Time-domain Analysis Method Research Articles

A clinical validation of AViTA home blood pressure monitor for atrial fibrillation detection in adults.

Atrial fibrillation (AF) is a stroke and heart complication riskbut is often overlooked due to subtle symptoms. The accessibility of sphygmomanometers that can detect AF, may play crucial roles in identifying asymptomatic patients. AViTA BPM63B is an automatic blood pressure (BP) monitor for atrial fibrillation detection. This study validated the performance of BPM63B for AF detection using two novel algorithms of time-domain analysis and frequency-domain analysis which evaluate multiple statistics. The study included 100 subject, with 47 participants being male (47%) and ages ranging from 24 to 89 years (mean ± SD: 59 ± 17 years). Each participant received three consecutive readings from the subject device and a 12-lead ECG assessment. The pulse wave data from subject device was analyzed using the two algorithms. The atrial fibrillation status thus determined was compared to the ECG results interpreted by a physician. Among the 100 participants, 52 patients had chronic atrial fibrillation, along with 48 outpatients exhibiting sinus rhythm or non-atrial fibrillation arrhythmias. Using the time-domain analysis method for atrial fibrillation detection, we achieved a sensitivity of 94.8% [95% confidence interval (CI), 90.08-97.75%] and a specificity of 98.6% (95% CI, 95.07-99.83%). Similarly, utilizing the frequency-domain analysis method resulted in a sensitivity of 91.6% (95% CI, 86.08-95.46%) and specificity of 94.4% (95% CI, 89.35-97.57%). These findings suggest that AViTA BPM63B, which integrates two novel algorithms for atrial fibrillation diagnosis, demonstrates high sensitivity and specificity. Utilizing the AViTA BPM63B for BP monitoring could aid in the early detection of atrial fibrillation among outpatients in cardiology clinics.

Radial artery pulse wave age-related assessment for diabetic patients based on multiple linear regression time domain analysis method

The global incidence of diabetes increases yearly. About 10 % of adults are affected. This study established a multiple linear regression (MLR) time domain analysis model of radial artery pulse wave characteristic parameters in CUN, GUAN and CHI based on traditional Chinese medicine (TCM) to assess diabetes. Pulse signals of diabetic subjects were collected by a pulse instrument. The locations of CUN, GUAN and CHI were determined by a TCM practitioner, and all pulse signals were normalized. Measurement data from 100 male and 100 female patients were used to establish a new time domain analysis method for extracting pulse wave characteristic parameters called equal pressure pulse transit time (EP-PTT). For these mentioned samples, the EP-PTT is different for male and female diabetic subjects, it was smaller for male diabetic subjects than those of female diabetic subjects. EP-PTT1 and EP-PTT6 are relevant to predicting age based on CUN, GUAN and CHI signals, which showed a linear negative correlation (P < 0.05). The EP-PTTi (i = 2, 3, 4) of female diabetic subjects are linearly correlated with age, and all of these are positively correlated (P < 0.05). These observations were clearly different from observations in healthy controls. The pulse waveform of CUN, GUAN and CHI of diabetic subjects can explore the relationship between the age of diabetic subjects and EP-PTT. The preliminary findings will provide foundational data for type 2 diabetes assessment based on CUN, GUAN and CHI pulse signals of radial artery, and the proposed new analysis method can be used for assessing type 2 diabetes.

Understanding stiffness degradation of composite helical springs with multi-braided layers under impact

Understanding stiffness degradation and developing suitable damage detection method for composite helical springs (CHSs) are important for their application and further development. In this study, a coupled plasticity-damage model for capturing stiffness degradation of CHSs with multi-braided layers (MBLs-CHS) is developed. Experimental results show that there is minor damage that only happens in the resin component of MBLs-CHS during impact. The element removal fraction in the simulation result is used to evaluate the damage severity, which is suggested to increase with impact energy (Ei) and decrease sequentially for CHSs with single, double, and triple braided layers (i.e., SCHS, DCHS, and TCHS). Specifically, damage severity of TCHS decreases by 51.3 % under 60 J impaction compared to that of SCHS. Finally, the time domain analysis method is introduced to monitor damage in real time. The amplitude intensity profiles under various Ei of CHSs have been fitted to predict the global stiffness degradation of CHSs in real time.

