A novel detection method for warhead fragment targets in optical images under dynamic strong interference environments

A measurement system for the scattering characteristics of warhead fragments based on high-speed imaging systems offers advantages such as simple deployment,flexible maneuverability,and high spatiotemporal resolution,enabling the acquisition of full-process data of the fragment scattering process.However,mismatches between camera frame rates and target velocities can lead to long motion blur tails of high-speed fragment targets,resulting in low signal-to-noise ratios and rendering conventional detection algorithms ineffective in dynamic strong interference testing environments.In this study,we propose a detection framework centered on dynamic strong interference disturbance signal separation and suppression.We introduce a mixture Gaussian model constrained under a joint spatialtemporal-transform domain Dirichlet process,combined with total variation regularization to achieve disturbance signal suppression.Experimental results demonstrate that the proposed disturbance suppression method can be integrated with certain conventional motion target detection tasks,enabling adaptation to real-world data to a certain extent.Moreover,we provide a specific implementation of this process,which achieves a detection rate close to 100%with an approximate 0%false alarm rate in multiple sets of real target field test data.This research effectively advances the development of the field of damage parameter testing.

Piecewise Acoustic Source Imaging with Unknown Speed of Sound Using a Level-Set Method

We investigate the following inverse problem:starting from the acoustic wave equation,reconstruct a piecewise constant passive acoustic source from a single boundary temporal measurement without knowing the speed of sound.When the amplitudes of the source are known a priori,we prove a unique determination result of the shape and propose a level set algorithm to reconstruct the singularities.When the singularities of the source are known a priori,we show unique determination of the source amplitudes and propose a least-squares fitting algorithm to recover the source amplitudes.The analysis bridges the low-frequency source inversion problem and the inverse problem of gravimetry.The proposed algorithms are validated and quantitatively evaluated with numerical experiments in 2D and 3D.

Criteria for assessing the diagnostic significance of modern methods of imaging gastrointestinal diseases in practical gastroenterology

Imaging methods are frequently used to diagnose gastrointestinal diseases and play a crucial role in verifying clinical diagnoses among all diagnostic algorithms.However,these methods have limitations,challenges,benefits,and advantages.Addressing these limitations requires the application of objective criteria to assess the effectiveness of each diagnostic method.The diagnostic process is dynamic and requires a consistent algorithm,progressing from clinical subjective data,such as patient history(anamnesis),and objective findings to diagnostics ex juvantibus.Caution must be exercised when interpreting diagnostic results,and there is an urgent need for better diagnostic tests.In the absence of such tests,preliminary criteria and a diagnosis ex juvantibus must be relied upon.Diagnostic imaging methods are critical stages in the diagnostic workflow,with sensitivity,specificity,and accuracy serving as the primary criteria for evaluating clinical,laboratory,and instrumental symptoms.A comprehensive evaluation of all available diagnostic data guarantees an accurate diagnosis.The“gold standard”for diagnosis is typically established through either the results of a pathological autopsy or a lifetime diagnosis resulting from a thorough examination using all diagnostic methods.

Particle velocity measurement of binary mixtures in the riser of a circulating fluidized bed by the combined use of electrostatic sensing and high-speed imaging

The flow dynamics of binary particle mixtures in the fluidized bed needs to be monitored in order to optimize the related industrial processes.In this paper,electrostatic sensing and high-speed imaging are applied to measure the velocities of polyethylene and sand particles in the binary particle mixtures in fluidization.Experimental studies were conducted on a lab-scale cold circulating fluidized bed.Correlation function between electrostatic signals from upstream and downstream electrodes placed along the riser shows two peaks that represent transit times for the two types of particles.To verify the above results,high-speed imaging was adopted to capture the flow images of particle mixtures.Particle Image Velocimetry and Particle Tracking Velocimetry algorithms were utilized to process the resulted images in order to measure the velocities of polyethylene and sand particles.The reasons for two-peak correlation functions are illustrated based on the frequency spectrums of the mono-solid-phase electrostatic signals and the velocity difference between polyethylene and sand particles.Finally,comparisons on the velocities obtained from electrostatic sensing and high-speed imaging demonstrate the electrostatic sensor can roughly estimate the particle velocity of binary particle mixtures in the near wall region of the circulating fluidized bed.

