Adaptive Algebraic Reconstruction Technique Research Articles

Reconstruction Algorithm Optimization Based on Multi-Iteration Adaptive Regularity for Laser Absorption Spectroscopy Tomography

Laser absorption spectroscopy tomography is an effective combustion diagnostic method for obtaining simultaneous two-dimensional distribution measurements of temperature and gas molar concentrations. For the reconstruction process of complex combustion flames, a new algorithm named ‘multi-iterative adaptive optimization regularization’ (MIARO) is proposed. This algorithm is a further development of another algorithm known as the ‘modified adaptive algebraic reconstruction technique’ (MAART) with the improvement of the initial value and adaptive regularization parameter selections. In MIARO, the problem of the MAART’s initial value sensitivity is compensated for, and in addition, reconstruction parameters are also introduced into the regularization so that both the quality of reconstruction and the convergence of regularization are guaranteed. In butane burner experiments, an average relative error of 1.82% was achieved with MIARO, compared to 2.44% with MAART, which is a significant reduction of 25.1%. The simulation and experimental results clearly demonstrate that the MIARO algorithm can be used to reconstruct dynamic combustion fields and eliminate boundary artifacts with improved measurement accuracy and robustness.

Optical absorption tomography for temperature and H2O concentration imaging by a compact photoelectric detecting system combined with twice adaptive algebraic algorithm

Tunable diode laser absorption spectroscopy is a robust method for simultaneous measurements of temperature and gas species. Different from commercial detectors integrated with photodiode receivers and amplifiers as the detecting system, a custom-made photoelectric detecting system comprised of Ge detectors and separated amplifiers was designed. First, Ge detectors received optical power from laser beams and then converted it into electrical current signals. The trans-impedance amplifiers were used to convert the current signals to voltage signals. The second stage amplifiers further amplified the voltage signals. All amplifiers that integrated the electronic circuits were packed in a portable case. Finally, the amplified voltage signals were received by data acquisition card. In this way, detectors could be arranged more compact and are easier to facilitate expandability. In addition, absorption data were reconstructed using twice adaptive algebraic reconstruction technique (AART) algorithm. During the reconstruction, after obtaining the temperature distribution through AART algorithm, AART algorithm was adopted for the second time for H2O concentration distribution. This system was validated with measurements of one-dimensional average temperature in a high temperature tube furnace and the system combined with twice adaptive algebraic algorithm demonstrated in a square flow field containing McKenna burners for simultaneous measurements of temperature and H2O distribution. The results indicated the viability and potential of this system combined with twice adaptive algebraic algorithm for sensitive temperature and H2O distribution tomography.

Adaptive Algebraic Reconstruction Algorithms for GNSS Water Vapor Tomography

Objectives Global navigation satellite system(GNSS) tomography, characterized by reconstructing the three-dimensional distribution of the atmospheric water vapor, has proved its capacity for studying the extreme weather events. The ill-conditioned problem resulting from the GNSS acquisition geometry is the critical issue of the GNSS tomography system. Algebraic reconstruction techniques, with the advantages of simple iteration and fast convergence, has been widely applied to the tropospheric tomography. However, the error allocation principle based on the intersection length of GNSS rays with each ray-voxel affects the accuracy of tomographic results. An improved adaptive algebraic reconstruction techniques are proposed to address this problem. Methods In view of the unreasonable error allocation in the traditional algorithm, we suggest a new error allocation principle based on the variation of water vapor density(WVD) in voxels for the adaptive algorithms, in which the product of the intersection length and WVD is considered as a new principle to redistribute the difference between the GNSS slant water vapor(SWV)and the reconstructed SWV. Besides, the weight matrix model of elevation angles is introduced to the improved algorithm to optimize the tomographic results. Results The new algorithms are tested by measured data from Xuzhou continuously operating reference stations(CORS) network and radiosonde during July2016. Experimental results reveal that the WVD derived from the adaptive algorithms performs better than that of the general algorithms in root mean squared error(RMSE), standard deviation(STD) and mean absolute error(MAE), and the RMSE is decreased by 25.91%, 15.81%, and 24.64% for adaptive algebraic reconstruction technique(AART), adaptive multiplicative algebraic reconstruction technique(AMART)and adaptive simultaneous iterative reconstruction technique(ASIRT) respectively. Under the conditions of light rain, moderate rain and heavy rain, the adaptive algorithms retrieve better water vapor profile than the traditional ones. Conclusions Overall, the water vapor profile derived from the adaptive algorithms agrees with the radiosonde distribution better than the traditional algorithms, which reveals the advantage of the proposed method on optimizing the tomography solutions.

