Fourier Transform Method Research Articles

LFformer: An improved Transformer model for wind power prediction.

Wind power forecasting has complex nonlinear features and behavioral patterns across time scales, which is a severe test for traditional forecasting techniques. To address the multi-scale problem in wind power forecasting, this paper innovatively proposes an ultra-short-term forecasting model LFformer based on Legendre-Fourier, which firstly focuses on the important information in the input sequences by using the encoder-decoder architecture, and then scales the range of the original data with the Devlin normalization method, and then utilizes the Legendre polynomials to The data sequence is projected into a bounded dimensional space, the historical data is compressed using feature representation, then feature selection is performed using the low-rank approximation method of Fourier Transform, the prediction is inputted into the multilayer perceptron through the multi-scale mixing mechanism, and finally the results are outputted after back-normalization. The experimental results show that compared with the existing prediction methods, the model realizes the improvement of prediction accuracy and stability, especially in the ultra-short-term prediction scenario, with obvious advantages. The research results are not only valuable for improving the overall operational efficiency of the wind power system, but also help to enhance the stable operation of the power grid, which provides strong technical support and guarantee for wind power enterprises to improve the competitiveness of bidding for Internet access in the power market competition.

Weak signal ultrafast interrogation of a micro-nano FBG probe sensor based on the hybrid amplified dispersion Fourier-transform method

To elucidate the thermal transport mechanisms at interfaces in micro- and nanoscale electronic devices, real-time monitoring of temperature variations at the microscopic and nanoscopic levels is crucial. Micro-nano fiber Bragg grating (FBG) sensors have been demonstrated as effective in-situ optical temperature probes for measuring local temperatures. Time-stretch dispersion Fourier transform (TS-DFT) that enables fast, continuous, single-shot measurements in optical sensing has been integrated with a micro-nano FBG probe (FBGP) for local temperature sensing. However, its temperature sensitivity and interrogation resolution are limited by the detection sensitivity. In this paper, we propose a hybrid amplified dispersion Fourier transform (ADFT) method to achieve ultrafast interrogation of FBGP’s weak signal. Thanks to the combined effect of TS-DFT and hybrid optical amplification, the reflection signal of the FBGP is amplified, and the wavelength shift of the FBGP sensor is converted to a temporal spacing change between two dispersed pulses through dispersion-induced wavelength-to-time mapping. The proposed method uses a homemade dissipative soliton mode-locked laser as the light source. The hybrid optical amplification technique comprises a L-band erbium-doped fiber amplifier and a distributed Raman amplifier. Their noise figure and net gain for the FBGP are 4.81 dB and 15.93 dB, respectively. In addition, the temperature calibration experiments show that a sampling rate of 51.43 MHz and the maximum temperature measurement error of 1.98°C are achieved within the temperature range of 20.3°C to 97°C. The stability of the net gain provided by the hybrid ADFT system is demonstrated by the coefficient of variation, which ranges from 2.22% to 2.95% in the peak voltage signal of the FBGP. This approach applies to scenarios requiring the handling of weak optical signals, particularly in temperature measurement at the micro-nano scale.

Analysis of vortex induced vibration on the hundred-meter wind turbine blade based on CFD and FEM

Abstract Along the development of wind turbine blade toward large size and light weight, the length of blade running-now has come to the level of hundred-meter, while the structure of blade trends to be flexible. During the shutdown conditions, blades are affected by wake vortex from different inflow speed and angle, which often induce blade vibration. It seriously affects the safety and service life of wind turbines, even may cause blade breakage accident. This paper focused on the vortex induced vibration on the hundred-meter wind turbine blade. Based on the Computational Fluid Dynamics (CFD) transient method, the wake flow field of three relative thickness aerofoils has been simulated under different inflow speed and angle. The distribution of vorticity has been compared. Based on the Fast Fourier Transform (FFT) method, the frequency of wake vortex has been analysed from the pressure pulsation, compared with the natural frequency of this hundred-meter blade calculated by the Finite Element Method (FEM). This result may be regarded as a simulation support to avoid vortex induced vibration of hundred-meter wind turbine blade.

