Accurate Velocity Measurements Research Articles

Optimal configuration design and attitude measurement method of redundant accelerometer for steering drilling tools

Abstract In order to improve the accuracy and reliability of attitude parameters measurement of the rotary steerable drilling tool, a slanting configuration method and measurement method of double accelerometer were proposed. The measurement equation of the redundant accelerometer in the drill coordinate system is established. According to the installation position of the accelerometer and sensitive direction, the trouble-free and uniaxial failure in both cases, in order to improve the component of gravity and angular velocity calculation precision as the objective, design measure performance evaluation indexes, the optimal configuration determines the redundant accelerometer. It uses the stability equation constraints gravity no trace adaptive Kalman filter algorithm, Accurate angular velocity measurement, the tool face Angle, and healthy inclination. Simulation and experimental results show that the optimal configuration of the redundant accelerometer is reasonable, and the attitude estimation algorithm is effective.

Phase contrast MRI with minimized background phase errors.

Phase contrast MRI (PC-MRI) is used clinically to measure velocities in the body, but systematic background phase errors caused by magnetic field imperfections corrupt the velocity measurements with offsets that limit clinical utility. This work aims to minimize systematic background phase errors in PC-MRI, thereby maximizing the accuracy of velocity measurements. The MRI scanner's background phase errors from eddy currents and mechanical oscillations were modeled using the gradient impulse response function (GIRF). Gradient waveforms were then numerically optimized using the GIRF to create pulse sequences that minimize the background phase errors. The pulse sequences were tested in a static phantom where the predicted response could be compared directly to the measured background velocity. The optimized acquisitions were then tested in human subjects, where flow rates and background errors were compared to conventional PC-MRI. When using the GIRF-optimized gradient waveforms, the predicted background phase was within 0.6 [95% CI = -3.4, 5.4] mm/s of the measured background phase in a static phantom. Excellent agreement was seen for in vivo blood flow values (flow rate agreement = 0.96), and the background phase was reduced by 78.8 18.7%. This work shows that using a GIRF to model the effects of magnetic field imperfections combined with numerically optimized gradient waveforms enables PC-MRI waveforms to be designed to produce a minimal background phase in the most time-efficient manner. The methodology could be adapted for other MRI sequences where similar magnetic field errors affect measurements.

Enhancing the correlation between azimuth and Doppler frequency for speed estimation of nearby tangential targets

With the development of intelligent transportation systems, traffic supervision radar with wide coverage plays a crucial role in traffic management and vehicle-road coordination. The correlation between Doppler frequency and azimuth has been widely validated in wide coverage traffic supervision radar for high-precision velocity measurement. However, angular glint and noise of the nearby targets lead to a decrease in correlation between the azimuth and Doppler frequency, which negatively impacts the accuracy of velocity estimation. Currently, adopting separate filtering strategies for target azimuth and Doppler frequency has limited performance in enhancing correlation. This paper presents a joint observation model for azimuth and Doppler frequency to achieve the extraction of interrelated components from subspaces, which improves the accuracy of velocity measurement. The effectiveness of this approach is validated using data obtained from X-band and Ku-band sensors.

Updated Kinematics of the Radcliffe Wave: Nonsynchronous, Dipole-like Vertical Oscillations

The kinematic information of the Radcliffe wave (RW) is essential for determining its existence and gaining insights into its origin and evolution. In this work, we present an accurate measurement of the vertical velocity (V Z ) of the RW by incorporating the radial velocity (RV) measures through two methods, which is crucial but was neglected previously. First, the velocities are measured toward young stars, using their RV measurements from APOGEE-2 and proper motion measurements from Gaia DR3. Second, we combine RV measurements toward clouds with proper motion measurements of associated young stellar objects to determine the vertical velocities of the clouds. The results reveal that the oscillations in V Z are not synchronous with the vertical coordinate Z, which differs from the conclusions of previous studies. Instead, we find a 5 km s−1 kpc−1 gradient in V Z along the RW, exhibiting a dipole-like pattern. Consequently, the kinematic arrangement does not show a corresponding coherence with the spatial arrangement, bringing the RW model into question.

