Wave Detection Technology Research Articles

Off-Axis Color Characteristics of Binary Neutron Star Merger Events: Applications for Space Multi-Band Variable Object Monitor and James Webb Space Telescope

With advancements in gravitational wave detection technology, an increasing number of binary neutron star (BNS) merger events are expected to be detected. Due to the narrow opening angle of jet cores, many BNS merger events occur off-axis, resulting in numerous gamma-ray bursts (GRBs) going undetected. Models suggest that kilonovae, which can be observed off-axis, offer more opportunities to be detected in the optical/near-infrared band as electromagnetic counterparts of BNS merger events. In this study, we calculate kilonova emission using a three-dimensional semi-analytical code and model the GRB afterglow emission with the open-source Python package afterglowpy at various inclination angles. Our results show that it is possible to identify the kilonova signal from the observed color evolution of BNS merger events. We also deduce the optimal observing window for SVOM/VT and JWST/NIRCam, which depends on the viewing angle, jet opening angle, and circumburst density. These parameters can be cross-checked with the multi-band afterglow fitting. We suggest that kilonovae are more likely to be identified at larger inclination angles, which can also help determine whether the observed signals without accompanying GRBs originate from BNS mergers.

Ultrasonic guided wave-based probabilistic diagnostic imaging method with Single-Path-Scattering sparse reconstruction for Multi-Damage detection in composite structures

Plate-like carbon fiber composite structures are essential for equipment such as spacecraft and rail vehicles. These structures are exposed to long-term cyclic loads and harsh environmental conditions, leading to damage of unknown location and quantity. Ultrasonic guided wave (UGW) detection technology shows promise for evaluating the structural performance of composite structures due to its advantages of high precision, high speed, and real-time capabilities. However, multi-damage scattering sources interfere with and superimpose the received signals when multiple damages coincide. This interference can lead to artifacts in probability imaging methods that rely on features such as amplitude and time of flight (TOF). This paper proposes a single-path-scattering sparse reconstruction-based probabilistic diagnostic imaging (SSR-PDI) method. Firstly, a Lamb dictionary with time shift is constructed. Each actuator-receiver path is treated as a target signal, enabling the approximate separation and extraction of multiple scattering waves from different damages. It mitigates the “curse of dimensionality” associated with the sparse reconstruction (SR) method. Secondly, a new ring-shaped damage probability distribution is proposed based on the sparse representation matrix’s time mapping and amplitude weighting. The experimental results demonstrate that the SSR-PDI method effectively mitigates issues related to multi-damage detection, specifically false negatives/positives and localization errors arising from the superposition of scattering sources.

Optimised design of aviation stainless steel sheet SH guided wave focusing PPM EMAT

ABSTRACT Electromagnetic Acoustic Transducer (EMAT) is an ultrasonic testing technique that generates sound in the part inspected instead of the transducer. Electromagnetic ultrasonic guided wave detection technology has problems such as low energy conversion efficiency and the great influence of environmental noise, resulting in low echo signal amplitude. When the two rows of permanent magnets are arranged non-parallel, the sound beam will be focused at the intersection point of the axes of the two rows of permanent magnets. This article uses this rule to optimise the design parameters of PPM EMAT. Distance amplitude curve (DAC) is a method of compensating. However, large-scale detection requires a flat DAC curve. In addition, the increase in the angle and length of the permanent magnets and the number of pairs of permanent magnets will improve the intensity of the defect wave indication intensity. However, the increase in the angle of the permanent magnets will increase the signal attenuation. After simulation and experiments, when the angle, length and number of permanent magnet pairs are 4°, 25 mm and 8 pairs, the corresponding EMAT has the optimal axis radiation sound field and a smoother DAC, which is more suitable for stainless steel sheets, long-distance rapid guided wave detection.