Cross-Domain Object Detection through Consistent and Contrastive Teacher with Fourier Transform

The teacher–student framework has been employed in unsupervised domain adaptation, which transfers knowledge learned from a labeled source domain to an unlabeled target domain. However, this framework suffers from two serious challenges: the domain gap, causing performance degradation, and noisy teacher pseudo-labels, which tend to mislead students. In this paper, we propose a Consistent and Contrastive Teacher with Fourier Transform (CCTF) method to address these challenges for high-performance cross-domain object detection. To mitigate the negative impact of domain shifts, we use the Fourier transform to exchange the low-frequency components of the source and target domain images, replacing the source domain inputs with the transformed image, thereby reducing domain gaps. In addition, we encourage the localization and classification branches of the teacher to make consistent predictions to minimize the noise in the generated pseudo-labels. Finally, contrastive learning is employed to resist the impact of residual noise in pseudo-labels. After extensive experiments, we show that our method achieves the best performance. For example, our model outperforms previous methods by 3.0% on FoggyCityscapes.

Vibration Characteristics and Mesoscopic State Evolution of Ballasted Track During Dynamic Stabilizing Operation

Dynamic stabilization of large machines is necessary procedures before the commencement of operations railway lines that are newly built. However, limited or no studies have been carried out to reveal the operational mechanism from the vibration transfer characteristics of ballasted track subjected to excitation by stabilizing machines. The focus of this study is to solve this shortcoming. First, a typical new railway line was selected to test the dynamic response of the ballasted track during stabilizing operation, and then a stabilizing machine-ballasted track model was established with the help of the DEM-MBD coupling method. And the biaxial vibration accelerometers were inserted at various locations in the ballast bed to monitor the evolution of the vibration level on real-time basis. The influence of the stabilizing operation process on the vibration transmission and attenuation characteristics of sleeper and ballast bed was explored using wavelet analysis and Fast Fourier Transform method. The vibration absorption capacity and energy dissipation characteristics of the ballasted track under various stabilizing frequencies were analyzed. At the same time, the contact state and movement posture of ballast particles during the stabilizing operation were explored. Results showed that the vertical vibration attenuation rate of the slope toe of the ballast bed after the first stabilizing machine pass is 92.32%, while the vertical vibration attenuation rate of the second stabilizing machine is reduced by 3.14%. The second stabilizing machine can cause a large lateral movement of the ballast at the bottom of the sleeper. Under the excitation of 25[Formula: see text]Hz stabilizing frequency, it was observed that, the vibration absorption capacity of the ballast bed at the bottom of the sleeper is high, the vibration level at the ballast bed slope is low, and the stability is better. This is the optimal frequency for the stable operation of the new railway. This study can provide theoretical support for the establishment of the internal correlation mechanism between the vibration characteristics of stabilizing machines and the mechanical state of the ballast bed.

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In this article, we investigated the solitary wave solutions of the KdV–mKdV equation using Hirota’s bilinear method. Closed-form analytical single and multiple solitary wave solutions were obtained. Through qualitative methods and the analysis of solitary waveforms, we discovered that in addition to sech-type solitary waves, the system also contains Sech2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{Sech}^{2}$$\\end{document}-type solitary waves. By employing the trial functions method, we obtained a single Sech2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{Sech}^{2}$$\\end{document}-type solitary wave and verified its existence and stability using the split-Step Fourier Transform method. Furthermore, we use the collision of two Sech2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{Sech}^{2}$$\\end{document}-type single solitary waves to excite a stable Sech2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{Sech}^{2}$$\\end{document}-type double solitary wave. Similarly, we excite a stable triple solitary wave with three Sech2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{Sech}^{2}$$\\end{document}-type single solitary waves. This method can also be used to excite stable multiple solitary waves. It is shown that these solitary wave solutions enrich the dynamic behavior of the KdV–mKdV equation and provide methods for solving Sech2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ ext{Sech}^{2}$$\\end{document}-type solitary waves, which hold significant theoretical value.

