Frequency Modulation Research Articles

Floating-point photonic iterative solver demonstrated for Newton–Raphson method

Though photonic computing systems offer advantages in speed, scalability, and power consumption, they often have a limited dynamic encoding range due to low signal-to-noise ratios. Compared to digital floating-point encoding, photonic fixed-point encoding limits the precision of photonic computing when applied to scientific problems. In the case of iterative algorithms such as those commonly applied in machine learning or differential equation solvers, techniques like precision decomposition and residue iteration can be applied to increase accuracy at a greater computing cost. However, the analog nature of photonic symbols allows for modulation of both amplitude and frequency, opening the possibility of encoding both the significand and exponent of floating-point values on photonic computing systems to expand the dynamic range without expending additional energy. With appropriate schema, element-wise floating-point multiplication can be performed intrinsically through the interference of light. Herein, we present a method for configurable, signed, floating-point encoding and multiplication on a limited precision photonic primitive consisting of a directly modulated Mach–Zehnder interferometer. We demonstrate this method using Newton's method to find the Golden Ratio within ±0.11%, with six-level exponent encoding for a signed trinary digit-equivalent significand, corresponding to an effective increase of 243× in the photonic primitive's dynamic range.

A RANDOMIZED CARRIER-BASED DISCONTINUOUS PULSE WIDTH MODULATION STRATEGY FOR NEUTRAL POINT CLAMPED THREE-LEVEL INVERTER

This article introduces a novel approach called randomized carrier-based discontinuous pulse width modulation (RCDPWM) to address the challenge of mitigating both low-order and high-order harmonics concentrated at the switching frequency and its integer multiples in the output voltage and current of a three-level inverter. The proposed strategy reduces switching losses and a wide dispersion of voltage and current harmonics with significantly smaller amplitudes by integrating features from discontinuous and randomized PWM methods. This characteristic proves beneficial for enhancing efficiency and electromagnetic compatibility. The RCDPWM strategy involves three schemes: two simple schemes (one random parameter), randomized pulse position modulation (RPP-DPWM) and randomized carrier frequency modulation (RCF-DPWM), and a dual scheme combining the two previous ones (RPPRCF-DPWM). Power spectral density (PSD) is used to assess the effectiveness of the proposed strategy in quantitatively analyzing the harmonic dispersion degree. The results demonstrate that the proposed RCDPWM strategy significantly expands harmonic clusters around the switching frequency, reducing its intensity. The spectrum analysis revealed that the RPPRCF-DPWM scheme is the most effective in spreading the output voltage and current spectrum compared to simple schemes (RPP-DPWM and RCF-DPWM).

Analysis on the vibration signals of a novel double-disc crack rotor-bearing system with single defect in inner race

Previous studies have paid little attention to the dynamic modeling of multi-fault systems with both bearing defect and cracked rotor. In the current research, a double-disc rotor model with a breathing crack and fault bearing was established using the finite element method (FEM). The dual-impulse phenomenon associated with inner race defect was addressed as a time-varying external excitation. The effects of varying crack depths and inner race spall lengths were further investigated. The maximum error between simulation and experiment was found to be less than 5% for the dual-impulse time spacing. The calculated results indicate that the inner race defect causes a slight increase in the rotational frequency frotor and 2frotor, followed by a decrease in the 3frotor at low speeds, as observed using Fast Fourier Transform (FFT) and Short-Time Fourier Transform (STFT). The influence of changes in crack depth is greater than the bearing defect in the system, a finding that is also confirmed at 1/2 critical speed. The phenomenon of frequency modulation observed in the simulation was also verified experimentally. The ball passing frequency on inner raceway fBPFI, frotor and mixed frequency components can be used to distinguish whether there is inner race defect.

A distributed PD detection method for high voltage cables based on high precision clock synchronization

Partial discharge (PD) is a crucial cause of high voltage (HV) cable failures. Detecting and locating PD efficiently and effectively is paramount for HV cable maintenance. However, the attenuation of the PD signal after long-distance propagation makes it challenging to identify. This paper presents a distributed PD detection method that significantly reduces the propagation distance of PD signals before the sensor captures them. The technique uses the time-of-arrival to locate PD, whose localization accuracy is directly linked to the clock synchronization (CS) accuracy. CS between different sensors is achieved through three times interactions of the CS signal. The linear frequency modulation (LFM) signal is selected as the CS signal, which can generate a significant gain after pulse compression. It ensures that the CS signal can be effectively recognized after the attenuation of long-distance propagation. The paper also introduces a signal discrimination method based on the short-time Fourier transform that eliminates the influence of the LFM signal on PD identification. The cableless CS method makes it easier to set up before the onsite test. A prototype was implemented and tested. The CS accuracy was measured within 4 ns in the laboratory. An onsite test was carried out to evaluate the performance of the distributed PD detection system. A defect was found at a joint location, which was also confirmed by an additional ultrasonic PD test.

