Angle Detection Research Articles

A multiscale nonreciprocal thermal radiation multilayer structure based on Weyl semimetal with angle and refractive index detection

In this paper, a multiscale nonreciprocal multilayer structure based on the Weyl semimetal is investigated. This multilayer structure enables the realization of nonreciprocal thermal radiation, as well as angle and refractive index (RI) detection at both θ and -θ angles of the forward and backward scenarios. Scenarios are used to describe the electromagnetic waves (EWs) incident from forward or backward with θ or -θ direction. When the EWs incident from the four scenarios, the localized electric field energy caused by the defect mode triggers a sharp emission peak (EP) within the terahertz range. Moreover, the frequency points of EP will shift regularly with changes in physical quantities. Hence, by precisely locating the frequency points of EP, the angle and RI across four scenarios can be detected. The broadest detection range for angle and RI is 30 degrees∼70 degrees and 1.4–1.9. Furthermore, the best performance of quality factor, the figure of merit, and the detection limit are 508.9, 1.3 degree−1, 4.2 × 10−2 degrees, and 671.7, 63.6 RIU−1, 7.9 × 10−4 RIU, respectively. The concepts and conclusions obtained from this article can offer new possibilities for the construction of novel sensing devices, energy harvesting devices, energy conversion devices, nonreciprocal thermal emitters, etc.

An improved calibration procedure for accurate plastic scintillation dosimetry on an MR-linac.

Plastic scintillation dosimeters (PSDs) are highly suitable for real-time dosimetry on the MR-linac. For optimal performance, the primary signal (scintillation) needs to be separated from secondary optical effects (Cerenkov, fluorescence and optical fiber attenuation). This requires a spectral separation approach and careful calibration. Currently, the 'classic' calibration is a multi-step procedure using both kV and MV X-ray sources, requiring an uninterrupted optical connection between the dosimeter and read-out system, complicating efficient use of PSDs. Therefore, we present a more time-efficient and more practical novel calibration technique for PSDs suitable for MR-linac dosimetry.
Approach: The novel calibration relies on prior spectral information combined with two 10x10 cm2field irradiations on the 1.5 T MR-linac. Performance of the novel calibration technique was evaluated focusing on its reproducibility, performance characteristics (repeatability, linearity, dose rate dependency, output factors, angular response and detector angle dependency) and IMRT deliveries. To investigate the calibration stability over time, prior spectral information up to 315 days old was used. To quantify the time efficiency, each step of the novel and classic calibration was timed.
Main results: The novel calibration showed a high reproducibility with a maximum relative standard deviation of 0.3%. The novel method showed maximum differences of 1.2% compared to the gold-standard calibration, while reusing old classic calibrations after reconnecting fibers showed differences up to 3.0%. The novel calibration improved time efficiency from 105 to 30 minutes compared to the classic method.
Significance: The novel calibration method showed a gain in time efficiency and practicality while preserving the dosimetric accuracy. Therefore, this method can replace the traditional method for PSDs suitable for MR-linac dosimetry, using prior spectral information of up to a year. This novel calibration facilitates reconnecting the detector to the read-out system which would lead to unacceptable dosimetric results with the classic calibration method.

An Optimized Graphene-Based Surface Plasmon Resonance Biosensor for Detecting SARS-CoV-2

Graphene-enhanced surface plasmon resonance (SPR) biosensors offer promising advancements in viral detection, particularly for SARS-CoV-2. This study presents the design and optimization of a multilayer SPR biosensor incorporating silver, silicon nitride, single-layer graphene, and thiol-tethered ssDNA to achieve high sensitivity and specificity. Key metrics, including SPR angle shift (Δθ), sensitivity (S), detection accuracy (DA), and figure of merit (FoM), were assessed across SARS-CoV-2 concentrations from 150 to 525 mM. The optimized biosensor achieved a sensitivity of 315.91°/RIU at 275 mM and a maximum Δθ of 4.2° at 400 mM, demonstrating strong responsiveness to virus binding. The sensor maintained optimal accuracy and figure of merit at lower concentrations, with a linear sensitivity response up to 400 mM, after which surface saturation limited further responsiveness. These results highlight the suitability of the optimized biosensor for real-time, point-of-care SARS-CoV-2 detection, particularly at low viral loads, supporting its potential in early diagnostics and epidemiological monitoring.