Acceleration of a wave-structure interaction solver by the Parareal method

Potential flow theory-based solvers are commonly used in ocean engineering to investigate the interactions between ocean waves and floating bodies. Depending on assumptions, several methods have been proposed. Among them, the Weak-Scatterer method is an interesting trade-off in the sense that this approach is not limited in theory by the small wave amplitudes and small body motions assumptions of linear methods. Moreover, this approach is in practice more stable than the fully non-linear methods. An implementation of the Weak-Scatterer method is the WS-CN code (Letournel, 2015; Chauvigné, 2016; Wuillaume, 2019).The computational time of the WS-CN code which is considered in the present study is relatively long for engineering purposes. In order to reduce it, the present paper presents an implementation of the Parareal method in the WS-CN code. The Parareal method is an algorithm for parallelizing a simulation in time that can accelerate the complete simulation (Lions, 2001) . This is a key difference in comparison to other acceleration techniques which have been studied in the literature (e.g. the Fast Multipole Method (FMM), the precorrected Fast Fourier Transform (pFFT) method, … ). To the authors’ knowledge, the present study is the first to couple the Parareal method to a potential flow theory-based wave-structure interaction solver. It is shown that the method can significantly reduce the computational time for small wave steepness, but that the performance decreases rapidly with increasing steepness.

Research on Sea Trial Techniques for Motion Responses of HDPE Floating Rafts Used in Aquaculture

The innovative aquaculture equipment known as high-density polyethylene (HDPE) floating rafts has gained popularity among fishermen in the southeast coastal regions of China. Compared to deep-water anti-wave fish cages, the construction costs of HDPE floating rafts are 50% to 75% less. There is a dearth of comprehensive publicly available records of HDPE floating rafts sea trial data, despite substantial numerical studies on the motion response of aquaculture fish cages and scale model experiments under controlled-wave conditions. This study involves sea trial techniques under operational and extreme environmental conditions for motion responses of HDPE floating rafts, presents a comprehensive procedure for sea trials of HDPE floating rafts, summarizes the issues encountered during the trials, and suggests solutions. Using MATLAB for independent programming, motion videos and photos collected from the sea trials are processed for image capture, yielding the original time history curve of vertical displacement. Based on the sea trials’ data, including motion displacement, acceleration, mooring line force, overall deformation patterns, and current and wave data, recommendations are provided for the design and layout of HDPE floating rafts. Based on the Fast Fourier Transform (FFT) method for spectral analysis, the influence of interference items on the observational data is eliminated; the rationality of the observational data is verified in conjunction with the results of the Gabor Transform. This study offers a scientific analytical method for the structural design and safe operation of HDPE floating rafts and provides a reference for subsequent numerical simulations.

Simultaneous PIV/LIF Measurements Of Velocity And Oxygen In An Advecting Air-Water Channel Flow

We investigate oxygen transfer across an air-water interface using an integrated Particle Image Velocimetry (PIV) and Laser-Induced Fluorescence (LIF) system. This setup allows for the simultaneous measurement of velocity and dissolved oxygen (DO) concentration fields, alongside the visualization of the air-water interface. The imaging process begins with zero DO concentration and continues until oxygen saturation in the water is achieved. Calibration of the oxygen LIF intensity field is performed using these images, benchmarked against measurements from an optical oxygen point probe, to ensure accurate conversion to a physically relevant unit. The air channel generates an air flow with a center-line mean velocity of 8.84 m/s, corresponding to a Taylor Reynolds number of 100. This high-velocity air flow results in the formation of wavy structures on the water interface creating situations similar to those found in nature (such as rivers and oceans). The wavy structures create reflections from the air-water interface; these reflections are mitigated during post-processing using a Wavelet-Fast Fourier Transform (W-FFT) method to remove high intensity noise. Additionally, the wind shear generated by the air flow induces high turbulence intensity and vortices near the air-water interface, significantly enhancing the dissolution of oxygen into the water. This turbulence and the associated vortical structures play a crucial role in the mixing process and the overall oxygen transfer efficiency. The study presents instantaneous dissolved oxygen structures overlapped with velocity structures in a flow with deformable interface, providing some insights into the oxygen transfer and mixing processes.

