Synchronous Detection Research Articles

Zero-dimensional lead telluride quantum dots optical modulator for red Pr:YLF ultrashort pulse laser

High-quality lead telluride quantum dots (PbTe QDs) are prepared by a top-down liquid phase exfoliation (LPE) method successfully and used as a novel saturable absorber (SA) to first realize a picosecond continuous-wave mode-locked (CWML) red laser with a Pr:YLF crystal. The nonlinear optical saturable characteristic of the PbTe QDs SA is measured by applying a double-channel synchronous detection technique. Further, a picosecond CWML Pr:YLF laser with a highest average output power of 115 mW is obtained, corresponding to a pulse energy of 1.5 nJ and a peak power of 24.2 W. These findings indicate that high-quality PbTe QDs SA is an effective optical modulator, demonstrating its application prospects in the field of visible ultrafast photonics.

Internal inspection method for crack defects in ferromagnetic pipelines under remanent magnetization

Magnetic flux leakage (MFL) testing is effective in detecting corrosion in ferromagnetic pipelines. However, the MFL generated at the crack is highly weak and is easily drowned in the strong background magnetic field and difficult to detect. Therefore, this paper creatively proposes a remanent magnetic flux leakage (RMFL) detection method. This method utilizes the hysteresis state of the pipeline after MFL detection and identifies crack defects by collecting the remanent magnetic flux density near the inner wall surface of the pipeline. The remanent magnetic field distribution near the pipeline surface is examined at different crack sizes, magnetization speeds, and lift-off values via theoretical analysis, finite element simulation, and experimental verification. In addition, experiments have demonstrated that in terms of crack detection capability, RMFL is superior to MFL. Therefore, adding a RMFL measurement module to the conventional MFL detector has important practical value. It can realize the targeted collaborative application of these two technologies, namely the synchronous detection of corrosion and crack defects, which greatly improves the detection coverage and detection efficiency.

Frequency of hepatitis D virus with different hepatitis B virus serological markers and coinfections in hospital patients from Argentina: synchronous testing of anti-HDV antibodies and HDV RNA.

Hepatitis D virus (HDV) RNA-positive cases with total anti-HDV antibodies nonreactive were documented. Moreover, HDV infection was observed in subjects with occult hepatitis B virus infection. The prevalence of HDV infection in Argentina is low; however, further research in different populations is needed. This study aimed to perform synchronous HDV detection in reactive hepatitis B virus patients treated in a public hospital in the province of Buenos Aires, Argentina, some of whom were coinfected with hepatitis C virus and/or HIV. A total of 189 hepatitis B virus-reactive serum samples with or without hepatitis C virus and/or HIV coinfection were synchronously analyzed for anti-HDV antibodies and HDV RNA. HDV prevalence was 4.2% with HDV RNA found in 61 samples, most of which were nonreactive to anti-HDV antibodies and hepatitis B surface antigen. Genotype 1 was identified in all HDV sequences. Moreover, triple and quadruple infections were observed, showing a high frequency of HDV infection in hospitalized patients not following the recommended diagnostic algorithm. This study is evidence that the synchronous testing of anti-HDV antibodies and HDV RNA is necessary for the diagnosis of HDV infection in Argentina. Finally, further research is necessary to identify high-risk populations and improve prevention and control strategies for triple and quadruple infections and their potential consequences.

A Low-Cost, Portable, Multi-Cancer Screening Device Based on a Ratio Fluorometry and Signal Correlation Technique.