Analysis of the limits of applicability of photomultiplier as part of a laser Doppler anemometer

This paper considers the use of laser Doppler anemometry methods for non-contact measurement of the velocity of a moving medium in various phase states. It notes the specifi city of conditions of application of laser Doppler anemometers, in that in a number of cases there are restrictions on the use of photomultipliers. In order to find an alternative to the classic photomultiplier of a laser Doppler anemometer, three types of photomultipliers were investigated: classic electric vacuum; silicon avalanche multipixel; with microchannel plate. Physical experiments were conducted to measure the velocity of aero- and hydrodynamic fl ows by laser Doppler anemometer with photomultipliers of three types. The velocities of a rotating glass disk, aerodynamic fl ow in a channel of rectangular cross-section, and aerosol flow, as well as hydrodynamic flooded jet, were measured. The obtained experimental data were analyzed according to the criteria for assessing the quality (efficiency) of operation and finding the limits of applicability of the specified photomultipliers. Based on the physical properties of the studied photomultipliers, their efficiency indicators in various experiments are explained. The boundaries of the effective use of these photomultipliers in a wide class of physical experiments are determined. The results obtained are important for researchers involved in the study of aero- and hydrodynamic flows, where accurate and reliable measurements of flow velocity are required. The choice of an optimal photomultiplier tube for the laser anemometer allows increasing the accuracy and ease of obtaining experimental data and reducing the cost of the final equipment.

The velocity extraction and feature analysis of glacier surface motion in the Gongar region based on multi-source remote sensing data

The movement of glaciers plays a crucial role in environmental and geological processes, significantly influencing the formation and dynamics of ice bodies. This study leverages feature tracking technology to analyze optical and Synthetic Aperture Radar (SAR) remote sensing imagery, specifically GF-1 optical images and GF-3, Sentinel-1 SAR images, captured during the 2020 to 2021 ablation season in Gongar. The aim was to quantify glacier surface velocities and to evaluate the comparative effectiveness of different remote sensing modalities in capturing these dynamics. Our findings indicate a strong consistency in the spatial distribution of glacier surface velocities derived from diverse remote sensing data sources, with high-precision optical imagery (GF-1) yielding the most accurate velocity measurements, followed by Sentinel-1 SAR data. Notably, large glaciers in Gongar exhibited rapid movements, with an average velocity of 0.16 m/d, primarily at elevations between 4,500 and 6,500 m. The fastest velocities were recorded at approximately 4,500 m elevation. Glaciers with inclines ranging from 10° to 60° displayed the highest velocities within the 20°–30° slope range. It was observed that glaciers on the southeast slope moved faster, exhibiting the highest average surface velocity, in contrast to those on the west slope, which moved more slowly. The surface velocity of the ice tongue region of Krayaylak Glacier that the largest glacier in Pamir, was observed to be lower than 0.6 m/d, indicating a slow movement speed. The study also reveals that the effectiveness of different remote sensing data in detecting glacier velocity in Gongar, with high-resolution data more accurately capturing surface velocities in melting areas or those with slower movement. This study underscores the importance of multi-source remote sensing data in understanding glacier dynamics and contributes valuable insights into the mechanisms driving glacier movements.

A novel method for measuring center-axis velocity of unmanned aerial vehicles through synthetic motion blur images

Accurate velocity measurement of unmanned aerial vehicles (UAVs) is essential in various applications. Traditional vision-based methods rely heavily on visual features, which are often inadequate in low-light or feature-sparse environments. This study presents a novel approach to measure the axial velocity of UAVs using motion blur images captured by a UAV-mounted monocular camera. We introduce a motion blur model that synthesizes imaging from neighboring frames to enhance motion blur visibility. The synthesized blur frames are transformed into spectrograms using the Fast Fourier Transform (FFT) technique. We then apply a binarization process and the Radon transform to extract light-dark stripe spacing, which represents the motion blur length. This length is used to establish a model correlating motion blur with axial velocity, allowing precise velocity calculation. Field tests in a hydropower station penstock demonstrated an average velocity error of 0.048 m/s compared to ultra-wideband (UWB) measurements. The root-mean-square error was 0.025, with an average computational time of 42.3 ms and CPU load of 17%. These results confirm the stability and accuracy of our velocity estimation algorithm in challenging environments.