Verification of the AIS service availability model based on dynamic data streams recorded from three receiving stations in the Polish coastal area

The reliability aspects of the operation of radio navigation systems constitute a crucial element for the safety of maritime navigation.. Technological progress in ship traffic monitoring is achieved through the design of ship systems and shore infrastructure equipped with Automatic Identification System (AIS) devices. One of the issues with AIS operation is the limited availability of the service in the form of data streams with an extended data age recorded on the receiving side. Another problem is the emission and reception by ships of incomplete positional reports without navigational parameters. Such situations render the system operationally unfit in terms of processed information. Therefore, it is essential to investigate the operational characteristics of radio navigation systems and develop tools to monitor the AIS service status on the receiving side. This article presents the development of a model for the availability of an AIS for vessels based on the determined mean time of the occurrence of incomplete navigation parameter values in AIS messages and the results of research in the domain of time and frequency using a mathematical method of the Fast Fourier Transform (FFT). The study results refer to six basic navigation parameters and show a varying service availability factor for the navigation parameters under study, i.e. the latitude (LAT), longitude (LON), speed over ground (SOG), course over ground (COG), heading (HDT), and the rate of turn (ROT). The data recorded by three receiving AIS stations on the Polish coast, i.e. PLKOL, PLSZZ, and PLSWI, were used as a key source of practical knowledge on the limitations of the AIS service availability. The experiment observed interruptions in the regular transmission of data from navigation equipment in the AIS service operational zone. As a result, the functional relationship was described based on the spectral analysis of the frequency of occurrence of times between the service repair (Time To Repair, TTR), and the model was proposed to be applied to the study of other variables. The presented model is a tool that allows for improving the monitoring of vessel traffic in terms of reliability, which directly affects the improvement of maritime traffic safety.

A regional approach for high-resolution gravity anomaly recovery from full airborne gravity gradient tensor

SUMMARY A regional approach is developed for high-resolution gravity anomaly recovery from the full airborne gravity gradient tensor (GGT) based on the radial basis function (RBF) technique. The analytical expressions that link the full GGT to the gravity anomaly based on Poisson wavelets are developed, where the closed formulae of the associated derivatives of Poisson wavelets are deduced. Based on this approach, the gravity anomalies at a mean resolution of ∼0.15 km over the Kauring Test Range in Australia are recovered by using the local airborne GGT. The results show that the solution computed from the vertical component provides the best quality when a single component is used, whereas the model computed from the curvature component performs the worst. Moreover, the incorporation of two components magnifies the gravity anomalies and further improves the fit with the terrestrial and airborne gravity data, compared with the solutions computed from individual components. However, the solutions calculated by additionally merging one or more components provide comparable qualities with the models calculated by fusing two components only. Finally, the solution is computed by merging the full airborne GGT, and the standard deviation of the misfits against the terrestrial gravity data is 0.788 mGal. Further comparisons with the Fourier transformation and equivalent source method demonstrate that the proposed approach has slightly better performance. The proposed method is numerically efficient and offers a better data adaptation, which is useful for high-resolution gravity data recovery in managing huge number of gravity gradient data.

Dual grid energy management strategy for electric vehicles in hybrid microgrid utilizing matrix pencil method

Abstract This study introduces a cutting-edge Matrix Pencil-based Dual Grid Energy Management System (MP-DEMS) aimed at seamlessly integrating electric vehicles (EVs) into power grids while enhancing power quality (PQ) and reliability (PR). Operating within an AC-DC hybrid microgrid (HMG) framework, the MP-DEMS reduces the necessity for additional conversion devices, simplifying the integration of EVs and batteries. The core of the proposed DEMS comprises three key modules: the Wind Energy Management Module (WEMS), Smart Storage and EV Power Coordination (SS-EVPC), and Coordinated Power Conversion Control (CPCC). These modules work together to optimize energy usage, leverage renewable sources effectively, and manage EV charging/discharging schedules to minimize grid impact. An innovative aspect of the MP-DEMS is its use of Matrix Pencil-based techniques, offering several advantages over traditional Discrete Fourier Transform (DFT) methods. These advantages include swift dynamic response, resilience to voltage variations, and precise voltage phase estimation. Software simulations and Hardware-in-the-Loop (HIL-402) testing validate the efficacy of the MP-DEMS approach, showcasing enhanced power transfer capabilities, improved harmonic performance, and superior voltage/frequency regulation within EV-HMS applications. Overall, the MP-DEMS presents a promising solution for advancing the integration of EVs into microgrid systems, contributing to a more sustainable and reliable energy future.