Efficient Verilog-A based time-domain variability analysis method for passive photonic integrated circuits

The performance of silicon photonic integrated circuits (PICs), especially wavelength filters, can be highly sensitive to variations in the fabrication process due to the large refractive index contrast of the silicon on insulator platform. This paper proposes an easy-to-implement and efficient time-domain variability analysis method for passive PICs. The method utilizes the polynomial chaos expansion technique to construct Verilog-A based models for estimating the statistical information of stochastic passive PICs. In comparison to existing methods, this approach is considerably easy to implement, efficient, and exhibits superior scalability, particularly as the numbers of ports and random parameters in the studied PICs increase. The technique is demonstrated via the time-domain variability analysis of a ring-resonator-based wavelength filter and a Mach-Zehnder interferometer-based demultiplexer filter.

A multi-energy load forecasting method based on complementary ensemble empirical model decomposition and composite evaluation factor reconstruction

Ensuring precise multi-energy load forecasting is crucial for the effective planning, management, and operation of Integrated Energy Systems (IES). This study proposes a novel multivariate load forecasting model based on time-series decomposition and reconstruction to handle the complex, high-dimensional multi-energy load data in IES and enhance forecasting accuracy. Initially, the model conducts a thorough correlation analysis and variable screening to minimize irrelevant data interference. It then applies denoising by decomposing the load sequence into modal components with distinct characteristics, using the complementary ensemble empirical mode decomposition (CEEMD). To overcome the unstable prediction accuracy inherent in time-domain decomposition methods, this study introduces an innovative composite evaluation factor (CEF) that reconstructs the modal components after considering their complexity, coupling, and frequency. The final predictions are generated using the proposed MTL-CNN-BiLSTM model, optimized with the attention mechanism. The results show that the proposed model significantly reduces error accumulation compared to traditional time-domain analysis methods, achieving a 37.40% reduction in average forecasting error and a 30.73% increase in forecasting efficiency.

Validating the accuracy of real-time phase-contrast MRI and quantifying the effects of free breathing on cerebrospinal fluid dynamics

BackgroundUnderstanding of the cerebrospinal fluid (CSF) circulation is essential for physiological studies and clinical diagnosis. Real-time phase contrast sequences (RT-PC) can quantify beat-to-beat CSF flow signals. However, the detailed effects of free-breathing on CSF parameters are not fully understood. This study aims to validate RT-PC’s accuracy by comparing it with the conventional phase-contrast sequence (CINE-PC) and quantify the effect of free-breathing on CSF parameters at the intracranial and extracranial levels using a time-domain multiparametric analysis method.MethodsThirty-six healthy participants underwent MRI in a 3T scanner for CSF oscillations quantification at the cervical spine (C2-C3) and Sylvian aqueduct, using CINE-PC and RT-PC. CINE-PC uses 32 velocity maps to represent dynamic CSF flow over an average cardiac cycle, while RT-PC continuously quantifies CSF flow over 45-seconds. Free-breathing signals were recorded from 25 participants. RT-PC signal was segmented into independent cardiac cycle flow curves (Qt) and reconstructed into an averaged Qt. To assess RT-PC’s accuracy, parameters such as segmented area, flow amplitude, and stroke volume (SV) of the reconstructed Qt from RT-PC were compared with those derived from the averaged Qt generated by CINE-PC. The breathing signal was used to categorize the Qt into expiratory or inspiratory phases, enabling the reconstruction of two Qt for inspiration and expiration. The breathing effects on various CSF parameters can be quantified by comparing these two reconstructed Qt.ResultsRT-PC overestimated CSF area (82.7% at aqueduct, 11.5% at C2-C3) compared to CINE-PC. Stroke volumes for CINE-PC were 615 mm³ (aqueduct) and 43 mm³ (spinal), and 581 mm³ (aqueduct) and 46 mm³ (spinal) for RT-PC. During thoracic pressure increase, spinal CSF net flow, flow amplitude, SV, and cardiac period increased by 6.3%, 6.8%, 14%, and 6%, respectively. Breathing effects on net flow showed a significant phase difference compared to the other parameters. Aqueduct-CSF flows were more affected by breathing than spinal-CSF.ConclusionsRT-PC accurately quantifies CSF oscillations in real-time and eliminates the need for cardiac synchronization, enabling the quantification of the cardiac and breathing components of CSF flow. This study quantifies the impact of free-breathing on CSF parameters, offering valuable physiological references for understanding the effects of breathing on CSF dynamics.

