Acoustic Travel-time Tomography Research Articles

Coupling adaptive filters with acoustic travel time tomography for indoor climate measurements in occupied room conditions

Acoustic travel time TOMography (ATOM) as a remote sensing technique allows for the measurement of indoor climate parameters, such as air temperature and airflow velocity distributions. The performance of ATOM in monitoring indoor air temperature in empty room conditions was evaluated recently, utilizing a combined analysis approach of room acoustics and tomography. This study shifts focus to the assessment of ATOM in an occupied room condition where fixed objects are introduced to the test area. The presence of objects in a room can result in notable shifts in the travel times of individual reflections. In some cases, these shifts can cause reflections to disappear completely or be replaced by new ones. These partial disruptions in the reflection pattern present challenges in obtaining accurate information about the room's temperature. To ensure the accurate identification of undisturbed reflection paths, an algorithm was developed that can convert distorted signals into a pure reference signal using a suitable adaptive filter. The measurement results confirm the validity of the approach for a temperature interval of 4°C where the system was trained for two temperatures of 20°C and 24°C in a climate chamber.

Acoustic travel time tomography for simultaneous indoor air temperature and airflow measurements

Acoustic travel time tomography for simultaneous indoor air temperature and airflow measurements

Validation of the stochastic inversion algorithm for acoustic travel-time tomography: a large eddy simulation study

Acoustic tomography (AT) is explored as a remote sensing technique to obtain instantaneous snapshots of temperature and velocity fluctuations for wind energy applications. This study integrates Large Eddy Simulation (LES) with the Stochastic Inversion (SI) method to validate the algorithm’s capacity for accurate reconstruction of atmospheric fluctuations. The initial findings demonstrate the efficacy of the method in accurately capturing the predominant flow structures. Normalized L2 error evaluations further inform the algorithm’s precision, with errors accentuated in less sampled peripheral regions. The results underscore the method’s promise as a non-intrusive observational tool, with ongoing development poised to improve its precision and reliability.

Measurement the 3D temperature distribution in the combustion zone using acoustic tomography and nolinear wavefont tracing

A non-invasive temperature measurement method in three dimensions is proposed to reconstruct the three-dimensional temperature. It relies on the use of nonlinear acoustic travel-time tomography, which incorporates acoustic path tracing, Gaussian kernel function, and modified Tikhonov regularization. Sound signals can be distorted due to large average temperature gradients and oscillatory release of heat in the combustion region. The effective acoustic signal is extracted based on spectral subtraction to evaluate the sound propagation time under distorted signals. The analysis of experimental errors indicates that the proposed acoustic pyrometry method has an average relative error of less than 15% compared to the time-averaged temperature measured by thermocouples. This result verifies the efficacy of the method when it comes to accurately reconstructing the temperature field in the combustion area. The reduction in error is attributed to the consideration of acoustic ray tracing within the proposed method.

Acoustic Travel-Time TOMography Technique to Reconstruct the Indoor Temperature: How to Improve the Field Reconstruction Quality?

Acoustic Travel-Time TOMography Technique to Reconstruct the Indoor Temperature: How to Improve the Field Reconstruction Quality?

Krylov Subspace Methods for Regularized Models in Acoustic Temperature Reconstruction From Simulated and Real Measurements

In a microwave heating system, there is usually an anomaly like thermal runaway or local overheating due to the propagation characteristics of electromagnetic waves during the heating process. The anomalous situation can be coped with by analyzing the temperature information obtained from acoustic travel time tomography. The aim of the research is to investigate the possibility of applying the acoustic approach to microwave heating. When applying acoustic tomography, an ill-conditioned least-squares problem is formulated, and the problem is hard to solve for super bad condition numbers of the coefficient matrices. In computational mathematics, researchers make a lot of effort in developing Krylov subspace methods to solve ill-conditioned problems. Some existing methods show slow convergence for practical applications, which motivates us to improve one Krylov subspace method based on real cases. Our method can be treated as an application of heavy ball minimal residual (HBMR) method to regularized least-squares problems. Based on the data collected from a measurement platform that simulates the internal circumstance of the heating system, our method is compared with certain classical Krylov subspace methods from aspects of convergence rate, reconstruction accuracy, and anti-interference capacity. Numerical experiments demonstrate a significant improvement in convergence rate on our method for regularized ill-conditioned problems. In addition, we display how to select an optimal kernel function. Details of choosing the optimal parameter are shown as well.