Thermodynamics of micellization of octyltrimethylammonium bromide in 1,2-propanediol-water mixtures at temperatures from (293.15 to 308.15) K

The micellar properties of octyltrimethylammonium bromide (C8TAB) in both water and aqueous solutions of 1,2-propanediol have been investigated using accurate measurements of density, sound velocity, and surface tension in the temperature range between 293.15 and 308.15 K. The critical micelle concentration, CMC, the ionization degree, β, the standard thermodynamic parameters of micellization: free energy, ΔmicG°, enthalpy, ΔmicH°, entropy, ΔmicS° and the free energy of transfer, ΔtrG°, of the surfactant octyltrimethylammonium bromide in both water and 1,2 propanediol aqueous solution were evaluated from the experimental results.The CMC of the surfactant increases as the concentration of 1,2-propanediol increases, while the temperature does not exert important changes within the range considered.The value of the micellization thermodynamic parameters suggests that adding 1,2-propanediol makes the micellization process less favorable.The thermodynamic functions of transfer were calculated. The values of the free energy of transfer are small and positive and increase as the diol concentration increases confirming that the transfer of the surfactant from the bulk into the micelle is less favorable.

A Waveform and Velocity Ambiguity Resolution Method for Corner Radar

Millimeter-wave radar is experiencing an increasing demand for higher resolution and elevation measurement, necessitating its evolution from 3D millimeter-wave radar systems to 4D millimeter-wave radar. Unlike front automotive radar, corner radar is particularly interested in close-range targets. This article proposes a composite waveform tailored for automotive corner radar, employing different waveform schemes for various distances. This allows millimeter-wave angle radar to achieve superior range resolution and velocity resolution in the close and medium ranges. However, enhancing velocity resolution inevitably results in a reduction in the maximum unambiguous velocity. Consequently, a velocity ambiguity resolution method based on target parameter matching for front and rear frames is proposed to address this issue. The feasibility of the composite waveform and method are verified through simulation. Finally, a radar designed with the ALPS PRO chip is employed to test the designed waveform and velocity ambiguity resolution method, yielding results that are largely consistent with the simulation outcomes. The findings indicate a notable enhancement in resolution for medium distances ranging from 60 to 100 m when employing the proposed waveform. Moreover, the velocity ambiguity resolution method effectively resolves velocity ambiguity, leading to enhanced accuracy in velocity measurements. This suggests that the composite waveform and algorithm are well suited for current automotive angle radar applications.

Internal-multiple-elimination with application to migration using two-way wave equation depth-extrapolation scheme

Internal multiple interference, affecting both seismic data processing and interpretation, has been observed for long time. Although great progress has been achieved in developing a variety of internal-multiple-elimination (IME) methods, how to increase accuracy and reduce cost of IME still poses a significant challenge. A new method is proposed to effectively and efficiently eliminate internal multiples, along with its application in internal-multiple-eliminated-migration (IMEM), addressing this issue. This method stems from two-way wave equation depth-extrapolation scheme and associated up/down wavefield separation, which can accomplish depth-extrapolation of both up-going and down-going wavefields simultaneously, and complete internal-multiple-elimination processing, adaptively and efficiently. The proposed method has several features: (1) input data is same as that for conventional migration: source signature (used for migration only), macro velocity model, and receiver data, without additional requirements for source/receiver sampling; (2) method is efficient, without need of iterative calculations (which are typically needed for most of IME algorithms); and (3) method is cost effective: IME is completed in the same depth-extrapolation scheme of IMEM, without need of a separate processing and additional cost. Several synthesized data models are used to test the proposed method: one-dimensional model, horizontal layered model, multi-layer model with one curved layer, and SEG/EAGE Salt model. Additionally, we perform a sensitivity analysis of velocity using smoothed models. This analysis reveals that although the accuracy of velocity measurements impacts our proposed method, it significantly reduces internal multiple false imaging compared to traditional RTM techniques. When applied to actual seismic data from a carbonate reservoir zone, our method demonstrates superior clarity in imaging results, even in the presence of high-velocity carbonate formations, outperforming conventional migration methods in deep strata.