A Si IGBT/SiC MOSFET Hybrid Isolated Bidirectional DC–DC Converter for Reducing Losses and Costs of DC Solid State Transformer

The DC solid state transformer (DCSST) is a crucial component for connecting buses of different voltage levels in the DC distribution grid. This paper proposes a Si IGBT/SiC MOSFET hybrid isolated bidirectional DC–DC converter and an optimized modulation strategy (OMS) to reduce the losses and costs of DCSST. Based on the analysis of topology and operating principles, a duty-cycle modulation strategy is proposed and the converter is modeled by the time domain analysis (TDA) method. Through the analysis of switching characteristics, an optimization problem is established, which aims to reduce the conduction losses of switches while ensuring zero-voltage switching (ZVS) for all switches and low-current turn-off for IGBTs simultaneously. The optimization problem is solved by the augmented Lagrangian genetic algorithm (ALGA), and the OMS for the proposed converter is deduced. Finally, a 2 kW experimental prototype with the primary voltage of 405–495 V and the secondary voltage of 150 V is built to verify the effectiveness of the proposed topology and OMS. The switching costs of the proposed converter is reduced by 27.3% and the efficiency is improved by up to 4.04% compared to the existing method.

Time Domain Analysis of Ride Comfort and Energy Dissipation Characteristics of Automotive Vibration Proportional–Integral–Derivative Control

&lt;div&gt;A time domain analysis method of ride comfort and energy dissipation characteristics is proposed for automotive vibration proportional–integral–derivative (PID) control. A two-degrees-of-freedom single wheel model for automotive vibration control is established, and the conventional vibration response variables for ride comfort evaluation and the energy consumption vibration response variables for energy dissipation characteristics evaluation are determined, and the Routh stability criterion method was introduced to assess the impact of PID control on vehicle stability. The PID control parameters are tuned using the differential evolution algorithm, and to improve the algorithm’s adaptive ability, an adaptive operator is introduced, so that the mutation factor of differential evolution algorithm can change with the number of iterations. The PID control parameter optimization method presented in this article is versatile and can be used to optimize PID control parameters under different conditions. This article provides the results of PID control parameter optimization under different conditions. Based on PID control and its parameter tuning, a time domain solution method for two types of vibration response variables, their root mean square values, and the average power of energy consumption vibration of automotive vibration PID control is proposed. Two kinds of simulation test schemes are designed under urban driving conditions, which are commonly used Class B road and pulse road, with a commonly used vehicle speed of 60 km/h. The ride comfort and energy dissipation characteristics of passive suspension and PID control are compared. The results show that introducing energy consumption vibration response variables as a supplement to the conventional vibration response variables is beneficial for expanding the research and application scope of the automotive vibration and its control; with the sprung mass acceleration deviation as the control input, PID control can effectively improve the vehicle ride comfort, but it makes the vibration energy dissipation characteristics worse.&lt;/div&gt;

Fault Diagnosis of Dry Gas Seal Operation Status Based on Acoustic Emission Monitoring