Novel baseline-free ultrasonic Lamb wave defect location method based on path amplitude matching

Ultrasonic Lamb wave detection technology constitutes a non-destructive evaluation approach extensively employed for the identification of flaws within plate-like structures. The conventional method for detecting and localizing defects in isotropic plate-like structures using ultrasonic Lamb waves relies on baseline signal data. However, the reliability of baseline data as a reference value is diminished due to varying working conditions of the structure. Therefore, to overcome the influence of mismatched baseline data, this paper proposes a novel non-baseline Lamb wave defect detection and localization method. Through simulation and experiment studies, it is discovered that defects at different positions have varied impacts on the amplitude of direct wave-packets under the same propagation path. By eliminating differences in the piezoelectric excitation characteristics of the sensing array (normalized through boundary reflect wave), the direct wave amplitude of multiple sensor pairs in the circular array can be compared and ranked. The paths closest to the location of the damage can be identified, enabling to obtain the defect location information. In this paper, the feasibility and effectiveness of this method has been verified by simulation and practical experiments. The experimental data and imaging results obtained over a four-month period demonstrate that, compared to the traditional baseline localization method, the baseline-free method proposed in this study exhibits a greater ability to resist interference caused by changes in environmental temperature. By increasing the number of sensors from 16 to 32, the positioning accuracy can be significantly improved, reducing the positioning deviation from 13 mm to 0.42 mm. This new non-baseline method based on path amplitude matching demonstrates enhanced practicality within the realm of engineering. Notably, this method holds the potential to be synergistically incorporated and applied in conjunction with various other measurement techniques.

Research on the Innovation and Development of Gravitational Wave Detection Technology

According to Einstein’s general theory of relativity, gravity is described as the curvature of space-time caused by gravitational sources, and to prove the existence of gravitational waves, many scientific research institutes around the world have begun to build equipment to try to detect gravitational waves in the vast background signals of the universe. At present, gravitational waves have been detected by many scientific research institutions and scientists. Now, the detection of gravitational waves has shifted to the direction of high precision and accuracy. This paper starts with the laser interferometer, the most basic instrument for gravitational wave detection. It expounds on the latest development progress and key technologies of gravitational wave detection in the current physical world, including noise suppression and gravitational wave detection spacecraft projects. In terms of laser interferometers, this paper describes their principle and key technologies and puts forward the difficult problems that still need to be tackled and studied. In terms of noise suppression, this paper describes the noise and interference that may be generated and how to suppress the noise to avoid interfering with the accuracy of the experiment. It also points out the shortcomings of current noise suppression techniques. For gravitational wave detection spacecraft projects, this paper first focuses on several key projects in the world, then describes the technologies and shortcomings of spacecraft, and puts forward the direction of improvement and in-depth research on these technologies. This paper aims to summarize the key technologies of gravitational wave detection in the world today and point out the direction of its future development.

Quantitative Detection of Pipeline Cracks Based on Ultrasonic Guided Waves and Convolutional Neural Network.

In this study, a quantitative detection method of pipeline cracks based on a one-dimensional convolutional neural network (1D-CNN) was developed using the time-domain signal of ultrasonic guided waves and the crack size of the pipeline as the input and output, respectively. Pipeline ultrasonic guided wave detection signals under different crack defect conditions were obtained via numerical simulations and experiments, and these signals were input as features into a multi-layer perceptron and one-dimensional convolutional neural network (1D-CNN) for training. The results revealed that the 1D-CNN performed better in the quantitative analysis of pipeline crack defects, with an error of less than 2% in the simulated and experimental data, and it could effectively evaluate the size of crack defects from the echo signals under different frequency excitations. Thus, by combining the ultrasonic guided wave detection technology and CNN, a quantitative analysis of pipeline crack defects can be effectively realized.

Research on pulse infrared thermal wave detection technology for honeycomb sandwich structure defects

Through the method of numerical simulation, the detection rules of different defect characteristics and the detection effect of detection process parameters on different defects were explored. The optimal detection process parameters for GFRP/NOMEX honeycomb sandwich structure specimens with delaminating, debonding, water accumulation, and glue plugging defects were obtained. Experimental research was carried out to verify its detection effect for actual tests. The result is that the technology under this parameter can get better defect detection effect.

Application of gravitational wave detection technology in astronomical observations

Gravitational waves are waves that propagate through space and time due to the interaction of gravity, representing a completely new physical phenomenon. This article reviews the background and issues of gravitational wave detection, with a focus on the progress of interdisciplinary research. It was not until 2015 that researchers successfully detected gravitational waves for the first time, capturing gravitational wave signals from the merger of two black holes using laser interferometry technology. This breakthrough confirms the predictions of Einstein's general relativity and opens a new chapter in the study of gravitational waves. Gravitational wave detection technology not only provides a new way to observe the universe, but also provides clues for studying the mysteries of the universe such as black holes, dark matter, and dark energy. Gravity wave detection technology also has potential communication application prospects, such as quantum gravity communication and long-distance communication, which brings new possibilities for future communication technology. In the future, there expects to be more success of gravitational wave detection and the continuous contribution of gravitational wave research in unlocking the mysteries of the universe and advancing the forefront of science.