3D high-quality temperature-field reconstruction method in furnace based on acoustic tomography

Reconstructed 3D high-quality temperature distribution in furnace can provide important information to better control boiler operations and to optimize the combustion process. Acoustic travel-time tomography is considered to be a promising method that uses the dependence of sound speed on temperature to reconstruct the temperature field. In this paper, a new 3D temperature field reconstruction method based on radial basis function approximation with polynomial reproduction (RBF-PR) and truncated generalized singular value decomposition (TGSVD) is proposed to solve the inverse problem. To improve the reconstruction quality, we consider the refraction effect of sound waves in the non-uniform temperature field and estimate the sound wave propagation path model in the reconstruction method. The shooting method with improved Powell algorithms is used to solve the propagation path model and obtain the relationship between the acoustic travel-time over the propagation path and temperature distribution. Simulations are implemented to evaluate the effectiveness of the proposed reconstruction method. The results indicate that compared with other methods, the new reconstruction method that considers the refraction effect can reconstruct temperature distribution with higher accuracy and better anti-noise ability. Experimental results also demonstrate that the temperature distribution can be reconstructed effectively by the proposed method.

Measurement of indoor air temperature distribution using acoustic travel-time tomography: Optimization of transducers location and sound-ray coverage of the room

Abstract Acoustic travel-time TOMography (ATOM) allows the measurement and reconstruction of air temperature distributions. Due to limiting factors, such as the challenge of travel-time estimation of the early reflections in the room impulse response, which heavily depends on the position of transducers inside the measurement area, ATOM is applied mainly outdoors. To apply ATOM in buildings, this paper presents a numerical solution to optimize the positions of transducers. This optimization avoids reflection overlaps, leading to distinguishable travel-times in the impulse response reflectogram. To increase the accuracy of the measured temperature within tomographic voxels, an additional function is employed to the proposed numerical method to minimize the number of sound-path-free voxels, ensuring the best sound-ray coverage of the room. Subsequently, an experimental set-up has been performed to verify the proposed numerical method. The results indicate the positive impact of the optimal positions of transducers on the distribution of ATOM-temperatures.

Elastic-wave evaluation of downhole hydraulic fracturing: Modeling and field applications

We numerically simulate elastic-wave propagation along a fluid-filled borehole with a hydraulically fractured formation. The numerical model is based on the results of hydraulic fracturing on laboratory specimens. Two typical models are simulated: a main fracture crossing the borehole and a fracture network extending from the borehole. In addition, both models contain small, secondary fractures surrounding the borehole. Our result indicates that wave propagation in the main-fracture model is characterized by significant S-wave anisotropy for polarization along and normal to the fracture orientation, with the magnitude of anisotropy depending on the fracture aperture and filling material. In contrast, no significant anisotropy is observed for the fracture network model. In both models, wave propagation is significantly affected by small-fracture-induced near-borehole velocity variation. Our modeling results provide a theoretical foundation for evaluating hydraulic fracturing using the borehole acoustic logging. The hydraulic fracture-induced S-wave anisotropy can be evaluated with the cross-dipole S-wave logging, and the fracturing-induced velocity change can be detected by acoustic traveltime tomography. We used field data examples to demonstrate the effectiveness and practicality of using the borehole acoustic techniques for hydraulic fracturing evaluation.