Rotary-wing drone-induced flow – comparison of simulations with lidar measurements

Abstract. Ultrasonic anemometers mounted on rotary-wing drones have the potential to provide a cost-efficient alternative to the classical meteorological mast-mounted counterpart for atmospheric boundary layer research. However, the propeller-induced flow may degrade the accuracy of free-stream wind velocity measurements by wind sensors mounted on drones – a fact that needs to be investigated for optimal sensor placement. Computational fluid dynamics (CFD) simulations are an alternative to experiments for studying characteristics of the propeller-induced flow but require validation. Therefore, we performed an experiment using three short-range continuous-wave Doppler lidars (light detection and ranging; DTU WindScanners) to measure the complex and turbulent three-dimensional wind field around a hovering drone at low ambient wind speeds. Good agreement is found between experimental results and those obtained using CFD simulations under similar conditions. Both methods conclude that the disturbance zone (defined as a relative deviation from the mean free-stream velocity by more than 1 %) on a horizontal plane located at 1 D (rotor diameter D of 0.71 m) below the drone extends about 2.8 D upstream from the drone center for the horizontal wind velocity and more than 7 D for the vertical wind velocity. By comparing wind velocities along horizontal lines in the upstream direction, we find that the velocity difference between the two methods is ≤ 0.1 m s−1 (less than a 4 % difference relative to the free-stream velocity) in most cases. Both the plane and line scan results validate the reliability of the simulations. Furthermore, simulations of flow patterns in a vertical plane at the ambient speed of 1.3 m s−1 indicate that it is difficult to accurately measure the vertical wind component with less than a 1 % distortion using drone-mounted sonic anemometers.

A flue gas velocimeter based on the hyperbolic chirp modulation method of acoustic source signal

Accurate measurement of flue gas velocity is of great significance for the safe production, energy saving, and emission reduction of coal-fired power plants. In this paper, a method of flue gas velocimetry based on a hyperbolic chirp-modulating acoustic source was proposed, and its superiority was verified by numerical simulations and field experiments. For an acoustic velocimeter, it is crucial to ensure the accuracy of the acoustic Time-of-Flight (TOF), which directly affects the flue gas velocity measurements. The improvement of the accuracy of estimation of the TOF directly determines the accuracy of the flue gas velocity measurement. Simulation on the different types of acoustic sources at different signal-to-noise ratios (SNRs) was conducted, and the results proved that the hyperbolic chirp signal is more accurate in the measurement of TOF. In the strong noise range of − 10 dB to − 20 dB, the average relative root mean square error (RRMSE) obtained using this hyperbolic chirp modulating acoustic source is 0.60 dB and 0.36 dB lower than obtained using the linear and logarithmic modulating modes, respectively. The average relative error (RE) is approximately 0.87 times that of the linear chirp. Power plant flue field experiments show that the measurement error using this hyperbolic modulating mode is about 0.52 times and 0.74 times that of using linear and logarithmic modulating modes, respectively. In harsh measurement environments with strong noise, the proposed acoustic source modulation scheme can significantly improve the measurement SNR and effectively enhance the accuracy and robustness of flue gas velocimetry.

Rotational Doppler effect of vortex beam with frequency-shifted laser feedback

We propose and demonstrate a rotational Doppler measurement system based on frequency-shifted laser feedback interferometry. The system utilizes a vortex beam as the probe, which is modulated by the target and then reflected back into the laser cavity. Compared with the conventional rotational Doppler methods, this approach effectively enhances the amplitude of the generated beat signal through intra-cavity interference between the echo signal and local oscillator. Consequently, it improves sensitivity in weak-signal detection and enables measurement with low probe-beam power. A signal to noise (SNR) enhancement of over 15 dB was observed compare to the Mach-Zehnder structure. This system inherits the advantages of rotational Doppler effect, possessing the capacity to get a frequency proportional to the topological charge of vortex. Experimental validation demonstrates accurate measurement of rotational angle and velocity, with the ability to distinguish rotational direction through heterodyne detection. For vortices with topological charge ranging from 18 to 21 and rotational speeds in range of 150 to 600 revolutions per minute (RPM), the measurement error is within ±3 RPM. Overall, the proposed system possesses high sensitivity to echo signal, low photon consumption, and direction information availability, which provides a new approach for optimizing the rotational Doppler effect in practical applications.

