Real-time Velocity Measurement Research Articles

Extension Of Spatial Filtering Technique Using Kalman Filters For Real-Time Pipe Flow Profile Measurements

Spatial filtering is used for real-time velocity measurement due to its computational efficiency. However, this method can be noisy in real measurement environments, requiring the averaging of a substantial number of measurements to achieve reliable results, which compromises temporal resolution. This study proposes enhancing the spatial filtering algorithm by implementing Kalman filtering for pipe flow profile measurements. Kalman filtering is expected to mitigate the noise issue more effectively than traditional methods like low-pass filtering while maintaining or improving the temporal resolution of measurements.

Spatio-spectral 4D coherent ranging using a flutter-wavelength-swept laser

Coherent light detection and ranging (LiDAR), particularly the frequency-modulated continuous-wave LiDAR, is a robust optical imaging technology for measuring long-range distance and velocity in three dimensions (3D). We propose a spatio-spectral coherent LiDAR based on a unique wavelength-swept laser to enable both axial coherent ranging and lateral spatio-spectral beam scanning simultaneously. Instead of the conventional unidirectional wavelength-swept laser, a flutter-wavelength-swept laser (FWSL) successfully decoupled bidirectional wavelength modulation and continuous wavelength sweep, which overcame the measurable distance limited by the sampling process. The decoupled operation in FWSL enabled sequential sampling of flutter-wavelength modulation across its wide spectral bandwidth of 160 nm and, thus, allowed simultaneous distance and velocity measurement over an extended measurable distance. Herein, complete four-dimensional (4D) imaging, combining real-time 3D distance and velocity measurements, was implemented by solid-state beam scanning. An acousto-optic scanner was synchronized to facilitate the other lateral beam scanning, resulting in an optimized solid-state coherent LiDAR system. The proposed spatio-spectral coherent LiDAR system achieved high-resolution coherent ranging over long distances and real-time 4D imaging with a frame rate of 10 Hz, even in challenging environments.

OPTIMIZATION OF THE USAGE OF 35 MM ANTI-AIRCRAFT GUN BARRELS IN TERMS OF RELIABILITY AND ECONOMIC EFFICIENCY

The scientific basis for optimizing the use of work resources of 35 mm anti-aircraft gun barrels, enabling their durability to be increased by 25÷100% while improving operational efficiency indicators are presented in this paper. The development of a new approach to assessing the durability and effectiveness of these barrels results from current solutions and capabilities of navigation and targeting systems, new generation projectiles (programmable ammunition with sub-projectiles) and real-time muzzle velocity measurement applications (while main-taining or even increasing the current muzzle velocity and rate of fire). This increases the probability of hitting floating, coastal and flying targets (especially UAVs and RAM). It has been shown that the durability and operational assessment of this class of guns (including economic efficiency) is not determined only by indicators based on the rate of fire, muzzle velocity or second burst of fire. What is now more important is the ability to reduce the rate of barrel destructive processes, resulting from the possibility of shortening the length of firing series. It has been shown that with short series, the barrels wear and the intensity of damage to the reload mechanisms are significantly reduced. The phenomenon of barrel overheating is also limited, and thus operational indicators are improved (average time to failure, continuous operation time, ammunition usage), which significantly reduces the cost of operating the guns.

Analysis of Perception Accuracy of Roadside Millimeter-Wave Radar for Traffic Risk Assessment and Early Warning Systems.

Millimeter-wave (MMW) radar is essential in roadside traffic perception scenarios and traffic safety control. For traffic risk assessment and early warning systems, MMW radar provides real-time position and velocity measurements as a crucial source of dynamic risk information. However, due to MMW radar's measuring principle and hardware limitations, vehicle positioning errors are unavoidable, potentially causing misperception of the vehicle motion and interaction behavior. This paper analyzes the factors influencing the MMW radar positioning accuracy that are of major concern in the application of transportation systems. An analysis of the radar measuring principle and the distributions of the radar point cloud on the vehicle body under different scenarios are provided to determine the causes of the positioning error. Qualitative analyses of the radar positioning accuracy regarding radar installation height, radar sampling frequency, vehicle location, posture, and size are performed. The analyses are verified through simulated experiments. Based on the results, a general guideline for radar data processing in traffic risk assessment and early warning systems is proposed.

Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging.

Determining brain hemodynamics plays a critical role in the diagnosis and treatment of various cerebrovascular diseases. In this work, we put forth a physics-informed deep learning framework that augments sparse clinical measurements with one-dimensional (1D) reduced-order model (ROM) simulations to generate physically consistent brain hemodynamic parameters with high spatiotemporal resolution. Transcranial Doppler (TCD) ultrasound is one of the most common techniques in the current clinical workflow that enables noninvasive and instantaneous evaluation of blood flow velocity within the cerebral arteries. However, it is spatially limited to only a handful of locations across the cerebrovasculature due to the constrained accessibility through the skull's acoustic windows. Our deep learning framework uses in vivo real-time TCD velocity measurements at several locations in the brain combined with baseline vessel cross-sectional areas acquired from 3D angiography images and provides high-resolution maps of velocity, area, and pressure in the entire brain vasculature. We validate the predictions of our model against in vivo velocity measurements obtained via four-dimensional (4D) flow magnetic resonance imaging (MRI) scans. We then showcase the clinical significance of this technique in diagnosing cerebral vasospasm (CVS) by successfully predicting the changes in vasospastic local vessel diameters based on corresponding sparse velocity measurements. We show this capability by generating synthetic blood flow data after cerebral vasospasm at various levels of stenosis. Here, we demonstrate that the physics-based deep learning approach can estimate and quantify the subject-specific cerebral hemodynamic variables with high accuracy despite lacking knowledge of inlet and outlet boundary conditions, which is a significant limitation for the accuracy of the conventional purely physics-based computational models.

Real-time distance and velocity measurement based on the dual-comb system.

With the development of laser metrology, the dual-comb system has natural superiority in the measuring fields. Specifically, distance and velocity represent a basic state for the target in space. We propose an application mode of the dual-comb interferometry integrated into the field programmable gate array. A high-speed parallel processor truly gives full play to the benefit of the data processing rate. The algorithm of the peak extraction and the address matching also bring an efficient working mode into the whole scheme. To verify the performance of this system, we devise a series of experiments for distance and velocity, respectively. The data processing rate of the distance is 425 Hz and that of the corresponding average velocity is 0.425 Hz, which is flexible for different measuring conditions. The experimental results show that the difference can be well within 252.8 µm at 5 m range and 284.9 µm/s over 0.5 m/s.

High Temporal Resolution Pyrometry and Velocimetry Based on Acoustic Frequency Division Multiplexing

Real-time and accurate flue gas temperature and velocity measurement is crucial for the safety, efficiency, and low emission of a power plant operation. This article describes a new technique for measuring flue gas temperature and velocity based on acoustic frequency division multiplexing (FDM) in a simultaneous way. The FDM method provides a technique that allows the simultaneous utilization of multiple acoustic signals that leads to a greatly reduced measurement cycle time required; therefore, the measurement system’s temporal resolution is significantly improved. With this new FDM method, the composite signal formed of two channels’ is decomposed by using a Butterworth filter for the extraction of the amplitude and phase information of signals passing each of the individual channels. From the derived frequency signals, the time of flight (TOF) on each acoustic path can be obtained. Demonstrated through both a theoretical analysis and experimental results, by applying the new technique, the measurement period can be reduced to 0.083 times (or say less than 10%) of that by using a traditional method. At the same time, the experimental results indicate that the new technique also improves the accuracy of the measurements. The sensitivity of the FDM method is 3.3, and 2.6 times higher than that of the HWA and traditional methods for velocity, and 1.6 and 1.4 times higher for temperature measurement. Moreover, its optimal robustness and precision are verified by several combined experiments with and without wind with background noise.