Line-averaging measurement methods to estimate the gap in the CO<sub>2</sub> balance closure – possibilities, challenges, and uncertainties

Abstract. An imbalance of surface energy fluxes using the eddy covariance (EC) method is observed in global measurement networks although all necessary corrections and conversions are applied to the raw data. Mainly during nighttime, advection can occur, resulting in a closing gap that consequently should also affect the CO2 balances. There is the crucial need for representative concentration and wind data to measure advective fluxes. Ground-based remote sensing techniques are an ideal tool as they provide the spatially representative CO2 concentration together with wind components within the same voxel structure. For this purpose, the presented SQuAd (Spatially resolved Quantification of the Advection influence on the balance closure of greenhouse gases) approach applies an integrated method combination of acoustic and optical remote sensing. The innovative combination of acoustic travel-time tomography (A-TOM) and open-path Fourier-transform infrared spectroscopy (OP-FTIR) will enable an upscaling and enhancement of EC measurements. OP-FTIR instrumentation offers the significant advantage of real-time simultaneous measurements of line-averaged concentrations for CO2 and other greenhouse gases (GHGs). A-TOM is a scalable method to remotely resolve 3-D wind and temperature fields. The paper will give an overview about the proposed SQuAd approach and first results of experimental tests at the FLUXNET site Grillenburg in Germany. Preliminary results of the comprehensive experiments reveal a mean nighttime horizontal advection of CO2 of about 10 µmol m−2 s−1 estimated by the spatially integrating and representative SQuAd method. Additionally, uncertainties in determining CO2 concentrations using passive OP-FTIR and wind speed applying A-TOM are systematically quantified. The maximum uncertainty for CO2 concentration was estimated due to environmental parameters, instrumental characteristics, and retrieval procedure with a total amount of approximately 30 % for a single measurement. Instantaneous wind components can be derived with a maximum uncertainty of 0.3 m s−1 depending on sampling, signal analysis, and environmental influences on sound propagation. Averaging over a period of 30 min, the standard error of the mean values can be decreased by a factor of at least 0.5 for OP-FTIR and 0.1 for A-TOM depending on the required spatial resolution. The presented validation of the joint application of the two independent, nonintrusive methods is in the focus of attention concerning their ability to quantify advective fluxes.

Acoustic travel-time tomography of the atmospheric surface layer at the Boulder Atmospheric Observatory

Acoustic tomography of the atmospheric surface layer (ASL) is based on travel-time measurements between speakers and microphones in a spatial array, which are arranged so as to create propagation paths through the region to be sampled. Then, the temperature and wind velocity fields inside the tomographic region are reconstructed by inverting the travel times. Tomography has certain advantages over conventional point measurements, such as spatial averaging and a quadratic growth of the observations relative to the number of sensors. An array built at the Boulder Atmospheric Observatory (BAO) enables horizontal-slice tomography of the ASL at a height of 8 m above the ground, in an 80 m x 80 m region. The instrumentation and principle of operation of the BAO tomography array are explained. Inverse algorithms for reconstruction of the temperature and wind velocity fields from the travel times are reviewed. Results in numerical simulations of the BAO tomography array and reconstruction of turbulence fields in tomography experiments are presented. Acoustic tomography of the atmosphere can also be performed at other spatial scales, ranging from a size of an ultrasonic anemometer/thermometer to the height of the atmospheric boundary layer and even in the stratosphere and thermosphere.

Real-time monitoring system of vortex wind field using coded acoustic wave signals between parallel array elements

An acoustic travel-time tomography system for the monitoring of the vortex wind flow velocity profile has been studied, where multichannel parallel acoustic transmitter/receiver pairs are placed along opposite sides of the monitoring region. For real-time high-speed collection and computation of data, a simultaneous transmission technique of using a pseudo-noise code-modulation signal was adopted, as well as a graphics processing unit with the use of an 8-channel indoor test system, bidirectional travel time lag data along 34 propagation paths were processed in parallel. By this means, vortex wind fields, including their 2D center position, were successfully monitored at a frame rate of approximately 1 s. Real-time tracking capability for a moving vortex wind field was examined. The results showed the feasibility of the method for the monitoring of outdoor moving vortex wind fields.