A dedicated test bench is employed to record acoustic emission signals from dry gas seals under various operating conditions. Time-domain and frequency-domain analysis methods are utilized to process and analyze the acoustic emission signals during start/stop, stable operation, and two common fault states (end-face defects and compensation spring failure). Furthermore, feature recognition research is conducted. A method for identifying the operational states of seals (low-speed friction, gradual detachment, stable operation) based on the root mean square (RMS) was established, with transition points at speeds of 100 and 1000 RPM, respectively. Additionally, spectral analysis is conducted using Fourier transform to determine the frequency band of acoustic emission signals (240–320 kHz) generated during contact wear of dry gas seals. Investigation into two typical faults of dry gas seals reveals that the RMS value of the acoustic emission signal gradually increases with the rotational speed during the operation of dry gas seal end-face defects. This is attributed to the insufficient dynamic pressure effect on the end face, resulting in long-term wear and tear. When the dry gas seal compensates for spring failure, the RMS value of the acoustic emission signal initially increases, then decreases, and finally increases again as the speed increases. It reaches the stable operating inflection point when the end-face speed is 800 r/min.

Research on the Application of Intelligent Diagnosis of Major Equipment Failures in Coal Mines

Abstract Currently, the implementation of a coal mine production safety monitoring system, capable of real-time monitoring of the safety condition of large coal mine equipment and timely dispatch management, is crucial for the efficient and safe operation of coal mine enterprises. This paper designs the coal mine major equipment failure process based on the rolling bearing’s vibration mechanism, analyzes the major equipment’s failure signal using both time domain and frequency domain analysis methods, and employs the intelligent fuzzy control method to identify the major equipment failure. We have designed and practically applied a real-time, multi-threaded, and comprehensive fault diagnosis and prediction system for coal mine major equipment, combining information from coal mine safety, production, and operation. The results show that the normal state’s time-domain amplitude approximates (-0.2, 0.2), and the time-domain waveforms all display periodic shock signals when the bearing sustains damage. The faulty vibration amplitude of the inner ring is within 0.08 ms 2 and the faulty vibration amplitude of the outer ring is within 0.44 ms 2, and the diagnostic accuracy using the method of this paper reaches 97.2%. This study demonstrates the effectiveness of remote monitoring and fault analysis of major equipment in coal mines, which effectively improves the equipment start-up rate and ensures coal mine production safety.

High-precision Time-domain Analysis Method based on the Superposition Principle for CLLC Converter in above-resonant-frequency Mode

High-precision Time-domain Analysis Method based on the Superposition Principle for CLLC Converter in above-resonant-frequency Mode

Application of Impact Elastic Wave Method in Quality Inspection of Concrete Lining

As the main part of inter-basin water transfer project, water tunnel plays an important role in long-distance water conveyance. In water tunnel, the lining quality problem is one of the important potential safety hazards of the tunnel engineering. It is very necessary to detect the internal defects of concrete lining. In this paper, a multi-parameter comprehensive interpretation method based on impact elastic wave is proposed to quickly detect the internal defects of lining. The common offset time domain analysis method, frequency domain analysis method and two-dimension Rayleigh wave method are used for data processing. The detection method has the characteristics of single data acquisition and multi-parameter joint interpretation. The physical model of concrete lining is tested and compared with the result of GPR method to verify the accuracy of this method. The coring results show the reliability and stability of this method in practical application.

CFI-LFENet: Infusing cross-domain fusion image and lightweight feature enhanced network for fault diagnosis

Data-driven fault diagnosis has become a hot topic of research in recent years, due to its wide applicability, high accuracy, and ease of modeling. In data-driven fault diagnosis, feature extraction is usually performed through a combination of one-dimensional time domain or frequency domain analysis methods. However, the constraints of data format and diagnostic methods give rise to three primary issues: inadequate utilization, expression, and mining of fault features, thereby impeding the broader application of data-driven methods. This paper presents a fault diagnosis framework that integrates cross-domain fusion images and a lightweight feature-enhanced network to address these issues. We leverage the temporal and frequency features of raw time series data, transforming them into images. This approach not only offers a greater amount of fault information but also highlights the inherent features more prominently. In terms of diagnosis methods, a novel feature-enhanced network model is proposed. This model takes images generated by a cross-domain image fusion module as inputs and then goes through a customized feature extraction module, a feature fusion module, a feature enhancement module, and a classification module to achieve high-precision and fast fault diagnosis. The effectiveness of this framework is validated on two publicly available datasets. The results show that the average accuracy of this fault diagnosis framework can reach 100%, surpassing the findings of existing research. The experiments on noise resistance further showcase the superiority of the proposed framework. It is expected that the framework presented in this study will provide a new perspective and direction for fault diagnosis.