A Lubricating Oil Condition Monitoring System Based on Wear Particle Kinematic Analysis in Microfluid for Intelligent Aeroengine.

Lubricating oil monitoring technology is a commonly used method in aeroengine condition monitoring, which includes particle counting technology, as well as spectral and ferrography technology in offline monitoring. However, these technologies only analyze the characteristics of wear particles and rely on physical and chemical analysis techniques to monitor the oil quality. In order to further advance offline monitoring technology, this paper explores the potential role of differences in wear particle kinematic characteristics in recognizing changes in wear particle diameter and oil viscosity. Firstly, a kinematic force analysis of the wear particles in the microfluid was carried out. Accordingly, a microfluidic channel conducive to observing the movement characteristics of particles was designed. Then, the wear particle kinematic analysis system (WKAS) was designed and fabricated. Secondly, a real-time tracking velocity measurement algorithm was developed by using the Gaussian mixture model (GMM) and the blob-tracking algorithm. Lastly, the WKAS was applied to a pin–disc tester, and the experimental results show that there is a corresponding relationship between the velocity of the particles and their diameter and the oil viscosity. Therefore, WKAS provides a new research idea for intelligent aeroengine lubricating oil monitoring technology. Future work is needed to establish a quantitative relationship between wear particle velocity and particle diameter, density, and oil viscosity.

Cover Picture: Real‐Time Plume Velocity Measurement of Solid Propellant Rocket Motors Using TDLAS Technique (Prop., Explos., Pyrotech. 4/2021)

The cover picture is based on the Full Paper Real-Time Plume Velocity Measurement of Solid Propellant Rocket Motors Using TDLAS Technique by Anchen Song et al., https://doi.org/10.1002/prep.202000091. The Full Paper can be found on page 636 ff.

Single Output and Algebraic Modal Parameters Identification of a Wind Turbine Blade: Experimental Results

This paper describes the evaluation of a single output, online, and time domain modal parameters identification technique based on differential algebra and operational calculus. In addition, an analysis of the frequency response function (FRF) of the system is conducted in a specific set up, emulating its nominal or operational conditions to determine the influence of the non-linearities over the dynamic behavior of the system in those particular magnitudes of deformations; thus, this influence is quantified by a numerical index. This methodology is applied to a wind turbine blade submitted to wind tunnel experiments. The natural frequencies and modal damping ratios of six bending modes associated with the blade are estimated using real-time velocity measurements from one single point of the blade. A comparison with the usual impact hammer modal testing is performed to evaluate and establish the proposed approach’s main contributions. The developed modal parameter identification algorithms are implemented to run into a standard personal computer (PC) where the data acquisition system’s measurements are conditioned and processed. The results show the performance and the fast parametric estimation of the proposed algebraic identification approach.

Micro-failure process and failure mechanism of brittle rock under uniaxial compression using continuous real-time wave velocity measurement

In this study, the micro-failure process and failure mechanism of a typical brittle rock under uniaxial compression are investigated via continuous real-time measurement of wave velocities. The experimental results indicate that the evolutions of wave velocities became progressively anisotropic under uniaxial loading due to the direction-dependent development of micro-damage. A wave velocity model considering the inner anisotropic crack evolution is proposed to accurately describe the variations of wave velocities during uniaxial compression testing. Based on which, the effective elastic parameters are inferred by a transverse isotropic constitutive model, and the evolutions of the crack density are inversed using a self-consistent damage model. It is found that the propagation of axial cracks dominates the failure process of brittle rock under uniaxial loading and oblique shear cracks develop with the appearance of macrocrack.