Integrated non-destructive assessment of concrete structures under flexure by acoustic emission and travel time tomography

Elastic stress wave methods are attracting increasing attention from researchers and practitioners for real time monitoring of structures as well as quantitative evaluation of damage. The acoustic emission (AE) and travel time tomography (TTT) techniques are promising elastic waves-based diagnosis approaches for condition assessment of structures. In this research, fiber reinforced concrete beams loaded under flexure were monitored using both the AE and TTT techniques. The primary aim was to evaluate the development of fracture in beams in a non-destructive manner, with the two adopted techniques complementing each other to provide a more reliable assessment. There was satisfactory agreement between the results of AE parametric analysis and tomographic reconstruction, suggesting the feasibility of integrating the two techniques for a more comprehensive and effective condition assessment of structures.

Acoustic Tomography of the Atmosphere Using Unscented Kalman Filter

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a new statistical-based acoustic travel-time tomography algorithm based on unscented Kalman filter (UKF) which is capable of reconstructing and tracking temperature and wind velocity fields (state variables) within a specified investigation area. The method exploits an iterative ray-tracing algorithm to handle situations when straight-ray assumption no longer holds. The observations used in the UKF process consists of the acoustic travel times computed for every pair of transmitter/reciever nodes deployed in the investigation area. A first-order spatial-temporal autoregressive model is used to account for state evolution in the UKF. To evaluate the performance of the UKF-based acoustic tomography method, 2-D fractal Brownian motion is used to generate synthetic temperature and wind velocity fields with spatial and temporal resolution of 1 m and 12 s, respectively. The UKF-based acoustic tomography algorithm is then compared to the well-known time-dependent stochastic inversion method. The results reveal the effectiveness of the proposed method for accurate and fast reconstruction of temperature and wind velocity fields.

A statistical-based approach for acoustic tomography of the atmosphere

Acoustic travel-time tomography of the atmosphere is a nonlinear inverse problem which attempts to reconstruct temperature and wind velocity fields in the atmospheric surface layer using the dependence of sound speed on temperature and wind velocity fields along the propagation path. This paper presents a statistical-based acoustic travel-time tomography algorithm based on dual state-parameter unscented Kalman filter (UKF) which is capable of reconstructing and tracking, in time, temperature, and wind velocity fields (state variables) as well as the dynamic model parameters within a specified investigation area. An adaptive 3-D spatial-temporal autoregressive model is used to capture the state evolution in the UKF. The observations used in the dual state-parameter UKF process consist of the acoustic time of arrivals measured for every pair of transmitter/receiver nodes deployed in the investigation area. The proposed method is then applied to the data set collected at the Meteorological Observatory Lindenberg, Germany, as part of the STINHO experiment, and the reconstruction results are presented.

Assessment of systematic measurement errors for acoustic travel-time tomography of the atmosphere

Two algorithms are described for assessing systematic errors in acoustic travel-time tomography of the atmosphere, the goal of which is to reconstruct the temperature and wind velocity fields given the transducers' locations and the measured travel times of sound propagating between each speaker-microphone pair. The first algorithm aims at assessing the errors simultaneously with the mean field reconstruction. The second algorithm uses the results of the first algorithm to identify the ray paths corrupted by the systematic errors and then estimates these errors more accurately. Numerical simulations show that the first algorithm can improve the reconstruction when relatively small systematic errors are present in all paths. The second algorithm significantly improves the reconstruction when systematic errors are present in a few, but not all, ray paths. The developed algorithms were applied to experimental data obtained at the Boulder Atmospheric Observatory.