Stochastic approach to a delayed in-host model of DENV transmission

Motivation. The immune response to the viral transmission experiences delays due to diverse biological factors and is affected by several factors. These include infection rate, rate of apoptosis and impact of the antibody-virus complex which exhibit unpredictable nature in a random environment. Objective. The main goal is to examine the impact of noise terms, introduced into every state variable, on a delayed in-host model of viral transmission. Methodology. To determine the intensity fluctuations and variances of all concerned state variables in the stochastic delayed model, which includes a constant delay and Gaussian white noise, the Fourier transformation method is employed. Results and Conclusions. The limiting value of the delay parameter is derived explicitly as well as numerically. The system experiences Hopf bifurcation, whenever the delay parameter crosses the limiting value which is shown graphically. The intensities and variances of different cells and virus populations are derived and the values are computed numerically. As the delay increases, the level of viremia decreases while other parameters maintain fixed values. The outcomes of data sensitivity, shown in graphical form, indicate that the transmission rate and supply rate of viruses are highly sensitive. Our findings suggest that the presence of noise causes fluctuations in the delayed model, leading to a noticeable impact on the transmission of the virus.

A Study on the Time-Frequency Characteristics of Electromagnetic Radiation Signals during Concrete Cracking

At the moment of rupture, brittle materials such as concrete, coal, and rocks experience a sudden stress change that generates oscillating positive and negative charges on the crack surfaces, resulting in the emission of electromagnetic radiation (EMR) signals. While extensive investigations have focused on the EMR signals produced during the fracturing of coal and rocks, limited attention has been given to the signals arising from concrete cracking. Previous studies have predominantly concentrated on amplitude or frequency domain analysis, lacking a comprehensive exploration of the time-frequency domain characteristics of electromagnetic signals. In this study, various magnetic field sensors capable of collecting frequencies ranging from 50Hz to 50kHz are developed. A laboratory testing platform for concrete cracking is established with the utilization of data acquisition equipment and a rock point load tester. The EMR signals are subjected to time-frequency domain analysis using Short-Time Fourier Transform (STFT) methods. The study explores the relationship between the time-frequency domain characteristics of EMR signals and concrete dimensions, as well as the instantaneous stress drop at the moment of fracture. Experimental findings reveal that the dominant frequency of EMR signals generated during concrete cracking is in the low-frequency range. As the instantaneous stress drop at the moment of fracture increases, the frequency of the EMR signals shifts towards higher frequencies and the signals around 10kHz has a longer duration. When the frequency of EMR signals is lower than 20kHz, larger concrete dimensions result in greater stress drops at the moment of fracture, leading to higher intensity EMR signals. Utilizing the EMR characteristics of concrete cracking holds promise for monitoring the safety and stability of concrete structures.

Fractional Fourier-transform off-axis digital holographic imaging

A fractional Fourier-transform digital holographic imaging method with resolution enhancement features is presented. In an optical configuration, an extended fractional Fourier-transform optical setup is set in the object arm of an off-axis digital holographic recording system to record a fractional Fourier-transform hologram via the optical interference of the fractional Fourier-transform wavefront of an object wave with a reference wave. For reconstruction imaging, the reconstruction approach for fractional Fourier-transform holograms is given. In the experiment, the fractional Fourier-transform digital holograms are recorded under the different recording parameters, and their amplitude images are effectively reconstructed. The imaging results demonstrate that the reconstruction-imaging resolution of fractional-order Fourier-transform holograms is obviously enhanced compared to that of conventional image-plane holograms. The presented fractional Fourier-transform digital holographic imaging with resolution enhancement and optical configuration flexibility provides, to our knowledge, a novel way for off-axis digital holographic imaging.