High-speed hyperspectral imaging enabled by compressed sensing in time domain

Hyperspectral imaging(HSI)is a powerful tool widely used for various scientific and industrial applications due to its ability to provide rich spatiospectral information.However,in exchange for multiplex spectral information,its image acquisition rate is lower than that of conventional imaging,with up to a few colors.In particular,HSI in the infrared region and using nonlinear optical processes is impractically slow because the three-dimensional(3D)data cube must be scanned in a point-by-point manner.In this study,we demonstrate a framework to improve the spectral image acquisition rate of HSI by integrating time-domain HSI and compressed sensing.Specifically,we simulated broadband coherent Raman imaging at a record high frame rate of 25 frames per second(fps)with 100 pixels×100 pixels,which is 10×faster than that of previous work,based on an experimentally feasible sampling scheme utilizing 3D Lissajous scanning.

Clinical issues and challenges in imaging of gastrointestinal diseases:A minireview and our experience

Imaging techniques play a crucial role in the modern era of medicine,particularly in gastroenterology.Nowadays,various non-invasive and invasive imaging modalities are being routinely employed to evaluate different gastrointestinal(GI)diseases.However,many instrumental as well as clinical issues are arising in the area of modern GI imaging.This minireview article aims to briefly overview the clinical issues and challenges encountered in imaging GI diseases while highlighting our experience in the field.We also summarize the advances in clinically available diagnostic methods for evaluating different diseases of the GI tract and demonstrate our experience in the area.In conclusion,almost all imaging techniques used in imaging GI diseases can also raise many challenges that necessitate careful consideration and profound expertise in this field.

A computational method for post-construction settlement of high-speed railway bridge pile foundation considering soil creep effect

Based on reasonable assumptions that simplified the calculational model,a simple and practical method was proposed to calculate the post-construction settlement of high-speed railway bridge pile foundation by using the Mesri creep model to describe the soil characteristics and the Mindlin-Geddes method considering pile diameter to calculate the vertical additional stress of pile bottom.A program named CPPS was designed for this method to calculate the post-construction settlement of a high-speed railway bridge pile foundation.The result indicates that the post-construction settlement in 100 years meets the requirements of the engineering specifications,and in the first two decades,the post-construction settlement is about 80% of its total settlement,while the settlement in the rest eighty years tends to be stable.Compared with the measured settlement after laying railway tracks,the calculational result is closed to that of the measured,and the results are conservative with a high computational accuracy.It is noted that the method can be used to calculate the post-construction settlement for the preliminary design of high-speed railway bridge pile foundation.

Analysis of the Temperature Characteristics of High-speed Train Bearings Based on a Dynamics Model and Thermal Network Method

High-speed trains often use temperature sensors to monitor the motion state of bearings.However,the temperature of bearings can be affected by factors such as weather and faults.Therefore,it is necessary to analyze in detail the relationship between the bearing temperature and influencing factors.In this study,a dynamics model of the axle box bearing of high-speed trains is established.The model can obtain the contact force between the rollers and raceway and its change law when the bearing contains outer-ring,inner-ring,and rolling-element faults.Based on the model,a thermal network method is introduced to study the temperature field distribution of the axle box bearings of high-speed trains.In this model,the heat generation,conduction,and dispersion of the isothermal nodes can be solved.The results show that the temperature of the contact point between the outer-ring raceway and rolling-elements is the highest.The relationships between the node temperature and the speed,fault type,and fault size are analyzed,finding that the higher the speed,the higher the node temperature.Under different fault types,the node temperature first increases and then decreases as the fault size increases.The effectiveness of the model is demonstrated using the actual temperature data of a high-speed train.This study proposes a thermal network model that can predict the temperature of each component of the bearings on a high-speed train under various speed and fault conditions.

Studyon Evaluation Methods for Lateral Stability of High-Speed Trains

Taking a high-speed train in China as an example,using computer simulation technology and comparing with the test data,the three current methods including linear stability analysis method,nonlinear stability analysis method and the field testing criterion are studied to evaluate stability of high-speed trains.A new stability evaluation method is proposed which can be used to evaluate lateral stability of high-speed vehicle based on the codes of UIC 515and UIC 518.From the viewpoint of taking the most unfavorable track conditions into account and improving the safety margin,the new method uses the root mean square of bogie lateral acceleration as a criterion to evaluate the lateral stability of high-speed trains.Numerical example shows that the proposed method not only considers the forced vibration caused by track irregularities in the actual practice,but also takes the instability self-excited vibration into account,so it can realize early warning of bogie slight unstable oscillation,meanwhile the method itself does not involve complex algorithms which has the possibility of engineering applications.