The autofluorescence of erythrocyte porphyrins has emerged as a potential method for multi-cancer early detection (MCED). With this method's dependence on research-grade spectrofluorometers, significant improvements in instrumentation are necessary to translate its potential into clinical practice, as with any promising medical technology. To fill this gap, in this paper, we present an automated ratio porphyrin analyzer for cancer screening (ARPA-CS), a low-cost, portable, and automated instrument for MCED via the ratio fluorometry of porphyrins. The ARPA-CS aims to facilitate cancer screening in an inexpensive, rapid, non-invasive, and reasonably accurate manner for use in primary clinics or at point of care. To accomplish this, the ARPA-CS uses an ultraviolet-excited optical apparatus for ratio fluorometry that features two photodetectors for detection at 590 and 630 nm. Additionally, it incorporates a synchronous detector for the precision measurement of signals based on the Walsh-ordered Walsh-Hadamard transform (WHT)w and circular shift. To estimate its single-photodetector capability, we established a linear calibration curve for the ARBA-CS exceeding four orders of magnitude with a linearity of up to 0.992 and a low detection limit of 0.296 µg/mL for riboflavin. The ARPA-CS also exhibited excellent repeatability (0.21%) and stability (0.60%). Moreover, the ratio fluorometry of three serially diluted standard solutions of riboflavin yielded a ratio of 0.4, which agrees with that expected based on the known emission spectra of riboflavin. Additionally, the ratio fluorometry of the porphyrin solution yielded a ratio of 49.82, which was ascribed to the predominant concentration of protoporphyrin IX in the brown eggshells, as confirmed in several studies. This study validates this instrument for the ratio fluorometry of porphyrins as a biomarker for MCED. Nevertheless, large and well-designed clinical trials are necessary to further elaborate more on this matter.

Quantitative suppression of unsteady powerline noise in transient electromagnetic surveys: Adjustment of base-frequency and optimal choice of stacking-times.

Powerline noise is a severe interference source in urban or mine transient electromagnetic (TEM) surveys. TEM systems generally adopt the synchronous detection scheme to suppress the powerline noise. However, when the powerline frequency fluctuates differing from its nominal value (50/60Hz), the considerable powerline noise residue still remains even after synchronous detection. To overcome this problem, this paper proposes the quantitative suppression method for powerline noise taking into account the instability of powerline frequency. The method is based on the adjustment of base-frequency and optimal choice of stacking-times. We represent mathematically the sufficient condition for powerline noise suppression by synchronous detection. It consists of two equations, one with respect to base-frequency and other with respect to stacking-times. The base-frequency is adjusted according to powerline frequency estimate. We first derive the mathematical relationship between frequency estimation accuracy, residual noise amplitude, and stacking-times. Based on it, we develop an efficient algorithm to determine the optimal stacking-times. The algorithm takes as an input the powerline noise estimates and the noise tolerance limit. The tolerance limit is set to a certain value desired by the user, such as 10, 4, and 1 µV. By adjusting base-frequency and determining optimal stacking-times, the powerline noise residue after synchronous detection is reduced to below the desired tolerance limit. We verify the effectiveness of the proposed method for both simulated and actual noise. Experimental results show that the method achieves quantitative suppression of unsteady powerline noise without any damage of effective signal and prevents the measurement time loss due to excessive stacking.

Comprehensive monitoring system for high voltage cables based on the ground current signal of the cable metal sheath

Abstract This paper has presented a comprehensive monitoring system for high voltage cables based on the ground current signal of the cable metal sheath. The system can collect and process the power frequency AC current and three high-frequency partial discharge signals in real time synchronously, which realize the synchronous detection of leakage current, relative dielectric loss, harmonic, partial discharge, and improve the integration of the hardware system.

Multi-frequency weak signal detection based on Liu-like chaotic synchronization system and its hardware circuit implementation

Considering the shortcomings of traditional chaotic systems in weak signal detection methods, such as the high threshold sensitivity requirement and the narrow detection frequency domain. This study proposes a novel three-dimensional chaotic synchronization system, and the dynamical of the system are exhaustively characterized using equilibrium points, phase diagrams, Lyapunov exponential spectra, and bifurcation diagrams. This method involves weak signal detection by means of chaotic synchronization control. Synchronization of a chaotic system using a backstepping synchronization method is used to detect weak signals by analyzing the synchronization error after the introduction of weak signals in a strong noise background. The chaotic system is implemented by hardware circuits, and the simulation of chaotic synchronization control and detection of weak signals from the perspective of circuits is carried out by circuit simulation software. Additionally, the frequency range within which the system is capable of weak signal detection is tested through extensive simulation experiments. Finally, multi-frequency signals detection experiments are performed. The experimental results demonstrate that the system can accurately detect the frequency of weak signals address the limitations of narrow-band detection and multi-frequency signal detection is possible. Meanwhile, the circuit structure proposed in this paper is simple and has some value for engineering applications.