Three-dimensional particle image velocimetry measurement through three-dimensional U-Net neural network

This paper proposes a light field (LF) three-dimensional (3D) particle image velocimetry (PIV) method based on a digital refocused algorithm and 3D U-Net neural network for 3D three-component (3D-3C) velocity measurement. A digital refocused algorithm is used to generate a stack of LF-refocused images of tracer particles for establishing the 3D U-Net. The 3D U-Net is then used for the 3D particle field reconstruction. Based on a pair of 3D particle fields, the 3D-3C velocity field is obtained through a 3D cross correlation algorithm. Numerical simulations and experiments are conducted to analyze the accuracy and efficiency of the proposed method. The simulation results show that the elongation along the depth direction and the efficiency of the 3D particle field reconstruction are improved by the 3D U-Net. The 3D U-Net also provides a better correlation coefficient. The experimental results show that the reconstruction time of the proposed method is ∼220 s which is 10 times faster than the LF tomographic PIV. This further demonstrates that the proposed method improves the reconstruction efficiency without affecting the accuracy of velocity measurement.

An RTK UAV-Based Method for Radial Velocity Validation of Weather Radar

The quality of weather radar affects the reliability and effectiveness of monitoring severe convective weather. Therefore, rigorous calibration and validation are the foundation for the quantitative application of weather radar. Among the available methods, radial velocity validation is of great significance for reducing the false alarm rate in the identification of tornadoes and thunderstorms. Based on the traditional method that utilizes internal and external instrument radar velocity measurements, we propose a weather radar radial velocity validation method that uses RTK UAV to simulate external targets. In addition, according to the characteristics of the UAV application scenarios, we introduce the evaluation parameter of optimal absolute accuracy to supplement the original parametric system. The experimental results show that the evaluation parameter of optimal absolute accuracy can effectively reduce the interference caused by the systematic deviation of the UAV due to the internal and external environment, which can affect the validation results. When the UAV velocity is not greater than 10 m/s, the optimal absolute accuracy of the radial velocity validation is less than 0.05 m/s, which is essentially consistent with the external instruments’ measurement results. This method can be effectively applied to the procedural handling of weather radar radial velocity validation. It is significant for ensuring the accuracy and quality of weather radar radial velocity measurements and improving the effectiveness of radar velocity data applications.

Turbulence model augmented physics-informed neural networks for mean-flow reconstruction

Experimental measurements and numerical simulations of turbulent flows are characterized by a tradeoff between accuracy and resolution. In this study, we combine accurate sparse pointwise mean velocity measurements with the Reynolds-averaged Navier-Stokes (RANS) equations using data assimilation methods. Importantly, we bridge the gap between data assimilation (DA) using physics-informed neural networks (PINNs) and variational methods based on classical spatial discretization of the flow equations, by comparing both approaches on the same turbulent flow case. First, by constraining the PINN with sparse data and the underdetermined RANS equations without closure, we show that the mean flow is reconstructed to a higher accuracy than a RANS solver using the Spalart-Allmaras (SA) turbulence model. Second, we propose the SA turbulence model augmented PINN (PINN-DA-SA), which outperforms the former approach by up to 73% reduction in mean velocity reconstruction error with coarse measurements. The additional SA physics constraints improve flow reconstructions in regions with high velocity and pressure gradients and separation. Third, we compare the PINN-DA-SA approach to a variational data assimilation using the same sparse velocity measurements and physics constraints. The PINN-DA-SA achieves lower reconstruction error across a range of data resolutions. This is attributed to discretization errors in the variational methodology that are avoided by PINNs. We demonstrate the method using high-fidelity measurements from direct numerical simulation of the turbulent periodic hill at Re=5600. Published by the American Physical Society 2024

Probing the Global 21 cm Background by Velocity-induced Dipole and Quadrupole Anisotropies

The motion of an observer in the rest frame of the cosmic 21 cm background induces an anisotropy in the observed background, even when the background is isotropic. The induced anisotropy includes a dipole and a quadrupole, in the order decreasing in amplitude. If observed, these multipole anisotropies can be used as additional probes of the spectral shape of the global 21 cm background for mitigating the ambiguity in the monopole spectrum probed by single-element radio telescopes such as EDGES and SARAS. This could also help with understanding the astrophysical and cosmological processes that occurred during the cosmic dawn and the epoch of reionization, and even improve the estimation of the solar velocity and the foreground spectra. Here, we study the feasibility of such observations and present science drivers for the measurement of the 21 cm dipole and quadrupole. We find that future 21 cm experiments can in principle detect the 21 cm dipole to high significance, potentially improving measurement accuracy of Earth velocity with respect to the Milky Way, galactic, and extragalactic foreground monopole spectra by an order of magnitude, as well as improving 21 cm astrophysical parameters by 2%–5%.