Application of Long-Range Cross-Hole Acoustic Wave Detection Technology in Geotechnical Engineering Detection: Case Studies of Tunnel-Surrounding Rock, Foundation and Subgrade

The adverse geological conditions of soil cave, karst cave and goaf in deep foundation directly affect the safety and economy of geotechnical engineering construction. It is a difficult problem in geotechnical engineering detection to detect the distribution of bad geological conditions efficiently and accurately. Aiming at the problems of short penetrating distance and low resolution of cross-hole acoustic wave detection in rock-soil mass, based on the characteristics of acoustic wave propagation in rock and soil layers and comprehensively utilizing the spark source and data acquisition device, a long-distance cross-hole acoustic wave detection technology is proposed. According to the indoor concrete model test and field tests of geotechnical engineering, the applicability of the long-distance cross-hole acoustic wave detection technology in the detection of geotechnical structure and adverse geological phenomena under complex geological conditions is verified. The results show that acoustic wave CT imaging can accurately detect the cavities in the indoor concrete model test. In addition, the field tests of the grouting effect of tunnel-surrounding rock, high-rise building foundation and subgrade further verify the rapidity, accuracy and intuitiveness of the long-distance cross-hole acoustic wave detection technology. This work provides a reference for eliminating the potential safety problems caused by adverse geological conditions and similar geotechnical engineering investigation.

Gravitational Wave-Signal Recognition Model Based on Fourier Transform and Convolutional Neural Network

The recent detection of gravitational waves is a remarkable milestone in the history of astrophysics. With the further development of gravitational wave detection technology, traditional filter-matching methods no longer meet the needs of signal recognition. Thus, it is imperative that we develop new methods. In this study, we apply a gravitational wave signal recognition model based on Fourier transformation and a convolutional neural network (CNN). The gravitational wave time-domain signal is transformed into a 2D frequency-domain signal graph for feature recognition using a CNN model. Experimental results reveal that the frequency-domain signal graph provides a better feature description of the gravitational wave signal than that provided by the time-domain signal. Our method takes advantage of the CNN's convolution computation to improve the accuracy of signal recognition. The impact of the training set size and image filtering on the performance of the developed model is also evaluated. Additionally, the Resnet101 model, developed on the Baidu EasyDL platform, is adopted as a comparative model. Our average recognition accuracy performs approximately 4% better than the Resnet101 model. Based on the excellent performance of convolutional neural network in the field of image recognition, this paper studies the characteristics of gravitational wave signals and obtains a more appropriate recognition model after training and tuning, in order to achieve the purpose of automatic recognition of whether the signal data contain real gravitational wave signals.

Reasearch on scattering characteristics of THz waves from a parabolic plasma-coated 2D metallic cylinder

Terahertz wave detection technology is regarded as an important research direction for solving plasma stealth. In this paper, we mainly study the penetration ability of terahertz waves into the plasma to apply terahertz waves in anti-stealth technology. We are going to build a two-dimensional metallic cylinder of unmagnetized plasma coverage, using Runge–Kutta Exponential Time Differencing-Finite Difference Time Domain method to calculate radar scattering cross-section. The effect of the plasma thickness, collision frequency and other parameters on the scattering characteristics is discussed, the numerical results indicate that terahertz wave has a strong penetration ability for plasma, which can be used to improve radar detection technology to deal with plasma stealth technology.