Device for detection of activity-dependent changes in neural spheroids at MHz and GHz frequencies

Intracellular processes triggered by neural activity include changes in ionic concentrations, protein release, and synaptic vesicle cycling. These processes play significant roles in neurological disorders. The beneficial effects of brain stimulation may also be mediated through intracellular changes. There is a lack of label-free techniques for monitoring activity-dependent intracellular changes. Electromagnetic (EM) waves at frequencies larger than 1x106 Hz (1 MHz) were previously used to probe intracellular contents of cells, as cell membrane becomes “invisible” at this frequency range. EM waves interact with membranes of intracellular organelles, proteins, and water in the MHz – GHz range. In this work, we developed a device for probing the interaction between active neurons’ intracellular contents and EM waves. The device used an array of grounded coplanar waveguides (GCPWs) to deliver EM waves to a three-dimensional (3D) spheroid of rat cortical neurons. Neural activity was evoked using optogenetics, with synchronous detection of propagation of EM waves. Broadband measurements were conducted in the MHz-GHz range to track changes in transmission coefficients. Neuronal activity was found to reversibly alter EM wave transmission. Pharmacological suppression of neuronal activity abolished changes in transmission. Time constants of changes in transmission were in the seconds – tens of seconds range, suggesting the presence of relatively slow, activity-dependent intracellular processes. This study provides the first evidence that EM transmission through neuronal tissue is activity-dependent in MHz – GHz range. Device developed in this work may find future applications in studies of the mechanisms of neurological disorders and the development of new therapies.

Secured mutual wireless communication using real and imaginary-valued artificial neuronal synchronization and attack detection

This research presents a cutting-edge security framework that integrates optimal Intrusion Detection System (IDS) and Artificial Neural Networks (ANNs)-based key exchange methods to enhance the reliability of mutual wireless communication in Internet of Medical Things (IoMT) networks. The advent of IoMT technology has brought about a significant transformation in patient care and healthcare operations. It allows for real-time monitoring and diagnosis to be conducted remotely. However, the protection of sensitive medical data has become a crucial issue that has to be addressed to maintain privacy and security. IoMT devices, which have limited processing capabilities, are especially susceptible to cyberattacks, therefore requiring the implementation of new security measures. The proposed methodology offers numerous advantages. By utilizing patient sensor data and analyzing network traffic, the suggested solution surpasses current methods in identifying and preventing network threats with increased precision. This research showcases the better effectiveness of Deep Learning (DL) models in identifying intrusions in IoMT settings, by examining 17 Machine Learning (ML) and 6 DL models. The suggested methodology relies on using a neural sequence of ANNs that consist of both real and imaginary-valued components. This approach enables reciprocal learning and synchronization, which in turn facilitates safe key distribution among IoMT devices. This novel method not only guarantees strong key exchange mechanisms but also enhances the overall security of IoMT networks. This paper presents a complete solution to solve the difficulties of protecting wireless communication in IoMT contexts. This approach performs better than comparable methods in the literature.

Design and Implementation of Optimized PCI Express Physical Layer for High-Speed and Low-Latency Data Transfer

The PCIe (Peripheral Component Interconnect Express) Protocol is crucial for establishing high-speed data communication between computer peripherals, such as graphics cards and network cards etc. This communication protocol is transmitting data in packet format, with each packet containing both data and destination address and other essential information for accurate data delivery. This paper focused on Physical Layer to achieve High-Speed Data Transmission by reducing delay parameter. To minimize disturbances and enhance reliability, the physical layer uses scrambling technique and an 8b – 10b encoding technique is used for synchronization and error detection. Additionally, SIPO and PISO converts data format to improve efficiency and accuracy. The design is implemented using the Cadence compiler targeting 45nm process technology. This design is delay efficient resulting in path delay of 5.0ns and the operating frequency of 200MHz, power consumption of 1.2mw and an area of 1999µm².

High-Sensitivity Refractive Index Sensor with Dual-Channel Based on Surface Plasmon Resonance Photonic Crystal Fiber.