Research on Measuring System of Sodium Hydroxide Concentration in Impregnation Solution Based on Ultrasonic Velocity Method

A sound velocity measurement system based on FPGA was designed. The time of flight was calculated by using the wave crest of ultrasonic signal to achieve high precision measurement of sound velocity. The high-speed data communication between field programmable gate array (FPGA) and host computer system is realized by using AN9238, DPRAM and 485 communication port. On the basis of FPGA hardware, high-speed AD chip is used for sampling to complete data storage and processing. The experimental results show that compared with the standard system, the time-of-flight measurement accuracy of the designed system is 0.1㎲, and the measurement accuracy of the solution sound velocity is better than 2 m/s, which verifies the reliability of the scheme.

Enhancing the accuracy of rotational velocity measurement for vortex beams within the optimal ability of phase retrieval algorithm

The measurement of the rotational velocity using the rotational Doppler effect (RDE) of a vortex beam is easily affected by atmospheric turbulence, leading to dispersed orbital angular momentum (OAM), and reduced measurement accuracy. This study investigates the optimal ability of the Gerchberg-Saxton (GS) phase retrieval algorithm to compensate for the optical field and enhance the velocity measurement accuracy within the optimal range of intrinsic parameters, such as the number of GS iterations, and extrinsic parameters, such as the atmospheric turbulence intensity and beam properties. Through detailed theoretical and simulation analyses, we demonstrate the outstanding effectiveness of the GS algorithm in improving the velocity measurement accuracy. Simulations conducted for a system-target distance of zS-T = 500 m show a 29.88% improvement in the velocity measurement accuracy and a 1.03-fold increase in the spectral signal-to-noise ratio (SSNR) within the optimal range. It showcases advantages that set it apart from other methods. This study reveals the threshold of the ability of GS algorithm to significantly enhance the rotational velocity measurement accuracy, providing valuable insights to precision measurements of rotational velocities in free-space applications.

Adaptive Position Feedback Control of Parallel Robots in the Presence of Kinematics and Dynamics Uncertainties

Uncertainties in the kinematic and dynamic parameters of a parallel robot are unavoidable. The problem is more crucial in the cases where the manipulator interacts with the environment and when it is large–scale or deployable. Furthermore, precise measurement of the velocity of the end-effector is almost inaccessible in practice. This paper addresses the above shortcomings by designing of an adaptive trajectory tracking controller with merely position feedback of joint and task space variables. Simplicity of implementation, separation of adaptation laws of dynamic and kinematic parameters, and reduction of the number of adaptation laws such that in some cases, e.g., cable-driven robots, it is identically equivalent to the number of unknown parameters are some advantages of the proposed controller. The method’s efficiency is shown via implementation on a cable-driven parallel manipulator and an intraocular surgery robot. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In order to achieve a suitable response in parallel robots with traditional controllers, a precise knowledge of kinematic and dynamic parameters, together with accurate measurement of velocity, is required. In practice, these values are usually derived by robot calibration and identification. Since the system’s parameters may alter or depend on external factors such as temperature, these time-consuming methods should be implemented repeatedly while the robot is out of duty. Additionally, precise velocity measurement is a prohibitive task and requires expensive instruments. This article presents a controller to address the above shortcomings. By this means, a simple adaptive controller based on position feedback is designed such that via suitable estimation of kinematic and dynamic parameters, trajectory tracking is obtained without the need for accurate initial estimates of the parameters. The proposed method has a number of advantages, including separation of the adaptation laws of kinematic parameters and dynamic parameters, simple representation of the Jacobian matrix in regressor form, and there is no requirement for velocity feedback. Furthermore, a force distribution method is introduced for redundant robots. Hence, the proposed controller is an appropriate alternative to traditional controllers widely used in industries.