A continuous plane of polarization rotator and detector based on the liquid crystal Θ-cell

Modulation of the polarization state of optical beams is crucial in advanced optical applications such as polarization microscopy, polarization rotation, and medical imaging. We demonstrate a continuous polarization rotator (PR) by utilizing the liquid crystals (LC) in Θ-cell configuration comprising of circular and parallel alignment of LC on two aligning glass substrates. A rotation of plane of polarization (PoP) up to ∼ 160˚ is observed using Stokes polarimetry. This is further substantiated by the mathematical analysis using Mueller matrix formalism. Further, the device is demonstrated as a PoP detector with high precision detection angle. The PoP is analyzed through single-shot imaging of the intensity distribution of transmitted light through the LC Θ-cell.

Observation of planar Hall effect in the topological insulator NaCd4As3

The observation of the planar Hall effect (PHE) illuminates the spin textures and topological properties of materials, indicating potential applications in quantum computing and electronic devices. Here, we present a study on the planar Hall transport of topological insulator NaCd4As3 single crystals. When the magnetic field is rotated within the sample plane relative to the current direction, we observe remarkable planar Hall resistivity and giant planar anisotropic magnetoresistance (AMR), both consistent with the theoretical expression of the PHE. Further analysis reveals that the orbital magnetoresistance effect, unrelated to surface electrons from topological surface states or bulk electrons from nontrivial Berry phases, lays a dominant role in the PHE in NaCd4As3. Additionally, the AMR ratio reaches −43% at 3 K under 14 T and remains −9% at room temperature, markedly exceeding that of traditional ferromagnetic metals. These findings provide a platform for understanding the PHE mechanism in topological insulators and highlight the potential of NaCd4As3 for angle and magnetic field detection applications.

A hydrogel sensor based on conic baston structure

AbstractResistive flexible pressure sensors are extensively employed in wearable devices owing to their wide operational range and straightforward construction. This study presents a conic bastion‐structured sensor microunit to improve the sensor sensitivity. The base hydrogel is synthesized using acrylamide (AM), with Mg2+ and Na+ acting as conductive ions. The sensor is fabricated using digital light processing (DLP) 3D printing technology and is subjected to experimental evaluation. The findings indicate that the hydrogel sensor with a 50 wt% AM composition demonstrates enhanced mechanical strength and conductive properties, achieving a peak sensitivity of 0.534 kPa−1 within a pressure range of 0–0.8 kPa. Furthermore, the sensor exhibits favorable response characteristics (30 ms) and recovery characteristics (40 ms), along with stability. The proposed sensor is suitable for wearable devices and live joint angle detection. Additionally, the “handwriting fingerprint” pattern recognition and document verification proposed in this article make it applicable in scenarios, such as banking, notarization, and other handwriting and seal verification contexts.

A geometric model with stochastic error for abnormal motion detection of portal crane bucket grab

Abnormal swing angle detection of bucket grabs is crucial for efficient harbor operations. In this study, we develop a practically convenient swing angle detection method for crane operation, requiring only a single standard surveillance camera at the fly-jib head, without the need for sophisticated sensors or markers on the payload. Specifically, our algorithm takes the video images from the camera as input. Next, a fine-tuned ‘the fifth version of the You Only Look Once algorithm’ (YOLOv5) model is used to automatically detect the position of the bucket grab on the image plane. Subsequently, a novel geometric model is constructed, which takes the pixel position of the bucket grab, the steel rope length provided by the Programmable Logic Controller (PLC) system, and the optical lens information of the camera into consideration. The key parameters of this geometric model are statistically estimated by a novel iterative algorithm. Once the key parameters are estimated, the algorithm can automatically detect swing angles from video streams. Being analytically simple, the computation of our algorithm is fast, as it takes about 0.01 s to process one single image generated by the surveillance camera. Therefore, we are able to obtain an accurate and fast estimation of the swing angle of an operating crane in real-time applications. Simulation studies are conducted to validate the model and algorithm. Real video examples from Qingdao Seaport under various weather conditions are analyzed to demonstrate its practical performance.

