recorded using Audacity 2.3.1. The dominant frequencies and magnitude were then analyzed using Matlab R2014b. The acoustic parameters were related to fruit weight and soluble solid contents to distinguish the different maturity stages. The results showed that the dominant frequencies and the magnitudes were clearly related to the fruit weight and soluble solid contents. As the frequencies and the magnitudes decreased the fruit weight and soluble solids contents consistently increased during maturity period. Therefore, this finding confirmed that the developed ripening detector was reliable to evaluate and distinguish the different ripeness stage of watermelon.

Jointly Leveraging Decorrelation and Sparsity for Improved Feedback Cancellation in Hearing Aids.

We propose a new adaptive feedback cancellation (AFC) system in hearing aids (HAs) based on a well-posed optimization criterion that jointly considers both decorrelation of the signals and sparsity of the underlying channel. We show that the least squares criterion on subband errors regularized by a p-norm-like diversity measure can be used to simultaneously decorrelate the speech signals and exploit sparsity of the acoustic feedback path impulse response. Compared with traditional subband adaptive filters that are not appropriate for incorporating sparsity due to shorter sub-filters, our proposed framework is suitable for promoting sparse characteristics, as the update rule utilizing subband information actually operates in the fullband. Simulation results show that the normalized misalignment, added stable gain, and other objective metrics of the AFC are significantly improved by choosing a proper sparsity promoting factor and a suitable number of subbands. More importantly, the results indicate that the benefits of subband decomposition and sparsity promoting are complementary and additive for AFC in HAs.

On microphone array beamforming and insights into the underlying signal models in the short-time-Fourier-transform domain.

This paper studies signal models for microphone array beamforming in the short-time-Fourier-transform (STFT) domain with long acoustic impulse responses. The major contributions are as follows. First, the signal modeling problem is investigated in the STFT domain and a general decomposition is proposed for the convolved source signal. Second, new insights into the array manifold are presented: the STFT of the windowed acoustic impulse response from the source to the sensors. Third, the structure of the reference signal is analyzed: it can be viewed as the output of a beamformer without considering the noise in the observation signal. Fourth, based on the new perspectives and decomposition, a signal model is derived based on the use of the superdirective beamformer. Finally, three performance measures are defined, based on which three optimal/suboptimal signal models are derived and their performance is assessed under different acoustic environments and analysis window lengths. The performance of the well-known minimum variance distortionless response (MVDR) beamformer is evaluated, which justifies the properties of the developed signal models.

Iterative Echo Labeling Algorithm With Convex Hull Expansion for Room Geometry Estimation

Estimating room geometry is an important problem in audio signal processing, with various applications such as dereverberation and spatial audio. Several methods have been proposed to localize the positions of the walls given the times of arrival (TOAs) from acoustic room impulse responses (RIRs). To localize a reflector, reflections from the same wall should be identified first. When multiple microphones are widely installed inside a room, however, it is hard to identify the reflections generated by the same walls, which leads to the echo labeling problem. In this paper, we propose an iterative echo labeling algorithm to solve the echo labeling problem. We construct a convex hull of ellipses with first-arriving reflections at the initial iteration and expand the convex hull by utilizing later reflections at subsequent iterations. While expanding the convex hull, we sequentially localize the walls by inspecting tangents of the convex hull. Finally, the iteration is terminated when the expanded convex hull of ellipses becomes a superset of a room. As a result, the proposed algorithm can solve the echo labeling problem without prior knowledge of the number of walls and high computational complexity.