Autofocus technique for ISAR imaging of uniformly rotating targets based on the ExCoV method

The inverse synthetic aperture radar (ISAR) imaging can be converted into a sparse reconstruction problem and solved by the l1norm minimization algorithm. The basis matrix in sparse ISAR imaging is usually characterized by the unknown rotation rate of a moving target, thus the rotation rate and the sparse signal should be jointly estimated. Especially due to the imperfect coarse motion compensation, we consider the phase error correction problem in the context of the sparse signal reconstruction. To address this issue, we propose an iterative reweighted method, which jointly estimates the rotation rate, corrects the phase error and reconstructs a high resolution ISAR image. The proposed method gives a gradual and interweaved iterative process to refine the unknown parameters to achieve the best sparse representation for the ISAR signals. Particularly, in ISAR image reconstruction, the l1norm minimization algorithm is sensitive to user parameters. Setting these user parameters are not trivial and the reconstruction performance depends significantly on their choices. Then, we consider an expansion-compression variance-component (ExCoV) based method, which is automatic and demands no prior knowledge about signal-sparsity or measurement-noise levels. Both numerical and electromagnetic data experiments are implemented to show the effectiveness of the proposed method. It is shown that the proposed method can estimate the rotation rate and correct the phase errors simultaneously, and its superior performance is proved in terms of high resolution ISAR image. © 2017 Beijing Institute of Aerospace Information.

AN ANALYSIS METHOD FOR HIGH-SPEED CIRCUIT SYSTEMS

A new method for analyzing high-speed circuit systems is presented. The method adds transmission line end currents to the circuit variables of the classical modified nodal approach. Then the matrix equation describing high-speed circuit system can be formulated directly and analyzed conveniently for its normative form. A time-domain analysis method for transmission lines is also introduced. The two methods are combined together to efficiently analyze high-speed circuit systems having general transmission lines. Numerical experiment is presented and the results are compared with that calculated by Hspice.

Efficient hybrid method for time reversal superresolution imaging

An efficient hybrid time reversal（TR） imaging method based on signal subspace and noise subspace is proposed for electromagnetic superresolution detecting and imaging. First, the locations of targets are estimated by the transmitting-mode decomposition of the TR operator（DORT） method employing the signal subspace. Then, the TR multiple signal classification（TR-MUSIC）method employing the noise subspace is used in the estimated target area to get the superresolution imaging of targets. Two examples with homogeneous and inhomogeneous background mediums are considered, respectively. The results show that the proposed hybrid method has advantages in CPU time and memory cost because of the combination of rough and fine imaging.

Lossless Compression Method for the Magnetic and Helioseismic Imager(MHI)Payload

The Solar Polar-orbit Observatory(SPO),proposed by Chinese scientists,is designed to observe the solar polar regions in an unprecedented way with a spacecraft traveling in a large solar inclination angle and a small ellipticity.However,one of the most significant challenges lies in ultra-long-distance data transmission,particularly for the Magnetic and Helioseismic Imager(MHI),which is the most important payload and generates the largest volume of data in SPO.In this paper,we propose a tailored lossless data compression method based on the measurement mode and characteristics of MHI data.The background out of the solar disk is removed to decrease the pixel number of an image under compression.Multiple predictive coding methods are combined to eliminate the redundancy utilizing the correlation(space,spectrum,and polarization)in data set,improving the compression ratio.Experimental results demonstrate that our method achieves an average compression ratio of 3.67.The compression time is also less than the general observation period.The method exhibits strong feasibility and can be easily adapted to MHI.

Advancements and challenges in gastrointestinal imaging

A recent review by Gulinac et al,provides an in-depth analysis of current clinical issues and challenges in gastrointestinal imaging.This editorial highlights the advancements in imaging techniques,including the integration of artificial intelligence and functional imaging modalities,and discusses the ongoing relevance of traditional nuclear medicine tests.The future of gastrointestinal imaging looks promising,with continuous improvements in resolution,enhanced ability to analyze color and texture beyond visual diagnosis,faster image processing,and the application of molecular imaging and nanoparticles expected to enhance diagnostic accuracy and clinical outcomes.

TEST METHOD OF HIGH-SPEED ON-OFF VALVE DYNAMIC CHARACTERISTICS

According to the valve port features of high speed on-off valve and its actions, the valve port can be simplified into an a-type half bridge construction. A method that tests the dynamic characteristics of the high speed on-off valve by the output pressure signal of the a-type half bridge is proposed. Having analyzed the factors related to the dynamic characteristics of an a-type half bridge, a rule for designing the outlet chamber＇s volume is worked out. According to the rule, a test stand is built to test the self-developed high-speed on-off valve. From the test results, it can be seen that with the outlet chamber＇s volume controlled by the rule the rise time of the pressure signals driven by signals with different frequencies changes very little. The test results conform to the simulation results, which nroves the correctness of the method.