In order to achieve a high-precision synchronous detection of two different refractive index (RI) analytes, a D-type surface plasmon resonance (SPR) photonic crystal fiber (PCF) RI sensor based on two channels is designed in this paper. The sensor uses a D-shaped planar region of the PCF and a large circular air hole below the core as the sensing channels. Surface plasmon resonance is induced by applying a coating of gold film on the surface. The full-vector finite-element method (FEM) is used to optimize the structural parameters of the optical fiber, and the sensing characteristics are studied, including wavelength sensitivity, RI resolution, full width at half maximum (FWHM), figure of merit (FOM), and signal-to-noise ratio (SNR). The results show that the channel 1 (Ch 1) can achieve RI detection of 1.36-1.39 in the wavelength range of 1500-2600 nm, and the channel 2 (Ch 2) can achieve RI detection of 1.46-1.57 in the wavelength range of 2100-3000 nm. The two sensing channels can detect independently or simultaneously measure two analytes with different RIs. The maximum wavelength sensitivity of the sensor can reach 30,000 nm/RIU in Channel 1 and 9900 nm/RIU in Channel 2. The RI resolutions of the two channels are 3.54 × 10-6 RIU and 10.88 × 10-6 RIU, respectively. Therefore, the sensor realizes dual-channel high- and low-RI synchronous detection in the ultra-long wavelength band from near-infrared to mid-infrared and achieves an ultra-wide RI detection range and ultra-high wavelength sensitivity. The sensor has a wide application prospect in the fields of chemical detection, biomedical sensing, and water environment monitoring.

Real-time detection of the lateral resistance of ballast bed during track realigning in tamping: A novel test method based on track shifting operation

Real-time detection of the mechanical state of ballast bed during the tamping operation in railway maintenance is of great significance for improving the effectiveness of operations. In this study, a novel test method named the track shifting test was proposed based on the track realigning operation of the tamping vehicle. The track panel was pushed by the shifting device. Moreover, the lateral resistance of ballast bed was reflected through easily measured indexes. An accurate coupling model of the shifting device and the ballasted track was constructed. Based on the model, the mechanical response of ballast and the track panel induced by the shifting load was analyzed. Results indicated that at an effective loading displacement of 2mm, the lateral resistance of ballast bed within a detectable range of up to five sleepers can be inverted by the shifting force and the displacement of sleepers. A machine learning model was established to obtain the mapping relationship between the shifting force, the displacement of sleepers, and the lateral resistance of ballast bed. Therefore, real-time detection of the lateral resistance was achieved by combining the proposed test method and the machine learning algorithm. This study can contribute to the synchronous detection of the mechanical state of ballast bed during tamping operation.

Passive Vision Detection of Torch Pose in Swing Arc Narrow Gap Welding.

To enhance the synchronous detection of the horizontal and vertical positions of the torch in swing arc narrow gap welding, a torch pose detection (TPD) method is proposed. This approach utilizes passive visual sensing to capture images of the arc on the groove sidewall, using advanced image processing methods to extract and fit the arc contour. The coordinates of the arc contour center point and the highest point are determined through the arc contour fitting line. The torch center position is calculated from the average horizontal coordinates of the arc contour centers in adjacent welding images, while the height position is determined from the vertical coordinate of the arc's highest point. Experimental validation in both variable and constant groove welding conditions demonstrated the TPD method's accuracy within 0.32 mm for detecting the torch center position. This method eliminates the need to construct the wire centerline, which was a requirement in previous approaches, thereby reducing the impact of wire straightness on detection accuracy. The proposed TPD method successfully achieves simultaneous detection of the torch center and height positions, laying the foundation for intelligent detection and adaptive control in swing arc narrow gap welding.