Acoustic Tomography of the Atmosphere: Comparison of Different Reconstruction Algorithms

Acoustic travel-time tomography in the atmosphere is based on travel-time measurements of sound signals propagating along different known ray paths through a medium. Because the speed of sound mainly depends on temperature and flow properties, an inversion of these travel times allows an estimation of temperature and wind velocity fields. The main reconstruction techniques for solving such inverse problems are least-squares methods and stochastic inversion algorithms. In this study, five representatives belonging to these types of inverse approaches are evaluated by reconstructions of two-dimensional temperature distributions from synthetically generated and experimental data. The comparison of the reconstruction results reveals several differences between the algorithms concerning spatial resolution of the reconstructed image, accuracy, and computational efficiency. The stochastic approach provides accurate reconstructions of spatially highly resolved temperature fields when the turbulence characteristic is chosen carefully. Nevertheless, the choice of suitable turbulence parameters, the determination of measurement errors prior to an experiment as well as comparatively high memory requirements of this method are unfavorable for real-time analysis of measured data although possible. In contrast, fast and simple on-site interpretations of temperature fields with acceptable accuracy are feasible with least-squares methods.

Experimental Study of Sound Travel-Time Estimation Method in Stored Grain

One common and traditional method for detecting stored grain deterioration is to measure grain temperature by contact sensors. Many sensors are installed throughout the bin for this. Temperature maps can also be obtained using acoustic travel-time tomography, which would be more suitable for store grain due to its non-contact measurement. The measurement of sound travel-time in grain bulk was researched. A time-delay estimation method using triple correlation with wavelet transform is proposed for solving the problem of sound attenuation in grain bulk. A measurement system of sound travel-time based on virtual instrument was built. Sound travel-time in soybeans was measured by the proposed method, cross-correlation method, and cross-correlation with wavelet transform method. The results show that the proposed method is best in measurement stability and accuracy. Thus it is expected to be used in an actual acoustic temperature monitoring system for stored grain.

Tomographic Measurement of Vortex Air Flow Field Using Multichannel Transmission and Reception of Coded Acoustic Wave Signals

An acoustic travel time tomography system for the monitoring of the vortex wind flow velocity profile has been studied, where multichannel parallel acoustic transmitter/receiver pairs are placed along opposite sides of the monitoring region. Thus far, to prevent cross-talk between the elements, travel time collections must be made successively for every single transducer element. Hence, it is difficult to achieve real-time observation while maintaining the temporal variation in the air flow field. To realize simultaneous multichannel travel time collections, a coded modulation method is introduced using the Kasami sequence. To verify the validity of the method, basic examinations of both simulation and experiment data are carried out.

Acoustic tomographic imaging of temperature and flow fields in air

Acoustic travel-time tomography is a remote sensing technique that uses the dependence of sound speed in air on temperature and wind speed along the sound propagation path. Travel-time measurements of acoustic signals between several sound sources and receivers travelling along different paths through a measuring area give information on the spatial distribution of temperature and flow fields within the area. After a separation of the two influences, distributions of temperature and flow can be reconstructed using inverse algorithms. As a remote sensing method, one advantage of acoustic travel-time tomography is its ability to measure temperature and flow field quantities without disturbing the area under investigation due to insertion of sensors. Furthermore, the two quantities—temperature and flow velocity—can be recorded simultaneously with this measurement method. In this paper, an acoustic tomographic measurement system is introduced which is capable of resolving three-dimensional distributions of temperature and flow fields in air within a certain volume (1.3 m × 1.0 m × 1.2 m) using 16 acoustic transmitter–receiver pairs. First, algorithms for the 3D reconstruction of distributions from line-integrated measurements are presented. Moreover, a measuring apparatus is introduced which is suited for educational purposes, for demonstration of the method as well as for indoor investigations. Example measurements within a low-speed wind tunnel with different incident flow situations (e.g. behind bluff bodies) using this system are shown. Visualizations of the flow illustrate the plausibility of the tomographically reconstructed flow structures. Furthermore, alternative individual measurement methods for temperature and flow speed provide comparable results.