Time Difference of Arrival Estimation Based on a Kronecker Product Decomposition

Time difference of arrival (TDOA) estimation, which often serves as the fundamental step for a source localization or a beamforming system, has a significant practical importance in a wide spectrum of applications. To deal with reverberation, the TDOA estimation problem is often transformed into one of identifying the relative acoustic impulse responses. This letter presents a method to efficiently identify the relative acoustic impulse response between two microphones for TDOA estimation based on the so-called Kronecker product decomposition. By decomposing the relative impulse response into a series of Kronecker products of shorter filters, the original channel identification problem with a long impulse response is converted into one of identifying a number of short filters. Since the TDOA information is embedded only in the direct path of the relative impulse response, the dimension of the Kronecker product decomposition can be very small and, as a result, the developed algorithm is expected to work well in real environments with a small number of data snapshots.

Recent Advances in Reducing Food Losses in the Supply Chain of Fresh Agricultural Produce

Fruits and vegetables are highly nutritious agricultural produce with tremendous human health benefits. They are also highly perishable and as such are easily susceptible to spoilage, leading to a reduction in quality attributes and induced food loss. Cold chain technologies have over the years been employed to reduce the quality loss of fruits and vegetables from farm to fork. However, a high amount of losses (≈50%) still occur during the packaging, pre-cooling, transportation, and storage of these fresh agricultural produce. This study highlights the current state-of-the-art of various advanced tools employed to reducing the quality loss of fruits and vegetables during the packaging, storage, and transportation cold chain operations, including the application of imaging technology, spectroscopy, multi-sensors, electronic nose, radio frequency identification, printed sensors, acoustic impulse response, and mathematical models. It is shown that computer vision, hyperspectral imaging, multispectral imaging, spectroscopy, X-ray imaging, and mathematical models are well established in monitoring and optimizing process parameters that affect food quality attributes during cold chain operations. We also identified the Internet of Things (IoT) and virtual representation models of a particular fresh produce (digital twins) as emerging technologies that can help monitor and control the uncharted quality evolution during its postharvest life. These advances can help diagnose and take measures against potential problems affecting the quality of fresh produce in the supply chains. Plausible future pathways to further develop these emerging technologies and help in the significant reduction of food losses in the supply chain of fresh produce are discussed. Future research should be directed towards integrating IoT and digital twins for multiple shipments in order to intensify real-time monitoring of the cold chain environmental conditions, and the eventual optimization of the postharvest supply chains. This study gives promising insight towards the use of advanced technologies in reducing losses in the postharvest supply chain of fruits and vegetables.

GpuRIR: A python library for room impulse response simulation with GPU acceleration

The Image Source Method (ISM) is one of the most employed techniques to calculate acoustic Room Impulse Responses (RIRs), however, its computational complexity grows fast with the reverberation time of the room and its computation time can be prohibitive for some applications where a huge number of RIRs are needed. In this paper, we present a new implementation that dramatically improves the computation speed of the ISM by using Graphic Processing Units (GPUs) to parallelize both the simulation of multiple RIRs and the computation of the images inside each RIR. Additional speedups were achieved by exploiting the mixed precision capabilities of the newer GPUs and by using lookup tables. We provide a Python library under GNU license that can be easily used without any knowledge about GPU programming and we show that it is about 100 times faster than other state of the art CPU libraries. It may become a powerful tool for many applications that need to perform a large number of acoustic simulations, such as training machine learning systems for audio signal processing, or for real-time room acoustics simulations for immersive multimedia systems, such as augmented or virtual reality.

Correction to: A novel cost-effective sparsity-aware algorithm with Kalman-based gain for the identification of long acoustic impulse responses

Correction to: A novel cost-effective sparsity-aware algorithm with Kalman-based gain for the identification of long acoustic impulse responses

A novel cost-effective sparsity-aware algorithm with Kalman-based gain for the identification of long acoustic impulse responses

In this paper, a new robust sparsity (or sparseness)-aware adaptive filtering algorithm is proposed for the purpose of system identification and acoustic echo cancelation. It is named the improved proportionate fast normalized least mean square (IPFNLMS) algorithm. This latter has been derived by an effective integration of the update control matrix of the improved proportionate NLMS (IPNLMS) algorithm to the Kalman-based adaptation gain of the fast-NLMS (FNLMS) algorithm. Simulations were carried out both in synthetic and real long acoustic impulse responses at different sparseness levels with stationary and non-stationary inputs, followed by a verification with real experiment data. Results have shown interesting improvements for the proposed algorithm with respect to its ancestors in terms of convergence speed, steady-state performance, tracking capability and robustness against system sparsity variation.