Detection of butt weld of laser-MIG hybrid welding of thin-walled profile for high-speed train

PurposeThis study aims to solve the problem of weld quality inspection, for the aluminum alloy profile welding structure of high-speed train body has complex internal shape and thin plate thickness (2–4 mm), the conventional nondestructive testing method of weld quality is difficult to implement.Design/methodology/approachIn order to solve this problem, the ultrasonic creeping wave detection technology was proposed. The impact of the profile structure on the creeping wave detection was studied by designing profile structural test blocks and artificial simulation defect test blocks. The detection technology was used to test the actual welded test blocks, and compared with the results of X-ray test and destructive test (tensile test) to verify the accuracy of the ultrasonic creeping wave test results.FindingsIt is indicated that that X-ray has better effect on the inspection of porosities and incomplete penetration defects. However, due to special detection method and protection, the detection speed is slow, which cannot meet the requirements of field inspection of the welding structure of aluminum alloy thin-walled profile for high-speed train body. It can be used as an auxiliary detection method for a small number of sampling inspection. The ultrasonic creeping wave can be used to detect the incomplete penetration welds with the equivalent of 0.25 mm or more, the results of creeping wave detection correspond well with the actual incomplete penetration defects.Originality/valueThe results show that creeping wave detection results correspond well with the actual non-penetration defects and can be used for welding quality inspection of aluminum alloy thin-wall profile composite welding joints. It is recommended to use the echo amplitude of the 10 mm × 0.2 mm × 0.5 mm notch as the criterion for weld qualification.

R&D of Relay Aging State Monitoring Device Based on Electromagnetic Signal

Relays are the key components in the operation of nuclear power plants. There are many kinds, large quantity and high failure rate of relays in nuclear power plants, which are the difficulties in on-site maintenance and equipment management. There is no effective method and equipment to judge the aging state of relays on site, so only passive maintenance and replacement strategy can be adopted. The device developed in this paper uses space electromagnetic wave detection technology to monitor the aging status of relay on line, which provides a new way for the aging status evaluation and failure diagnosis of relay in service. The preliminary test results also show that the device has the potential to solve the key technology of relay maintenance activities in nuclear power field and realize relay aging management and predictive maintenance.

Analysis of Bioelectrical Impedance Spectrum for Elbow Stiffness Based on Hilbert-Huang Transform.

With the advent of posttraumatic elbow rehabilitation, prevention of elbow stiffness has become a key part of the development of sports medicine. In order to clarify the time point of joint movement after internal fixation to the elbow and to provide a mechanical model for individualized diagnosis. This paper uses electromagnetic wave detection technology to quickly detect the bioelectrical impedance signal of the patient's lesion location, then passes the message to the upper control system for processing, summarizes the improved Hilbert–Huang transform to deep learning, and deep learning algorithms and computer technology are used to mine the bioelectrical impedance signal of the elbow joint. The simulation and human experiment results show that bioelectrical impedance signals can clarify the pathogenesis of elbow joint stiffness and the relationship between rehabilitation treatment time and duration. It has the advantages of low cost, high fitting accuracy, strong robustness, and noninvasiveness.

Label-free detection of living cervical cells based on microfluidic device with terahertz spectroscopy.

Early diagnosis of cervical cancer is essential for a good prognosis. Terahertz wave detection technology is a nondestructive and label-free physical detection technology, which can detect and monitor the cancer cells in real time, especially for patients with deep or inaccessible tumors. In this study, a single-cell-layer microfluidic device was developed. After replacing the optical clearing agent, the characteristics of H8, HeLa and SiHa cell lines in adherent and suspended states were detected. Additionally, the absorption increased with increasing cell density. For the mixed suspension cell samples, principal component analysis-support vector machine method was used to identify benign and malignant cell component. After living cells formaldehyde, changes in cell membrane permeability were evaluated to identify the cell survival status (i.e., dead or living) based on terahertz spectroscopy amplitude differences. Therefore, extending the terahertz spectrum detection to the molecular level can characterize the life essence of cells and tissues.

Research on the analytical development and progress of gravitational wave detection technology

This article demonstrates the basic principle and the recent progress of gravitational wave detection based on information retrieval and literature review. The article describes and illustrates the gravitational wave, including the description of the adopted field equation and its properties. There is also a demonstration of the principle behind the first direct gravitational wave detection. Some other potential ground-based detectors, e.g., KAGRA and space-borne detectors, are also listed and contrasted. Since gravitational waves tend to retain themselves from interacting with matter, which travels from a much earlier time than Electromagnetic waves and should be a vital component to Cosmology studies, the space-borne detectors Taiji and LISA will also interlace with each other to explore deeper space in the 2030s, which would be significant progress in gravitational wave Astronomy. This article employs literature analysis that examines papers that discuss the nature of gravitational waves and their detection. These analyses will shed light on gravitational wave detection development.