A Visual Indoor Localization Method Based on Efficient Image Retrieval

The task of indoor visual localization, utilizing camera visual information for user pose calculation, was a core component of Augmented Reality (AR) and Simultaneous Localization and Mapping (SLAM). Existing indoor localization technologies generally used scene-specific 3D representations or were trained on specific datasets, making it challenging to balance accuracy and cost when applied to new scenes. Addressing this issue, this paper proposed a universal indoor visual localization method based on efficient image retrieval. Initially, a Multi-Layer Perceptron (MLP) was employed to aggregate features from intermediate layers of a convolutional neural network, obtaining a global representation of the image. This approach ensured accurate and rapid retrieval of reference images. Subsequently, a new mechanism using Random Sample Consensus (RANSAC) was designed to resolve relative pose ambiguity caused by the essential matrix decomposition based on the five-point method. Finally, the absolute pose of the queried user image was computed, thereby achieving indoor user pose estimation. The proposed indoor localization method was characterized by its simplicity, flexibility, and excellent cross-scene generalization. Experimental results demonstrated a positioning error of 0.09 m and 2.14° on the 7Scenes dataset, and 0.15 m and 6.37° on the 12Scenes dataset. These results convincingly illustrated the outstanding performance of the proposed indoor localization method.

Distance-Coefficient-Based Imaging Accuracy Improving Method Based on the Lamb Wave

An imaging accuracy improving method is established, within which a distance coefficient including location information between sparse array configuration and the location of defect is proposed to select higher signal- to-noise ratio data from all experimental data and then to use these selected data for elliptical imaging. Tile relationships among imaging accuracy, distance coefficient and residual direct wave are investigated, and then the residual direct wave is introduced to make the engineering application more convenient. The effectiveness of the proposed method is evaluated experimentally by sparse transducer array of a rectangle, and the results reveal that selecting experimental data of smaller distance coefficient can effectively improve imaging accuracy. Moreover, the direct wave difference increases with the decrease of the distance coefficient, which implies that the imaging accuracy can be effectively improved by using the experimental data of the larger direct wave difference.

High-contrast imaging based on wavefront shaping to improve low signal-to-noise ratio photoacoustic signals using superpixel method

Photoacoustic(PA) imaging has drawn tremendous research interest for various applications in biomedicine and experienced exponential growth over the past decade. Since the scattering effect of biological tissue on ultrasound is two-to three-orders magnitude weaker than that of light, photoacoustic imaging can effectively improve the imaging depth.However, as the depth of imaging further increases, the incident light is seriously affected by scattering that the generated photoacoustic signal is very weak and the signal-to-noise ratio(SNR) is quite low. Low SNR signals can reduce imaging quality and even cause imaging failure. In this paper, we proposed a new wavefront shaping and imaging method of low SNR photoacoustic signal using digital micromirror device(DMD) based superpixel method. We combined the superpixel method with DMD to modulate the phase and amplitude of the incident light, and the genetic algorithm(GA) was used as the wavefront shaping algorithm. The enhancement of the photoacoustic signal reached 10.46. Then we performed scanning imaging by moving the absorber with the translation stage. A clear image with contrast of 8.57 was obtained while imaging with original photoacoustic signals could not be achieved. The proposed method opens new perspectives for imaging with weak photoacoustic signals.

AN AUTOMATIC SEGMENTATION METHOD FOR FAST IMAGING IN PET

A new segmentation method has been developed for PET fast imaging. The technique automatically segments the transmission images into different anatomical regions, it efficiently reduced the PET transmission scan time. The result shows that this method gives only 3 min-scan time which is perfect for attenuation correction of the PET images instead of the original 15-30 min-scan time. This approach has been successfully tested both on phantom and clinical data.

SAR imaging method for sea scene target based on improved phase retrieval algorithm

Due to the influence of the platform random motion and electromagnetic propagation in turbulent media, the synthetic aperture radar (SAR) high resolution imaging for the sea scenes where there are large amounts of water returns with some target (land) returns is very difficult. To solve this problem, a SAR imaging method based on the improved phase retrieval (PR) algorithm is proposed. First, a filter is added to the conventional PR algorithm which can reduce the influence of water returns on the reconstruction of the targets and improve the reconstruction result of the targets. Then, the corrupted phase of the Fourier transform of the intensity image in the iterative process, which can improve the stability of the iterative algorithm, is used to reduce the recovery errors, and a better recovery performance is achieved. Finally, several experiments are performed to demonstrate the advantages of the proposed method. © 2016 Beijing Institute of Aerospace Information.