Change in acoustic impulse response of a room due to a fire.

A room fire creates temperature gradients and inhomogeneous time varying temperature, density, and flow fields. Experimental measurements of the room acoustic impulse/frequency response are presented and compared with a ray traced model. The results show that the fire causes wave-fronts to arrive earlier (due to the higher sound speed) and with more variation in the delay times (due to the sound speed perturbations). The frequency response shows that the modes are shifted up in frequency and high frequency (>2500 Hz) modes are significantly attenuated. Model results are compared with data and show good agreement in observed trends.

The acoustical impulse response of a line source of finite length above an absorbing plane

It was shown in previous publications that the impulse response of an infinite line source, as well as a point source in the three-dimensional space above an absorbing plane, can be expressed in closed form. However, line sources of a finite length are much more practical. In this study, the impulse response of a finite line source above the absorbing ground is derived and presented in a closed form, which is the main result of the present work. The corresponding analytical solution is composed of three distinct signals. Those are the direct signal, the mirrored signal, and the "pressure tail." The direct signal is the line-of-sight signal. The mirrored signal is the signal emitted from the image source. It is weighted with the reflection coefficient of the infinite line source, which is a surprising mathematical result. The direct signal and the mirrored signal are both of finite duration. However, the third signal-the pressure tail-starts at the end of the mirrored signal and continues indefinitely for a finite surface impedance. In general, this last signal is relatively weak; it can be considered as the reverberation of the source caused by the infinite plane.

Impact of channel fluctuations on channel estimation errors in underwater acoustic communications

Channel estimation is critical to achieve high data rate acoustic communications in the ocean. Channel estimates are often utilized to address the distortions induced by multipath propagation in various communication receivers. Therefore, accurate channel estimation is often the prerequisite for reliable coherent acoustic communications. Many efforts have been devoted to either characterizing the acoustic channel or developing high-performance channel estimation algorithms. However, limited work has been directed to investigate effect of channel fluctuations on estimation performance. Here we seek to quantify the impact of channel fluctuations on least squares channel estimators. A new metric, channel variation ratio, is used to describe the rate of fluctuations in the acoustic impulse responses. We investigate the relationship between the mean squared error (MSE) of the channel estimates and the channel variation ratio. We show the new metric can be used to predict channel estimation MSE for least squares channel estimators. Numeric results also show that there exists an optimal channel length with the minimum estimation error for fluctuating acoustic channels. Both computer simulations and experimental data have been used to validate the findings. [Work supported by the National Science Foundation CNS# 1704076.]

Deconvolution of underwater acoustic marine mammal signals from the Northern Gulf of Mexico

Extracting useful information from electronically recorded data measurements often requires the signal to be separated from the noise and the blurring impulse response deconvolved out. In order to denoise LADC-GEMM underwater acoustic data, we apply and compare several techniques from Fourier frequency filtering and wavelet denoising. We also look at methods of estimating the acoustic impulse response (system response, transfer function, etc.) for the northern Gulf of Mexico to be used in implementing several deconvolution methods applied to the same dataset. Deconvolution techniques tested include Fourier deconvolution, Wiener filtering, various blind deconvolution methods, as well as combination algorithms. Comparisons of techniques will be presented, showing that the different methods may yield different results. Metrics for analysis will include both the final quality of results along with computational efficiency. Some recommendations will be made within the framework of marine mammal signal detection; although specifics of denoising and deconvolution will often be data dependent, these ideas can be applied more broadly to a variety of situations.Extracting useful information from electronically recorded data measurements often requires the signal to be separated from the noise and the blurring impulse response deconvolved out. In order to denoise LADC-GEMM underwater acoustic data, we apply and compare several techniques from Fourier frequency filtering and wavelet denoising. We also look at methods of estimating the acoustic impulse response (system response, transfer function, etc.) for the northern Gulf of Mexico to be used in implementing several deconvolution methods applied to the same dataset. Deconvolution techniques tested include Fourier deconvolution, Wiener filtering, various blind deconvolution methods, as well as combination algorithms. Comparisons of techniques will be presented, showing that the different methods may yield different results. Metrics for analysis will include both the final quality of results along with computational efficiency. Some recommendations will be made within the framework of marine mammal signal detectio...