Does cardiovascular autonomic modulation correspond to the increase in dim-light onset of melatonin? A preliminary analysis

Introduction: The endogenous circadian system promotes the rise in melatonin approximately every 24 hours. In the laboratory, dim light melatonin onset (DLMO) is used as the gold standard method to assess circadian phase. Exogenous melatonin affects cardiac sympathovagal balance and vasomotor sympathetic modulation. Whether or not the endogenous increase in melatonin corresponds to changes in cardiovascular autonomic modulation is unclear. Objective: To evaluate if the timing of DLMO corresponds to the timing of changes in cardiovascular autonomic indices. Methods: Five healthy adults (3 females, age 23.8±SD1.8 y) completed a minimum of four nights of sleep regularization by maintaining a self-selected 8h in bed each night before the experiment. The day after regularization, they reported to the laboratory ~8 hours before bedtime. Measurements for melatonin and cardiovascular autonomic modulation started 6 hours before bedtime and continued 1 hour after. Saliva samples were collected every 30 minutes. At the end of every hour, 10 minutes of continuous R-R intervals (R-R) and systolic blood pressure (SBP) were recorded via electrocardiogram and beat-to-beat finger photoplethysmography, respectively. As currently established, DLMO was defined as the interpolated time for melatonin increase over 3pg/ml. Cardiovascular autonomic indexes were run through CardioSeries v.2 to create a temporal series for R-R interval and systolic blood pressure. Cardiac autonomic modulation was assessed by applying the spectral analysis using the fast Fourier transformation method and time domain analysis of heart rate variability (HRV) and spectral analysis of blood pressure variability (BPV). For each autonomic index, data were plotted and fitted with a segmental linear regression to reveal the intercept of the two segments to define the autonomic onset (AO). A paired t-test compared the difference between DLMO and AO times. Bland-Altman plots with a 95% limit of agreement (LOA) identified the distribution of differences between the methods. Additionally, a one-sample t-test compared the differences between methods to a fixed time clock range. Data are shown as mean ± SD and significance was set as p<0.05. Results: AO time calculated for all indexes from HRV and BPV were not statistically different compared to DLMO time (R-R: +16±86 mins, P=0.70; root mean square of successive differences (RMSSD): -20±91 mins, P=0.67; low frequency (LF) nu: +29±52 mins, P=0.74; high frequency (HF) nu: -43±91 mins, P=0.23; LFHF: -26±73 mins, P=0.47; SBP: -14±104 mins, P=0.78; LFSBP: -6±107 mins, P=0.90). The Bland Altman plots did not identify any systematic difference between AO and DLMO times. The smallest difference was LFnu with a LOA 95% from -73 to +131 minutes, while the largest difference was LFSBP with LOA 95% from -217 to +204 minutes. Additionally, the difference between DLMO and AO LFnu times (LFnu: +29±52) was statistically similar from -36 to +95 minutes. Conclusion: In young healthy adults, our preliminary data shows that AO times of cardiovascular autonomic indexes correspond to salivary DLMO. A larger dataset with more frequent simultaneous measurements of melatonin and cardiovascular autonomic modulation are essential to confirm our preliminary findings. Medical Research Foundation of Oregon, OHSU OFDIR, R01HL163232. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Research on Maximum Power Control of Direct-Drive Wave Power Generation Device Based on BP Neural Network PID Method

Ocean wave energy is a new type of clean energy. To improve the power generation and wave energy conversion efficiency of the direct-drive wave power generation system, by addressing the issue of large output errors and poor system stability commonly associated with the currently used PID (proportional, integral, and derivative) control methods, this paper proposes a maximum power control method based on BP (back propagation) neural network PID control. Combined with Kalman filtering, this method not only achieves maximum power tracking but also reduces output ripple and tracking error, thereby enhancing the system’s control quality. This study uses a permanent magnet linear generator as the power generation device, establishes a system dynamics model, and predicts the main frequency of irregular waves through the Fast Fourier Transform method. It designs a desired current tracking curve that meets the maximum power strategy. On this basis, a comparative analysis of the control accuracy and stability of three control methods is conducted. The simulation results show that the BP neural network PID control method improves power generation and exhibits better accuracy and stability.