Modulation of anisotropic magnetoresistance by anomalous hall signal and its application to real-time domain wall velocity measurement

We present here a way to modulate the anisotropic magnetoresistance (AMR) by anomalous Hall signal and thus measure the domain wall (DW) motion velocity at near-coercivity. We study the magnetization relaxation at the constant field in the longitudinal (Rxx) Hall geometry. We observed asymmetric Rxx peaks that appear at the DW pinning fields. This unusual magnetoresistance behavior is explained by considering the AMR modulation by the anomalous Hall voltage. In the proposed method, using the magnetization relaxation, the real-time DW velocity measurement is much easier in comparison to the other microscopy methods. Moreover, the additional signal from anomalous Hall voltage makes this technique simpler and sensitive for DW velocity measurements, which can be useful for various spintronic sensing applications.

Comparison of GPS Velocity Obtained Using Three Different Estimation Models

This study analyses the GPS velocity estimation performances of three different estimation models, namely, the time-differenced carrier phase velocity estimation (TDCPVE), Doppler observation velocity estimation (DopplerVE), and precise point positioning velocity estimation (PPPVE). Static and vehicle kinematic experiments are conducted for validation. Under simulated kinematic conditions using static data, the accuracy of the DopplerVE is the worst, and the precision of the velocity by the PPPVE is the same as with the TDCPVE. Under kinematic conditions, the accuracies of the three methods are related to the motion state of the mobile carrier (such as its acceleration and turning). When the sampling interval is 1 s, the TDCPVE can obtain precise velocity using a single-frequency stand-alone GPS receiver; the TDCPVE and DopplerVE can obtain accuracies of the same order of magnitude with broadcast and precise ephemerides, and can be used for real-time velocity measurement; the PPPVE can obtain not only an accurate position, but also an accurate velocity.

Real-Time and Long-Distance Measurement of Displacement Based on Optoelectronic Oscillator

A frequency-encoded real-time and long-distance displacement measurement method based on two cross-referencing optoelectronic oscillators (OEOs) is proposed and experimentally demonstrated. In the system, one OEO is used for reference, and the other is used for measurement. The initial distance is evaluated by the oscillation frequency and free spectral range of the OEO for reference. The small displacement is calculated by using the frequency of the intermediate frequency (IF) signal generated by mixing the two OEOs. The two OEOs with the same characters are placed in the same environment. This protects the displacement measurement from the influence of the variation of ambient temperature. A high measurement sensitivity, which improves the precision of the displacement measurement, is also implemented due to the accumulative magnification effect at high-order resonant frequency modes. In addition, the low frequency of the IF signal, which is far smaller than the oscillation frequency of the two OEOs, allows a cost-effective and real-time measurement by a frequency counter. The proposed displacement measurement method is demonstrated experimentally. When the sampling time is 1 ms, displacement measurement errors less than ±3.71 and $\pm 11.14~\mu \text{m}$ are realized at emulated distances of around 800m and 6 km, respectively. The real-time velocity and acceleration measurements are also implemented owing to the introduction of a time signal in the measurement process.

小波变换实现的光电编码器精确实时测速

小波变换实现的光电编码器精确实时测速

Initial operation of the NSTX-Upgrade real-time velocity diagnostic

A real-time velocity (RTV) diagnostic based on active charge-exchange recombination spectroscopy is now operational on the National Spherical Torus Experiment-Upgrade (NSTX-U) spherical torus (Menard et al 2012 Nucl. Fusion 52 083015). The system has been designed to supply plasma velocity data in real time to the NSTX-U plasma control system, as required for the implementation of toroidal rotation control. Measurements are available from four radii at a maximum sampling frequency of 5 kHz. Post-discharge analysis of RTV data provides additional information on ion temperature, toroidal velocity and density of carbon impurities. Examples of physics studies enabled by RTV measurements from initial operations of NSTX-U are discussed.