The Effects of Free Breathing on Cerebral Venous Flow: A Real-Time Phase Contrast MRI Study in Healthy Adults.

Quantifying the effects of free breathing on cerebral venous flow is crucial for understanding cerebral circulation mechanisms and clinical applications. Unlike conventional cine phase-contrast MRI sequences (CINE-PC), real-time phase-contrast MRI sequences (RT-PC) can provide a continuous beat-to-beat flow signal that makes it possible to quantify the effect of breathing on cerebral venous flow. In this study, we examined 28 healthy human participants, comprising of 14 males and 14 females. Blood flows in the right/left internal jugular veins in the extracranial plane and the superior sagittal sinus (SSS) and straight sinus in the intercranial plane were quantified using CINE-PC and RT-PC. The first objective of this study was to determine the accuracy of RT-PC in quantifying cerebral venous flow, relative to CINE-PC. The second, and main objective, was to quantify the effect of free breathing on cerebral venous flow, using a time-domain multiparameter analysis method. Our results showed that RT-PC can accurately quantify cerebral venous flow with a 2 × 2 mm2 spatial resolution and 75 ms/image time resolution. The mean flow rate, amplitude, stroke volume, and cardiac period of cerebral veins were significantly higher from the mid-end phase of expiration to the mid-end phase of inspiration. Breathing affected the mean flow rates in the jugular veins more than those in the SSS and straight sinus. Furthermore, the effects of free breathing on the flow rate of the left and right jugular veins were not synchronous. These new findings provide a useful reference for better understanding the mechanisms of cerebral circulation.

Post-earthquake Dynamics of Bridge Structures using New Particle Dampers – A Case Study of the Nujiang River Bridge

In this study, a new mechanical model, named particle damping mechanics model (PU_SPD), is proposed to study the damping problem of bridge structures. The model takes the Nujiang River Bridge as a case study, and explores the mechanism of force action by analyzing the time domain vibration characteristics and frequency domain of the excitation force, vibrating body (bridge structural properties) and particle damping. the PU_SPD model and its calculation method can intuitively and scientifically describe the damping dissipation characteristics of a vibrating beam under the action of particle damping, avoiding the tedious process of parameter iterative solution and improving the computational efficiency. In addition, the damping influence law of particle damping on the beam structure is derived through the analysis of transfer function and damping level. The study also proposes an optimal design method for PU_SPD damping parameters under dynamic loading of the bridge, and its performance parameters are analyzed and verified, and compared and validated with the time-domain analysis method. The results show that the PU_SPD mechanical model based on time-frequency domain analysis can intuitively reflect the damping dissipation mechanics with high accuracy, clear solution process and reasonable and accurate parameter optimization analysis method. PU_SPD has a wide frequency range, good effect and stability, and has a good prospect of application in engineering vibration and noise reduction.

Design and Hydrodynamic Performance Analysis of Offshore Multi-Module Floating Docks

This study presents a design scheme for a multi-module connected floating dock, comprising two configurations for the lower floating body: transverse and longitudinal floats. An articulated connection between the modules is also included. The hydrodynamic performance of the floating dock with these two configurations is compared and analyzed by taking the South China Sea as an example. Frequency and time-domain analysis methods are employed, considering the coupling between the mooring and the multi-module floating dock. The results indicate that, under the condition of both cross waves and oblique waves, the transverse float configuration exhibits superior motion response performance in all degrees of freedom compared to the longitudinal float configuration, particularly in terms of roll performance. Furthermore, the maximum mooring tension and connection structure load for the transverse float configuration are lower than those for the longitudinal float configuration, resulting in superior overall hydrodynamic performance.