Studies on gas concentration reconstruction methods for simultaneous temperature and H2O concentration tomographic imaging in a flame based on tunable diode laser absorption spectroscopy

Analysis of spatial temperature and gas concentration distributions is of great importance for combustion research. Algebraic reconstruction technique (ART) and adaptive algebraic reconstruction technique (AART) based on tunable diode laser absorption spectroscopy are both widely used methods for temperature tomographic imaging in a flame. After being obtained the temperature tomography through iterative method, the gas concentration reconstruction could be determined from a simple division equation (direct gas concentration algorithm) or iterative algorithm (ART gas concentration algorithm or AART gas concentration algorithm) for the second time. For the latter, iterative algorithm was used twice through the whole process. A series of numerical simulations were carried out by three gas concentration reconstruction methods mentioned above. The results demonstrated that AART method had better robustness for different phantoms and stability in the case that measured projections contained different levels of noise. Experimental measurements in a flat methane/air flame on a McKenna burner under three different equivalence ratios (1.0, 0.9, and 0.8) were conducted using AART gas concentration algorithm. The reconstructed results coincide well with those results obtained by thermocouple and theoretical calculation. Both simulation and experiment demonstrate that the AART gas concentration algorithm would be reliable and suitable for simultaneous temperature and H2O concentration tomographic imaging during combustion. As a consequence, this method has unrivalled potential for two-dimensional combustion diagnosis.

Simultaneous measurement of gas distribution in a premixed flame using adaptive algebraic reconstruction technique based on the absorption spectrum

Four tomography algorithms, including the algebraic reconstruction technique, simultaneous iterative reconstruction technique, the multiplicative algebraic reconstruction technique, and the adaptive algebraic reconstruction technique (AART), are compared with each other based on the tunable diode laser absorption spectroscopy technique; the determination of the relaxation parameter is discussed to improve reconstruction quality and shorten computational time as much as possible. The calculated results demonstrate that the AART algorithm can produce the reconstruction results with better quality and less computational time. In the experimental measurement, the AART algorithm with a two-line thermometry scheme is adopted to measure the spatial distribution of H2O temperature and concentration, two H2O absorption lines near 1397.8 nm are selected, the temperature and H2O concentration in the McKenna plat premixed flames are experimentally reconstructed and analyzed, and the results of integrated tomography reconstruction are consistent with the thermocouple traverse measurement.

Numerical investigation of the two-dimensional gas temperature distribution based on tunable diode laser absorption spectroscopy

Based on tunable diode laser absorption spectroscopy and modified adaptive algebraic reconstruction technique, two-dimensional tomographic reconstruction was derived for the gas temperature distribution in the range of 600–1400 K in the controlled projections. It is explicitly shown that the quality of temperature reconstruction is heavily dependent on the relative sensitivity of the selected spectrum and the algorithm of modified adaptive algebraic reconstruction technique but independent of the complexity of the present field distribution. When the relative sensitivity is less than 1.5, the accuracy of reconstruction relates to the relative sensitivity of the selected spectrum and improves with the increase in relative sensitivity. When the relative sensitivity is larger than 1.5, the accuracy is mainly limited by the algorithm of modified adaptive algebraic reconstruction technique.

Modified adaptive algebraic tomographic reconstruction of gas distribution from incomplete projection by a two-wavelength absorption scheme

A modified adaptive algebraic reconstruction technique (MAART) with an auto-adjustment relaxation parameter and smoothness regularization is developed to reveal the tomographic reconstruction of H2O distribution in combustion from incomplete projections. Determinations of relaxation parameter and regularization factor are discussed with regard to the consideration of improvement in reconstruction and reduction of computational burden. A two-wavelength scheme from tunable diode laser absorption measurement, 7444.36 and 7185.59 cm ?1, is used to simplify the nonlinear solution problem for obtaining the tomographic distributions of concentration and temperature simultaneously. Results of calculations demonstrate that MAART can perform the reconstruction results more efficiently with little complex modification and much lower iterations as compared with the traditional algebraic reconstruction technique (ART) or simultaneous iterative reconstruction technique (SIRT) methods. The stability of the algorithm is studied by reconstruction from projections with random noise at different levels to demonstrate the dependence of reconstruction results on precise line-of-sight measurements.