CSSF-BL360: Color Segmentation-Based Bolt Localization and 0~360° Full-Scale Loosening Angle Detection in Single-Frame Images

Introduction: Bolt loosening detection plays a crucial role in ensuring structural safety. Existing research using deep learning methods has the drawback of being applicable to limited scenarios and typically requires at least two frames of images for comparison in subsequent angle detection, with a limited range of detectable angles. Method: In this study, a color segmentation method was first used to separate the red square gasket placed between the bolt and the base, thereby locating the bolt area; then, the image was perspective-corrected using the four corners of the red square gasket; finally, the red mark bars on the bolt and base were separated using the same color segmentation method, and the geometric moments of the connected domains of the mark bars were processed, combined with vector processing techniques, to achieve quantified detection of bolt loosening angles within 0~360 degrees using a single frame image. In the verification experiments, 150 images were collected from different shooting angles and distances, and the bolt areas to be tested were located using the color segmentation method, all with an IOU (Intersection over Union) greater than 0.9317. Subsequent experiments set different variables, including different shooting distances, bolt loosening angles, perspective angles, lighting conditions, bolt types, and image rotation angles. Result: The results demonstrated that the method presented in this study could accurately detect bolt loosening angles in multiple scenarios. Conclusion: Hence, it is capable of measuring loosening angles within the range of 0~360 degrees using only a single frame image. result: In the verification experiments, 150 images were collected from different shooting angles and distances, and the bolt areas to be tested were located using the color segmentation method, all with an IOU(Intersection over Union) greater than 0.9317. Subsequent experiments set different variables, including different shooting distances, bolt loosening angles, perspective angles, lighting conditions, bolt types, and image rotation angles.

Vision-Based Real-Time Bolt Loosening Detection by Identifying Anti-Loosening Lines

Bolt loosening detection is crucial for ensuring the safe operation of equipment. This paper presents a vision-based real-time detection method that identifies bolt loosening by recognizing anti-loosening line markers at bolt connections. The method employs the YOLOv10-S deep learning model for high-precision, real-time bolt detection, followed by a two-step Fast-SCNN image segmentation technique. This approach effectively isolates the bolt and nut regions, enabling accurate extraction of the anti-loosening line markers. Key intersection points are calculated using ellipse and line fitting techniques, and the loosening angle is determined through spatial projection transformation. The experimental results demonstrate that, for high-resolution images of 2048 × 1024 pixels, the proposed method achieves an average angle detection error of 1.145° with a detection speed of 32 FPS. Compared to traditional methods and other vision-based approaches, this method offers non-contact measurement, real-time detection capabilities, reduced detection error, and general adaptability to various bolt types and configurations, indicating significant application potential.

Main lobe deceptive jamming suppression based on blind source separation and energy detection for monopulse radar

AbstractMain lobe deceptive jamming always causes the serious degradation of signal detection ability and angle measurement precision of monopulse radar. In recent years, the Blind Source Separation (BSS) method has been adopted to suppress the main lobe jamming. However, the separation results of BSS have the problem of amplitude ambiguity, which will cause the radar using monopulse angle measurement fail to measure the angle parameters after jamming suppression. To tackle this problem, a novel main lobe jamming suppression method is proposed based on BSS and energy detection. Firstly, the models of target echoes and jamming in the sum and difference beam receiving channels are derived. Secondly, the target echoes and interferences are separated by the Joint Approximate Diagonalisation of Eigenmatrices (JADE) algorithm, and then the unperturbed signal segments in the mixed signal are extracted by energy detection, thereby obtaining the precise ratio of the sum and difference channels to complete the angle measurement. Performance of the method was verified by numerical simulation. The results show that the proposed method can achieve interference suppression while accurately estimating the angle parameter of the target.

A new solution for the observed isotropic cosmic birefringence angle and its implications for the anisotropic counterpart through a Boltzmann approach