A dynamic object removing 3D reconstruction system based on multi-sensor fusion

Abstract Currently, one of the key technologies for autonomous navigation of unmanned mobile robots is SLAM, which faces many challenges in practical applications. These challenges include a lack of texture, deterioration in sensor performance, and interference from moving objects in dynamic outdoor environments, all of which have an impact on the mapping system. To address these issues, this paper proposes a framework for lidar, vision camera, and inertial navigation data, resulting in fusion and dynamic object removing. The system consists of three sub-modules: the Lidar-Inertial Module (LIM), the Visual-Inertial Module (VIM), and the Dynamic-Object-Removing Module (DORM). LIM and VIM assist each other, with lidar point clouds providing three-dimensional information for the global voxel map and the camera providing pixel-level color information. At the same time, the DORM performs synchronous dynamic object detection to remove dynamic objects from the global map. The system constructs a multi-sensor factor graph using the state and observation models, and the optimal solution is obtained using least squares. Furthermore, this paper employs triangle descriptors and bundle adjustment methods for loop closure detection in order to reduce accumulated errors and maintain consistency. Experimental results demonstrate that the system can perform clean state estimation, dynamic removing and scene reconstruction in a variety of complex scenarios.

A dual-channel sensing platform for the cross-interference-free detection of tetracycline and copper ion

Tetracycline (TC) and copper ion (Cu2+), as important additives in animal feed, play a crucial role in disease prevention and growth regulation. However, the abuse leads to concentration accumulation, which seriously threatens human health and the ecological environment. There is an urgent need to develop a detection method to achieve fast and synchronous detection of these pollutants without cross-interference. Here, a carbon dots-doped lanthanide-based fluorescent nanosensor (CDs@Tb-MOFs@SiO2–NH2-Eu) was synthesized, which can detect TC in the 380 nm channel by “antenna effect” and internal filtering effects (IFE), and identify Cu2+ in the 320 nm channel. The sensor was highly sensitive to TC within 0–4 μM with a detection limit as low as 3.64 nM, and Cu2+ could be detected within 0–40 μM with a detection limit of 38 nM. A portable dual-channel visual fluorescence sensor was obtained by loading the probes onto test paper and cotton swabs in food samples, which indicates the practicability of this sensing strategy.

A novel Au nanoparticles/ionic liquids/N‐ and P‐co‐doped carbon nanotubes‐modified carbon cloth sensor for the sensitive detection of adrenaline

AbstractAdrenaline (AD) is important in information transmission through the human central nervous system. Considering the significant biochemical functions of AD, the development of electrochemical sensors capable of detecting AD levels in living organisms has attracted considerable interest. In this study, AD was detected using electrochemical sensors developed based on Au nanoparticles/ionic liquids/N‐ and P‐co‐doped carbon nanotubes‐modified carbon cloth (AuNPs/ILs/N,P‐MWCNTs/CC) electrodes. AuNPs/ILs/N,P‐MWCNTs/CC composites were prepared on carbon cloth (CC) substrates using ionic liquids (ILs), N‐ and P‐co‐doped multi‐walled carbon nanotubes (N,P‐MWCNTs), and Au nanoparticles (AuNPs) as modified materials. The effects of pH and scanning speed were optimized and tested on the prepared composites. The results of cyclic voltammetry (CV) and differential pulse voltammetry (DPV) experiments showed that the modified ILs, N,P‐MWCNTs, and AuNPs effectively improved the oxidation performance of AD. In addition, the linear range obtained from the DPV scans of the AuNPs/ILs/N,P‐MWCNTs/CC composite material was 30–505 μmol/L, with a detection limit of 0.31 μmol/L. The fabricated sensors have good sensitivity (6.9 μA·mM−1·cm−2) for AD of 30–505 μM. Therefore, the electrochemical sensing method based on the AuNPs/ILs/N,P‐MWCNTs/CC composite material is a promising and reliable AD detection technology that also exhibits good selectivity in the presence of interfering substances such as folic acid and ibuprofen. In practical applications, this material can help realize real‐time AD detection to determine whether athletes use doping and other illegal drugs before competitions and to perform synchronous detection.