Three-dimensional tomographic reconstruction of unstable ejection phenomena of droplets for electrohydrodynamic jet

The electrohydrodynamic (EHD) jet is becoming increasingly popular within industrial printing areas based on phenomena induced by electrical potentials. Regardless of the physical observations of unstable ejection phenomena in regions possessing high electric potential, quantitative visualization is still necessary; no report exists exemplifying quantitative visualization. Thus, the size, shape and position of EHD droplets were reconstructed in this study using developed three-dimensional tomography methods. Two computer-synthesized phantoms for the liquid meniscus containing small satellite droplets were generated according to actual images captured by two high-speed cameras. These droplets were made in order to numerically reconstruct droplet behavior. Four three-dimensional tomography methods, such as the algebraic reconstruction technique (ART), the adaptive algebraic reconstruction technique (AART), the simultaneous iterative reconstruction technique (SIRT) and the multiplicative algebraic reconstruction technique (MART), were developed to accurately mimic droplet movement using multiple image views. Four basis functions including the cubic B-spline, cosine, o-Moms and Keys basis functions were adopted in order to improve the performance of the tomographic reconstructions. After completing a comparison of the four tomography results, the MART method in association with the cubic cosine basis function was selected as the means to significantly improve reconstruction accuracy. Additionally, it was the applied method for the reconstruction of the droplet behavior from experimental projections by two cameras.

SU‐FF‐I‐37: An Adaptive Simultaneous Algebraic Reconstruction Technique

Purpose: To improve the computational efficiency of Algebraic Reconstruction Technique (ART), and suppress the “stripping” artifacts due to ART like ray‐by‐ray update, especially in cone‐beam reconstruction. Method and Materials: Inspired by Adaptive ART (AART) and Simultaneous ART (SART), a new ART, the Adaptive Simultaneous ART (ASART), which combines multi‐level scheme (MLS) data‐access scheme, data‐driven contribution weighting, and SART like updating, is proposed. When the CT system is modeled as Wv = p, ASART can be mathematically expressed as: urn:x-wiley:00942405:media:mp0414:mp0414-math-0001 where λ is.0 the relaxation factor that is typically chosen within the interval (0.0, 1.0] and the initial value are uniformly set to be a nonzero value. This method combines the advantages of SART and AART: the feature of SART, simultaneous correction image update in each view, is introduced into AART. In ASART, the reconstructed object is updated view‐by‐view, rather than ray‐by‐ray, and all views are accessed according to MLS. In general, the computation burden for ASART is less than that of SART. Results: For quality evaluation, we adopt a 3D extension of the Shepp‐Logan phantom, in which the least value variance is only 0.5% of the maximal value of the model, in our experiments. It is observed that ASART always achieves higher correlation coefficient (CC) than MLS‐SART does. Actually, 1‐iteration ASART produces much higher CC than 10‐iteration MLS‐SART does in our experiments. We have also applied the proposed approach on real dataset reconstruction. Fine image details are fairly visible in the slices obtained by our approach when only 96 limited numbers of projections are used. Conclusion: A new image reconstruction technique inspired by AART and SART is proposed in this work. Although the convergence has not been proved mathematically, this approach always performs well in our experiments. Both quantitative and visual analyses have shown that promising computational efficiency and better reconstructed image have been achieved.

Adaptive algebraic reconstruction technique

Algebraic reconstruction techniques (ART) are iterative procedures for reconstructing objects from their projections. It is proven that ART can be computationally efficient by carefully arranging the order in which the collected data are accessed during the reconstruction procedure and adaptively adjusting the relaxation parameters. In this paper, an adaptive algebraic reconstruction technique (AART), which adopts the same projection access scheme in multilevel scheme algebraic reconstruction technique (MLS-ART), is proposed. By introducing adaptive adjustment of the relaxation parameters during the reconstruction procedure, one-iteration AART can produce reconstructions with better quality, in comparison with one-iteration MLS-ART. Furthermore, AART outperforms MLS-ART with improved computational efficiency.