Abstract Cosmic Birefringence (CB) is a phenomenon in which the polarization of the Cosmic Microwave Background (CMB) radiation is rotated as it travels through space due to the coupling between photons and an axion-like field. We look for a solution able to explain the result obtained from the Planck Public Release 4 (PR4), which has provided a hint of detection of the CB angle, α = (0.30 ± 0.11)∘. In addition to the solutions, already present in the literature, which need a non-negligible evolution in time of the axion-like field during recombination, we find a new region of the parameter space that allows for a nearly constant time evolution of such a field in the same epoch. The latter reinforces the possibility to employ the commonly used relations connecting the observed CMB spectra with the unrotated ones, through trigonometric functions of the CB angle. However, if the homogeneous axion field sourcing isotropic birefringence is almost constant in time during the matter-dominated era, this does not automatically imply that the same holds also for the associated inhomogeneous perturbations. For this reason, in this paper we present a fully generalized Boltzmann treatment of this phenomenon, that is able, for the first time to our knowledge to deal with the time evolution of anisotropic cosmic birefringence (ACB). We employ this approach to provide predictions of ACB, in particular for the set of best-fit parameters found in the new solution of the isotropic case. If the latter is the correct model, we expect an ACB spectrum of the order of (10-15 ÷ 10-32) deg2 for the auto-correlation, and (10-7 ÷ 10-17) μK·deg for the cross-correlations with the CMB T and E fields, depending on the angular scale.

Numerical Simulation of Spectral Radiation for Hypersonic Vehicles

The spectral radiation of hypersonic vehicles and surrounding flow fields is crucial for optical target detection. A novel approach combines Low-Discrepancy Sequences with the Reverse Monte Carlo Method to simulate the spectral radiation of hypersonic missiles. The effects of chemical non-equilibrium reactions and high-emissivity coating failures on the spectral radiation of a typical biconical hypersonic missile were investigated. Significant differences were found among chemical equilibrium, non-equilibrium, non-reactive, and catalytic wall models. High-emissivity coating failures occur mainly in the high-temperature regions of the nose cone and fins. The non-equilibrium model shows a transition peak distribution of NO in the head shock layer within the ultraviolet gamma band, with integrated ultraviolet radiation (200–300 nm) three times higher than the equilibrium model. In the 1–3 μm band, the non-equilibrium model’s radiation intensity at a 120° horizontal detection angle is about 1.46 times that of the equilibrium model. Using real coating emissivity, the 3–5 μm band radiation intensity is about 5% higher, and the 8–14 μm band is about 8.51% lower than the uniform emissivity model. When high-emissivity coating emissivity fails by 40%, the 3–5 μm band intensity decreases by about 15.38%, and the 8–14 μm band intensity decreases by about 12.67%.

Acquired angle error correction based on variation of an angle detection signal intensity in rotary encoders

Abstract Rotary encoders are used in various machines to measure the angular position of a rotating axis. Therefore, rotary encoders are required not only to be highly accurate, but also usable in various environments. When using a rotary encoder on a machine, angle errors occur due to eccentricity between the encoder and the machine, the deformation of the scale, and the shaft runout of a rotation axis. Various methods have been adopted to reduce such angle errors. However, these methods have problems such as the large size and high cost of the rotary encoder, the necessity of additional devices for measuring, and increasing installation labor, so the environment in which they can be implemented is limited. In this study, we have proposed a method to correct the angle errors based on variation of an angle detection signal intensity in the sensor head. This method can correct the errors on machine without using multiple sensor heads or separate devices. The angle error estimated by this method is compared with that measured by the external equipment of a reference encoder. While the maximum angle error was 28.36” without correction, the residual error with correction can be reduced to 1.75” or less. From this result, the proposed method can improve the measurement accuracy of the rotary encoder already installed on the machine. Therefore, this method is an effective means for achieving both high rotational accuracy on machines and ease of correcting an error in rotary encoders to the machines.

Comparison of Faster R-CNN, YOLO, and SSD for Third Molar Angle Detection in Dental Panoramic X-rays.

The use of artificial intelligence algorithms (AI) has gained importance for dental applications in recent years. Analyzing AI information from different sensor data such as images or panoramic radiographs (panoramic X-rays) can help to improve medical decisions and achieve early diagnosis of different dental pathologies. In particular, the use of deep learning (DL) techniques based on convolutional neural networks (CNNs) has obtained promising results in dental applications based on images, in which approaches based on classification, detection, and segmentation are being studied with growing interest. However, there are still several challenges to be tackled, such as the data quality and quantity, the variability among categories, and the analysis of the possible bias and variance associated with each dataset distribution. This study aims to compare the performance of three deep learning object detection models-Faster R-CNN, YOLO V2, and SSD-using different ResNet architectures (ResNet-18, ResNet-50, and ResNet-101) as feature extractors for detecting and classifying third molar angles in panoramic X-rays according to Winter's classification criterion. Each object detection architecture was trained, calibrated, validated, and tested with three different feature extraction CNNs which are ResNet-18, ResNet-50, and ResNet-101, which were the networks that best fit our dataset distribution. Based on such detection networks, we detect four different categories of angles in third molars using panoramic X-rays by using Winter's classification criterion. This criterion characterizes the third molar's position relative to the second molar's longitudinal axis. The detected categories for the third molars are distoangular, vertical, mesioangular, and horizontal. For training, we used a total of 644 panoramic X-rays. The results obtained in the testing dataset reached up to 99% mean average accuracy performance, demonstrating the YOLOV2 obtained higher effectiveness in solving the third molar angle detection problem. These results demonstrate that the use of CNNs for object detection in panoramic radiographs represents a promising solution in dental applications.