Research on Leak Location of Liquid-filled Pipe Based on Frequency Dispersion Characteristics

Due to the material problems and force majeure factors, the leakage will be occurred on the liquid-filled pipe resulting in waste of resources, environmental pollution and even endangering safety. Acoustic wave detection technology is widely used in buried pipeline leak detection, this technology mainly uses the wave (n=0, s=1) in the pipeline acoustic wave to locate the leak. When the leakage acoustic signal propagates along the liquid-filled pipe, the frequency dispersion characteristics can be obtained by wavelet decomposition. And there is a time delay (time difference) value between the leaky acoustic signals collected by the sensors at both ends of the leak. The outputs show that the results obtained by wavelet decomposition are in good agreement with the theoretical calculation results. Based on the obtained dispersion relation, the time delay values at different characteristic frequencies are analyzed by the cross-correlation method, and the leak location accuracy is discussed. This research content provides theoretical support and engineering application guidance for pipe leakage location technology.

Defect Signal Detection of Station Process Pipelines Based on the BP Neural Network

In recent years, leakage, rupture, and perforation accidents in oil and gas pipelines caused by corrosion have increased significantly. Therefore, the online, nondestructive testing of oil and gas pipelines has become essential to maintain their structural integrity. Ultrasonic guided wave detection technology presents advantages, such as high detection efficiency and complete coverage of the pipeline body, which is conducive to popularization and application. This paper considered the natural gas transmission station as the research object, while ultrasonic guided wave technology was used for detection. Ultrasonic guided wave equipment was used to detect the field process pipeline and experimental pipeline, obtaining data samples of the defects and welds. Defects were automatically identified via data processing by combining the characteristic signal method and the BP neural network. The results indicated that the neural network displayed a recognition accuracy of 80.9% for the features and defects in the test samples. By combining the characteristic signal method and the BP neural network, the defect recognition technology can reduce the subjective influence of inspectors while improving recognition efficiency and accuracy.

A case-based reasoning method for discriminating damage levels in ancient wood components based on fuzzy similarity priority

In order to rapidly identify internal damage levels accurately in ancient wood components, stress wave detection technology was used to perform simulated damage tests on pine specimens. Based on the detected wave velocity data, the diameter of the specimen, the attenuation coefficient, and the ratio of the wave velocities on the four paths were selected as the discriminant factors for identifying the level of internal damage in the specimens. A case-based reasoning method for discriminating internal damage levels in ancient wood components based on fuzzy similarity priority was proposed. A fuzzy similarity priority relationship between the target case and the source case was established. By introducing the idea of variable weights, the weight of each discriminant factor was determined via the “penalize-excitation” variable weight function. The comprehensive similarity sequences between the target case and the source case were obtained. The source case that was most similar to the target case was used to determine the damage level of the target case. The results showed that this method can quickly and accurately identify the damage levels in ancient wood components, which provides a new method for the safe evaluation of ancient wood buildings.

Strength test and penetration effect of intrusion surface of heavy metal contaminated soft rock

ABSTRACT The progressive expansion and contraction damage caused by heavy metal intrusion into rocks is one of causes to the collapse of rock slopes. Based on shear strength test, point load test, disintegration resistance test, durability test and weathering test, the mechanical properties of typical heavy metal contaminated mudstone and sandstone are studied. The spectral band characteristics and spatial frequency changes of mineral elements before and after the intrusion are identified by the spectral diffraction method and acoustic wave detection technology. The penetration effect of heavy metals after intrusion is analyzed. According to the Weibul1 distribution law of microstructure, the discrete characteristics of intrusion failure of the microelement structure of rock under the single-porous medium, and the relationship between the intrusion performance, elongation performance and time of heavy metals are discussed. The results show that the mechanical strength decreases with the intrusion of heavy metals into rock, and the value reduces with the increasing content of intrusive elements. The differentiation degree of intrusion relationship is shown as the relationship of logarithmic function and power function. The spectral color band characteristics and spatial frequency changes reflects the expansion process of the fissure surface after the intrusion of heavy metal into rock effectively. The penetration effect of microstructure caused by the expansion results in the damage of the integrity of rock. The loss of microscopic mineral colloid particles, the expansion of macroscopic cracks and the penetration failure are mainly affected by the intrusion and extension properties of the contaminated elements.