High space–time bandwidth product imaging in low coherence quantitative phase microscopy

Current low coherence quantitative phase microscopy (LC-QPM) systems suffer from either reduced field of view (FoV) or reduced temporal resolution due to the short temporal coherence (TC) length of the light source. Here, we propose a hybrid, experimental and numerical approach to address this core problem associated with LC-QPM. We demonstrate high spatial resolution and high phase sensitivity in LC-QPM at high temporal resolution. High space–time bandwidth product is achieved by employing incoherent light source for sample illumination in QPM to increase the spatial resolution and single-shot Hilbert spiral transform (HST) based phase recovery algorithm to enhance the temporal resolution without sacrificing spatial resolution during the reconstruction steps. The high spatial phase sensitivity comes by default due to the use of incoherent light source in QPM which has low temporal coherence length and does not generate speckle noise and coherent noise. The spatial resolution achieved by the HST is slightly inferior to the temporal phase-shifting (TPS) method when tested on a specimen but surpasses that of the single-shot Fourier transform (FT) based phase recovery method. Contrary to HST method, FT method requires high density fringes for lossless phase recovery, which is difficult to achieve in LC-QPM over entire FoV. Consequently, integration of HST algorithm with LC-QPM system makes an attractive route. Here, we demonstrate scalable FoV and resolution in single-shot LC-QPM and experimentally corroborate it on a test object and on both live and fixed biological specimen such as MEF, U2OS and human red blood cells (RBCs). LC-QPM system with HST reconstruction offer high-speed single-shot QPM imaging at high phase sensitivity and high spatial resolution enabling us to study sub-cellular dynamic inside U2OS for extended duration (3 h) and observe high-speed (50 fps) dynamics of human RBCs. The experimental results validate the effectiveness of the present approach and will open new avenues in the domain of biomedical imaging in the future.

Decoding Stress with Computer Vision-Based Approach Using Audio Signals for Psychological Event Identification during COVID-19

Interpreting psychological events can be costly and quite complex. It is simple to translate such experiences into a person's spoken and nonverbal cues. The suggested model investigates a computer vision-based method for using an individual's audio signal to identify stressful psychological events. Different people's input speech signals are recorded and compared to the common questionnaire. A series of inquiries pertaining to the second stage of COVID-19 events are included in the questionnaire set. Through additional processing, these speech signals are converted into frequency components by means of the Fast Fourier transformation (FFT) method. A long short-term memory module processes each frequency component and produces temporal information from each frequency band. The features of speech signals are extracted into the temporal frames by this module. The VGG 16 algorithm is used to further classify each temporal frame into stress and un-stress classes. A classifier with 16 layers of architecture is called VGG 16. A feed-forward convolutional neural network called VGG 16 is used to divide the vast array of speech signal features into classes: stressed and unstressed. The proposed model attempts to recognize speech signals as stress indicators. A standard set of questionnaires with a series of interrogation-style questions has been used to develop the stress symptoms in an individual's mind. The audio signals generated by each person's responses are recorded and subsequently analyzed for stress and un-stress classes. The proposed model was able to identify stress in speech signals with 98% accuracy. The time and cost implications of the suggested model are relevant. Medical research is typically costly and time-consuming.LSTM; VGG 16; CNN model; data preprocessing; speech signal.

High-Efficiency Dynamic Three-Dimensional Topography Measurement Using the Phase Shift Generation Method

In the fringe projection profilometry (FPP), the traditional phase-shifting (TPS) algorithm and the Fourier transform (FT) algorithm are beset with a conundrum where measurement efficiency and conflicts with measurement accuracy, thereby limiting their application in dynamic three-dimensional (3D) measurements. Here, we propose a phase shift generation (PSG) method, which acquires the sinusoidal fringes by sparse sampling and reconstructs the complete phase-shifting sequence by generating the missing fringes with superimposed coupling of adjacent fringes. According to our proposed PSG method in which the sinusoidal fringe sequence size is about half of the TPS method, meaning that the PSG method will be timesaving in the phase-shifting sequence sampling process. Moreover, because of the utilization of multiframe fringes, our PSG method allows for a more accurate measurement than the FT method. Both simulation and experimental results demonstrate that our proposed PSG method can well balance the measurement accuracy and efficiency with a lower sampling rate, bearing a great potential to be applied in both scientific and industrial areas.