Enhanced slit methodology for characterization of x‐ray focal properties

AbstractThe measurement of focal spot sizes in industrial x‐ray tubes using conventional edge and slit methods typically requires complex slit diaphragms and auxiliary testing equipment. Additionally, stringent spatial‐positioning requirements are imposed on the x‐ray tube, auxiliary testing equipment, and detector, making the machining of auxiliary testing equipment and meeting test conditions challenging. This study optimized and improved the auxiliary testing equipment and computations in the slit method based on the principles of the edge method. An experimental setup capable of self‐calibrating the spatial positions was designed, avoiding measurement errors during focal‐spot‐size measurements. We derived a formula for the focal spot size for this experimental setup, allowing measurements using slits of various sizes. Furthermore, we proposed a method for determining the focal spot size through linear fitting of multiple sets of slit dimensions and projected widths of the focal spot on the detector. This approach filters out random noise and errors during data collection, significantly enhancing measurement precision. By adjusting the slit and detector angles, we could measure the focal spot sizes at various angles and draw contour maps of the focal spot shape. This method was applied to measure the focal spot size and shape of a side‐window x‐ray tube under different voltage conditions. The overall measurement error was less than 6%, reflecting the reliability, accuracy, and consistency of the results obtained using the proposed method. Thus, the proposed method supports the inspection, verification, and maintenance of x‐ray sources.

Role of citric acid in selective flotation of limonite from quartz using sodium oleate as collector

The issue that eliminating the negative effects of inevitable ions in the pulp on mineral flotation separation has attracted widespread attention. To achieve the efficient flotation separation of limonite from quartz, citric acid was utilized as a depressant for quartz in this paper. The solubility of limonite was studied using inductively coupled plasma tests (ICP), and the effect of Fe3+ and citric acid on the separation of limonite from quartz under sodium oleate (NaOL) system was investigated using batch flotation tests. The underlying mechanisms were probed through zeta potential measurements, infrared spectroscopy (IR), X-ray photoelectron spectroscopy (XPS), and contact angle detection. It was found that limonite could dissolve a certain number of Fe3+ in the pulp. These Fe3+ adsorbed onto quartz and acted as the active sites to promote the adsorption of NaOL, thereby enhancing quartz flotation evidently and deteriorating the separation of limonite from quartz. Fortunately, citric acid could depress the flotation of iron-activated quartz quite well by covering and desorbing the active sites of Fe3+ and causing the steric hindrance to prohibit the adsorption of NaOL. Meanwhile, the hydrophilic groups in citric acid could also increase the surface hydrophilicity of quartz and enhance the inhibitory effect. In comparison, Fe3+ and citric acid had little effect on the adsorption of NaOL onto limonite since its surface exposed enough Fe-active sites for the adsorption of NaOL. Thus, the difference in the floatability of limonite and quartz was enlarged, eventually achieving a better separation of them. This research sheds new light on the role of citric acid in the selective separation of quartz from soluble iron minerals.