Trigger Control Research of Electromagnetic Coil Launcher Based on Real-Time Velocity Measurement

In order to avoid the inherent defect of the traditional position trigger and time trigger, reduce launch error accumulation, and improve the launch efficiency of the electromagnetic coil launcher, a new trigger control method based on real-time velocity measurement is provided in this paper. By the simulation of the launcher whose structural parameters are given, the optimal trigger time corresponding to the different initial velocity could be achieved and preset to the host computer. First, the initial velocity of each stage is measured in real time, and a new time reference is set. Second, the measured data are matched with the preset data, and then the final control time of trigger can be fixed by the interpolation method. Finally, the validity of the method is verified by the experiment.

INVESTINGATION DOWNWARD WIND PRESSURE ON A SMALL QUADROTOR HELICOPTER

Abstract. Small rotary-wing UAVs are susceptible to gusts and other environmental disturbances that affect inflow at their rotors. Inflow variations cause unexpected aerodynamic forces through changes in thrust conditions and unmodeled blade-flapping dynamics. This pa­per introduces an onboard, pressure-based flow measurement system developed for a small quadrotor helicopter. The probe-based instrumentation package provides spatially dis­tributed airspeed measurements along each of the aircraft-fixed axes. Lateral and vertical windspeed estimates enable the development of disturbance-tolerant flight control strate­gies. The focus of this paper is vertical flow disturbances such as those caused by the downwash of a second vehicle. Real-time velocity measurements are incorporated into a recursive Bayesian estimator to localize a nearby rotorcraft using its downwash. A path planner developed for proximity flight is demonstrated through indoor flight testing with multiple vehicles to safely guide an instrumented quadrotor towards a goal point while avoiding another quadrotor.

Frequency-agile dual-frequency lidar for integrated coherent radar-lidar architectures.

We propose a novel architecture for implementing a dual-frequency lidar (DFL) exploiting differential Doppler shift measurement. The two frequency tones, needed for target velocity measurements, are selected from the spectrum of a mode-locked laser operating in the C-band. The tones' separation is easily controlled by using a programmable wavelength selective switch, thus allowing for a dynamic trade-off among robustness to atmospheric turbulence and sensitivity. Speed measurements for different tone separations equal to 10, 40, 80, and 160GHz are demonstrated, proving the system's capability of working in different configurations. Thanks to the acquisition system based on an analog-to-digital converter and digital-signal processing, real-time velocity measurements are demonstrated. The MLL-based proposed architecture enables the integration of the DFL with a photonic-based radar that exploits the same laser for generating and receiving radio-frequency signal with high performance, thus allowing for simultaneous or complementary target observations by exploiting the advantages of both radar and lidar.

Real-time velocity measurement to linear motion of a rigid object with monocular image sequence analyses

This paper presents a methodology and all procedures used to validate it, which were executed in a physics laboratory under controlled and known conditions. The validation was based on the analyses of registered data in an image sequence and the measurements acquired by high precision sensors. This methodology intended to measure the velocity of a rigid object in linear motion with the use of an image sequence acquired by commercial digital video camera. The proposed methodology does not need a stereo pair of images to calculate the object position in the 3D space: it needs only images sequence acquired for one, only one, angle view (monocular vision). To do so, these objects need to be detected while in movement, which is conducted by the application of a segmentation technique based on the temporal average values of each pixel registered in N consecutive image frames. After detecting and framing these objects, specific points belonging to the object (pixels), on the plane image (2D coordinates or space image), are automatically chosen, which are then transformed into corresponding points in the space object (3D coordinates) by the application of collinearity equations or rational functions (proposed in this work). After obtaining the coordinates of these points in the space object that are registered in the sequence of images, the distance, in meters, covered by the object in a particular time interval may be measured and, consequently, its velocity can be calculated. The system is low cost, use only a computer (architecture Intel I3), and a webcam used to acquire the images (640 × 480, 30 fps). The complexity of the algorithm is linear, fact that allows the system to operate in real time. The results of the analyses are discussed and the advantages and disadvantages of the method are presented.