Speech quality enhancement using a two channel sparse adaptive filtering approach

A forward two channel blind source separation scheme can be used as a effective method for speech enhancement. In such a scheme, two mixed sound signals are used as inputs to estimate the original signals which created these mixtures. In an endeavour to enhance the speech quality, an attempt has been made in this paper to design a two channel blind source separation method based on a sparse learning strategy. The proposed approach takes advantage of the sparse nature of the acoustic path impulse responses of the mixing model and offers improved speech quality in comparison with traditional approach. Simulation study shows the improvement in speech quality in terms of perceptual evaluation of speech quality by the proposed sparse forward two channel blind source separation scheme.

Measurement and Adaptive Identification of Nonstationary Acoustic Impulse Responses

In this work, we present a method of measurement of nonstationary acoustic impulse responses identified by the fast version of the Recursive Least Squares algorithm (FRLS), using professional acoustic equipment. This measurement bench realized in a deaf room presents several tests of capability of adaptive algorithm to tracking the nonstationarities of true system to be identified. The tests of tracking capability obtained are stronger compared to what is encountered in real life and can be used in several applications.

Design and Implementation of Universal Acoustic Signal Processing Platform

Acoustic signal processing has been widely used in many fields. In order to meet the demand of engineering applications, a universal acoustic signal processing platform based on DSP+ARM has been proposed to realize acquisition, processing and output of two-channel acoustic signals. The hardware and software realization methods have been discussed. At the same time, the acoustic signal acquisition performance and impulse response of acoustic signal output module have been measured. The results show that the acquisition sensitivity is 86 mV/Pa, the output response is changed by different loudspeakers.

An Approach to Frequency Selectivity in an Urban Environment by Means of Multi-Path Acoustic Channel Analysis.

The improvement of quality of life in the framework of the smart city paradigm cannot be limited to a set of objective measures carried out over several critical parameters (e.g., noise or air pollution). Noise disturbances depend not only on the equivalent level LAeq measured, but also on the spectral distribution of the sounds perceived by people. Propagation modelling to conduct auralization can be done either with geometrical acoustics or with wave-based methods, given the fact that urban environments are acoustically complex scenarios. In this work, we present a first analysis of the acoustic spectral distribution of street noise, based on the frequency selectivity of the urban outdoor channel and its corresponding coherence bandwidth. The analysis was conducted in the framework of the data collected in the Milan pilotWASN of the DYNAMAP LIFE project, with the use of three simulated acoustic impulse responses. The results show the clear influence of the evaluated coherence bandwidth of each of the simulated channels over real-life acoustic samples, which leads us to the conclusion that all raw acoustic samples have to be considered as wide-band. The results also depict a dependence of accumulated energy at the receiver with the coherence bandwidth of the channel. We conclude that, the higher the delay spread of the channel, the narrower the coherence bandwidth and the higher the distortion suffered by acoustic signals. Moreover, the accumulated energy of the received signal along the frequency axis tends to differ from the accumulated energy of the transmitted signal when facing narrow coherence bandwidth channels; whereas the accumulated energy along the time axis diverges from the accumulated transmitted energy when facing wide coherence bandwidth channels.