Angular distribution measurements of neutron elastic scattering on natural carbon

The angular distributions of neutron elastic scattering on natural carbon were studied in the fast neutron energy region between 1 and 8 MeV. The experiments were carried out at the white neutron source of the Geel Electron Linear Accelerator (GELINA) facility by using thin and thick natural carbon samples. This work demonstrates the need for using thin samples to avoid strong multiple scattering effects. Neutrons and γ rays from scattering were detected using the ELastic and Inelastic Scattering Array (ELISA), a setup consisting of 32 liquid organic scintillators. The n−γ separation was achieved via pulse-shape analysis. For each sample a different approach in methodology is studied, one based on a global response function model and another one based on a per-detector model. The detectors are placed at eight different detection angles between 16∘ and 164∘ with respect to the neutron beam direction, allowing the simultaneous calculation of both the differential and the integral cross section by implementing the Gauss-Legendre quadrature rule. The neutron flux was measured with a U235 ionization chamber. The angular distributions were extracted relative to the U235(n,f) cross section. The results are compared with other experimental data available in the EXFOR library, along with the most recent nuclear data evaluations. The angle-integrated cross sections are in excellent agreement with the nuclear data evaluations and for the angular distributions, ENDF/B-VIII.0 is better reproducing the experimental data in all eight detection angles. Published by the American Physical Society 2024

Novel drainage pipeline breakages detection based on MEMS inertial sensor: From mechanism to application

Urban water environment pollution is a global concern, in developing countries, sewage infiltration resulting from urban drainage pipelines breakage is an essential element in the urban groundwater pollution and the recurrence of black odor water bodies, it is crucial to accurately and efficiently detection and localisation of urban drainage pipelines breakage to protect the urban water resources. In this paper, a device for detecting defects in drainage pipelines was developed and assembled using microelectromechanical systems (MEMS) inertial sensors as the core components, and the improved cumulative sum (CUSUM) model was used for anomalous detection of the pitch angle of the device's movement along the course of the pipeline as a method of detecting pipeline breakage. In the laboratory simulation of drainage pipeline tests, the CUSUM peaks (0.709, 1.102, 3.038, 7.990) for the case of external water infiltration rates into the pipeline at the point of pipe breakage (2.9%, 4.6%, 5.8%, 9.2%), and for the cases of sewer exfiltration rates in the pipeline of 4.2% and 6.4% (0.760, 1.382). CFD simulations of the water flow in the laboratory pipeline show a high degree of overlap between the trend of the water surface near the point of breakage and the anomalous fluctuations in the pitch angle of the device motion in the laboratory tests. Finally, the authors tested the device on municipal drains in the city of A. The results demonstrated the reliability and high accuracy of the device. The device enables to improve the ecological quality of urban water environment by accelerating the rate of defect detection in urban drainage pipelines and reducing the detection expenses.

Hemispherical Retina Emulated by Plasmonic Optoelectronic Memristors with All-Optical Modulation for Neuromorphic Stereo Vision.

Binocular stereo vision relies on imaging disparity between two hemispherical retinas, which is essential to acquire image information in three dimensional environment. Therefore, retinomorphic electronics with structural and functional similarities to biological eyes are always highly desired to develop stereo vision perception system. In this work, a hemispherical optoelectronic memristor array based on Ag-TiO2 nanoclusters/sodium alginate film is developed to realize binocular stereo vision. All-optical modulation induced by plasmonic thermal effect and optical excitation in Ag-TiO2 nanoclusters is exploited to realize in-pixel image sensing and storage. Wide field of view (FOV) and spatial angle detection are experimentally demonstrated owing to the device arrangement and incident-angle-dependent characteristics in hemispherical geometry. Furthermore, depth perception and motion detection based on binocular disparity have been realized by constructing two retinomorphic memristive arrays. The results demonstrated in this work provide a promising strategy to develop all-optically controlled memristor and promote the future development of binocular vision system with in-sensor architecture.

Cell sorting based on pulse shapes from angle resolved detection of scattered light

Flow cytometry is a key technology for the analysis and sorting of cells or particles at high throughput. Conventional and current flow cytometry is primarily based on fluorescent stains to detect the cells of interest. However, such stains also have disadvantages, as their effect on cells must be carefully tested to avoid effects on the results of the experiments. Alternative approaches using imaging or other label-free techniques often require highly sophisticated setups, are commonly limited in resolution, and produce challenging amounts of data. Our technology exploits scattered light instead. The custom-built flow cytometry setup comprises a fiber array in forward scatter detection for angular resolution and captures the whole pulse shape with advanced signal processing. Thereby this setup enables cell analysis and sorting purely based on scattered light signals without the need for fluorescent labels. We demonstrate the feasibility of this cell sorting technology by sorting cell lines for their cell cycle stages based on scattered light. Furthermore, we demonstrate the ability to classify human peripheral blood T- and B-cell subsets.