Analysis of P-wave propagation in filled jointed rock mass with viscoelastic properties

Stress wave propagation in filled jointed rock mass is an important basis for the analysis of rock dynamic stability. The presence of small cracks in rock mass often causes the rock to exhibit viscoelastic behavior, resulting in the amplitude attenuation and time delay of the stress wave. In view of the incomplete understanding of stress wave propagation in viscoelastic media, this study presents an analysis on stress wave propagation in filled jointed rock mass with viscoelastic properties based on the time-domain recursive analysis method. By introducing the quality factors of stress wave in viscoelastic medium, the propagation equation of plane P-wave in filled jointed rock mass with viscoelasticity is established. Subsequently, the transmission and reflection characteristics of P-wave are accordingly analyzed. The results indicate that the transmission and reflection coefficients of P-wave through the filled joint decrease obviously due to the attenuation effect of rock viscoelasticity on wave amplitude, but the coefficients gradually stabilize as the quality factor increases. As the propagation distance of the P-wave increases in viscoelastic rock masses, the transmission and reflection coefficients decrease gradually. The normal stiffness of joint contact interface has a decisive influence on the wave propagation. Specifically, a higher normal stiffness leads to stronger transmission and poorer reflection. The larger the thickness of filled joint, the more obvious the attenuation of P-wave becomes. Additionally, the viscoelasticity of filling layer further aggravates the influence of joint thickness on the attenuation of P-wave. The study comprehensively takes into account the effect of viscoelasticity of both the rock mass and the filling layer on transmission and reflection of waves. The research results provide certain theoretical support for the dynamic response and stability analysis of rock mass containing structural planes.

Non-Contact Global Measurement of the Engine in Working Condition

Vibration measurements are essential for studying the dynamic properties of structures, as they can better capture the global characteristics of the structure. This paper proposes a three-dimensional measurement method based on projected structured light to address the challenge of measuring the vibration information of engine pipes during operation. By using the data obtained from this method and applying the time domain analysis method for modal analysis, the modal parameters of the engine under operating conditions can be obtained. The feasibility of this method is demonstrated by comparing it with different measurement methods, and it provides an effective solution for modal identification of engines under operating conditions.

Novel fluid typing method of NMR dual-TW logging in mixed-wet reservoirs

In mixed wetting reservoirs, the fluids typing is difficult by using nuclear magnetic resonance (NMR) logging. The data processing and interpretation method of NMR dual-waiting time (TW) activation faces serious challenges and the previous NMR time-domain analysis (TDA) of NMR dual-TW logging for water-wet condition is not applicable. The petrophysical characteristics under mixed-wet conditions was studied and the oil-wet factor was defined, and new NMR logging response equations was investigated and the echo train difference between long and short wait times were derived. The relaxation parameters of fluids and water saturation was finally calculated by the genetic algorithm. Therefore, a new improved TDA method was proposed for mixed-wet reservoirs. To verify the method, a petrophysical model was set and some simulations proved it accurate. A case study from Chang 8, Ordos Basin, China, was studied, and the oil saturation and volume in the flushed zone were calculated. From the oil-testing results, two cross-plots for fluid typing were constructed based on the calculated oil saturation in flushed zone, T2 geomean difference of dual-TW NMR logging. The practical application shows that the novel TDA method of NMR dual-TW logging for mixed-wet reservoirs is efficient for the fluid identification.

Analysis of the acceleration of the multi-level vibration of the tank as firing

Aiming at the system level vibration problem caused by the strong impact load during the tank firing, the tank is divided into several levels according to the vibration transmission path, such as barrel, cradle, turret, seat ring, car body and wheel. The multi-level vibration response characteristics of the tank during firing are obtained by arranging acceleration sensors at the typical positions of each level. Based on the time domain analysis method, the vibration acceleration at the positions of cradle, turret, seat ring, car body and wheel is analyzed, and the pulse amplitude and pulse time of vibration acceleration at each level are obtained. The analysis shows that under the action of firing load, the acceleration amplitude of muzzle, cradle, turret, seat ring, vehicle body and wheel decreases in turn. And the peak acceleration at the muzzle position is the largest, about 1400g, and the peak acceleration at the wheel position is the smallest, about 0.6g. The results will provide support for obtaining the multi-level vibration characteristics of the tank under the fire load and revealing the vibration transmission law of the tank under the fire load.