Experimental study on synchronous detection of output force in a self-sensing giant magnetostrictive actuator

This paper systematically investigates the real-time detection of static and dynamic output forces by a self-sensing giant magnetostrictive actuator (SSGMA). The online stiffness of the actuator is perceived as the sensing signal according to the ΔE effect of Terfenol-D. Numerical simulations are carried out to analyze the effects of the driving magnetic field and the hysteresis caused by magneto-mechanical coupling on the performance of self-sensing output force. Then the prototype is fabricated and tested to verify the self-sensing characteristics of SSGMA for the output force. The noise density of prototype is tested to be below 56.92 nV √Hz−1. The experimental results illustrate that SSGMA has a self-detection sensitivity of 0.47 mV N−1 for a static force with an amplitude of nearly 120 N. The SSGMA is able to synchronize the tracking of quasi-static and low-frequency dynamic output forces, respectively. The hereby proposed SSGMA further broadens the application scenario of precision actuation systems by synchronizing the detection and control of the output force without requiring external sensors.

Robust and fast backbone tracking via phase-locked loops

Phase-locked loops are commonly used for shaker-based backbone tracking of nonlinear structures. The state of the art is to tune the control parameters by trial and error. In the present work, an approach is proposed to make backbone tracking much more robust and faster. A simple PI controller is proposed, and closed-form expressions for the gains are provided that lead to an optimal settling of the phase transient. The required input parameters are obtained from a conventional shaker-based linear modal test, and an open-loop sine test at a single frequency and level. For phase detection, an adaptive filter based on the LMS algorithm is used, which is shown to be superior to the synchronous demodulation commonly used. Once the phase has locked, one can directly take the next step along the backbone, eliminating the hold times. The latter are currently used for recording the steady state, and to estimate Fourier coefficients in the post-process, which becomes unnecessary since the adaptive filter yields a highly accurate estimation at runtime. The excellent performance of the proposed approach is demonstrated for a doubly clamped beam undergoing bending–stretching coupling leading to a 20 percent shift of the lowest modal frequency. Even for fixed control parameters, designed for the linear regime, only about 100 periods are needed per backbone point, also in the nonlinear regime. This is much faster than what has been reported in the literature so far.

Sessile serrated lesion prevalence and factors associated with their detection: a post-hoc analysis of a multinational randomized controlled trial from Asia.

Sessile serrated lesions (SSLs) are associated with an increased risk of colorectal cancer. Data on the prevalence of SSLs in Asia are limited. We performed this study to estimate the prevalence of SSLs in Asia and to explore endoscopic factors that are associated with SSL detection. This is a post-hoc analysis of a multicenter randomized controlled trial from four Asian countries/regions that compared adenoma detection rates using linked-color imaging (LCI) and white-light imaging. Colonoscopies were performed in an average-risk population for screening, diagnostic examination, or polyp surveillance. Patients with SSLs were compared against those without SSLs to evaluate for possible predictors of SSL detection using Firth's logistic regression. 2898 participants (mean age 64.5 years) were included in the analysis. The estimated prevalence of SSLs was 4.0% (95%CI 3.4%-4.8%), with no sex or age group differences. On multivariable analysis, use of LCI (adjusted odds ratio [aOR] 1.63, 95%CI 1.10-2.41), experienced endoscopists (aOR 1.94, 95%CI 1.25-3.00), use of transparent cap (aOR 1.75, 95%CI 1.09-2.81), and longer withdrawal time (aOR 1.06, 95%CI 1.03-1.10) were independently associated with SSL detection. Synchronous adenoma detection (aOR 1.89, 95%CI 1.20-2.99) was also predictive of SSL detection. The prevalence of SSLs in Asia is 4.0%. Use of LCI or a transparent cap, greater endoscopist experience, and longer withdrawal time were all associated with increased SSL detection.

Hybrid fiber-based time synchronization and vibration detection system.

We propose a hybrid fiber-based time synchronization and vibration detection system. The vibration is detected by exploring the idle light of the time synchronization system, i.e., the Rayleigh backscattering of the timing pulse disseminated in the fiber link. The addition of a sensing function does not affect the performance of time synchronization. In the multiuser experimental demonstration, time deviation results are 3.6 ps at τ = 1 s and 1.4 ps at τ = 104 s on the 40-km fiber link. Meanwhile, the hybrid system can accurately detect and locate vibrations occurring on the link. This method enables multiple functions of the optical fiber network without occupying extra optical channels. Moreover, it gives a possible solution for enhancing the security of the time synchronization network through vibration detection.