Photonic-assisted generation of fast switchable multi-format LFM waveforms with a tuned bandwidth for a joint radar-communication system

A photonic-assisted generation scheme of fast switchable multi-format linearly frequency modulation (LFM) waveforms with a tuned bandwidth for a joint radar-communication (JRC) system is proposed and demonstrated. In this scheme, the up-, down-, dual-chirp LFM waveforms along with zero-value are obtained to form the joint waveform for carrying two bits of information per symbol. The bandwidth of the LFM waveforms can be tuned by adjusting the parabolic signal that drives the phase modulator (PM). The joint waveform can be used not only for radar ranging but also for the wireless communication. Simulation results show the 9–11 GHz up-, down- and dual-chirp waveform as well as the zero-value signal can switch at a rate of 64 MHz. The bandwidths of the LFM waveforms are tunable. The communication rate is up to 128 Mbit/s and the radar ranging resolution can reach up to 1.875 cm. The proposed scheme has a simple structure and can get good communication and range detection performance based on a joint waveform, and is expected to be used in the multifunctional JRC system.

Optimization strategy of property energy management based on artificial intelligence

This study focuses on the design and optimization of property energy management systems, aiming to improve energy efficiency, reduce waste, and enhance user comfort and satisfaction through intelligent means. The research background is based on the urgency of energy conservation and emission reduction, and the rise of smart property management models on a global scale, especially the increasing demand for energy efficiency monitoring, predictive analysis, automated control, and user engagement. To address the urgent need for energy conservation and emission reduction, particularly in the realm of property management, this study designed and optimized a property energy management system. The core of the research is a systematic energy management framework that encompasses efficient monitoring, intelligent predictive analytics using techniques such as Long Short-Term Memory (LSTM) networks for energy consumption forecasting, automated control, user-friendly interfaces, and system safety. An empirical case study was conducted at a large-scale commercial complex, confirming the effectiveness of the system. Through intelligent transformation, specifically the optimization of air conditioning and lighting systems using advanced technologies like frequency modulation and LED lighting, a total energy saving rate of 25% was achieved. The annual economic savings exceeded 1.25 million yuan, and user satisfaction was significantly improved. During the research process, several limitations and challenges were encountered, including data quality issues and scalability concerns. These limitations were addressed through rigorous data preprocessing and validation, ensuring the robustness of the findings and their applicability to similar environments. The results demonstrate the potential of integrating artificial intelligence and machine learning techniques into property energy management systems, paving the way for more sustainable and efficient buildings. This revised abstract includes more specific details about the technologies used, such as LSTM networks, and mentions the limitations and challenges faced during the research. It also emphasizes the practical application and scalability of the system.

The use of artificial songs to assess song recognition in imprinted female songbirds: a concept proposal.

We propose an experimental paradigm to examine acoustic features responsible for song preference and recognition in songbirds. Song preference in female songbirds is often influenced by early song experience. That is why several Estrildid species, including our subject species, the Java sparrow (Padda oryzivora), are known to show an imprinted preference for their father's songs. After confirming that Java sparrow females preferred their father's song compared to non-imprinted through song playbacks (first step), we repeated the playback tests in the same subjects using synthesized stimuli (second step). To create synthesized stimuli, we removed all the complex frequency modulations and subharmonics from song notes that we used for the first step playback tests to see the effect of spectrometric features on song recognition. The results indicated that females showed higher rate of calling towards synthesized father song stimuli, suggesting that the macroscopic patterns would play more important roles in song recognition than the microscopic acoustic features. Although we looked at spectrometric features and father-imprinted song preference in this study, similar testing can be applied in many ways to test preference for local dialects or subspecies-specific songs.

Magnetic tuning with minimal thermal drift in high-Q microspheres coated with magnetorheological polydimethylsiloxane.

Integration of whispering-gallery-mode (WGM) resonators with high-quality factors (Q) into advanced timing, oscillator, and sensing systems demands a platform that enables precise resonance frequency modulation. This study investigates the tuning characteristics of magnetorheological polydimethylsiloxane (MR-PDMS) coated microspheres (µ-spheres) employed as magnetic microresonators, achieving a Q value of 107 at the 1550 nm wavelength. Magnetic WGM resonators not only endow the device with magnetic adjustability but also markedly improve thermal resistance. Experimental findings reveal that the magnetic µ-sphere demonstrates a sensitivity of -32.53 MHz/mT, outperforming conventional magnetic WGM resonators. Furthermore, analysis of the temperature dependence shows a reduction in fluctuation to -2.85 MHz/K, thereby greatly enhancing the sensor's practical detection limit.

MDT-MVMD-based frequency modulation for photovoltaic energy storage systems

MDT-MVMD-based frequency modulation for photovoltaic energy storage systems

Hybrid-Energy Storage Optimization Based on Successive Variational Mode Decomposition and Wind Power Frequency Modulation Power Fluctuation

In order to solve the problem of frequency modulation power deviation caused by the randomness and fluctuation of wind power outputs, a method of auxiliary wind power frequency modulation capacity allocation based on the data decomposition of a “flywheel + lithium battery” hybrid-energy storage system was proposed. Firstly, the frequency modulation power deviation caused by the uncertainty of wind power is decomposed by the successive variational mode decomposition (SVMD) method, and the mode function is segmented and reconstructed by high and low frequencies. Secondly, a mathematical model is established to maximize the economic benefit of energy storage considering the frequency modulation mileage, and quantum particle swarm optimization is used to solve the target model considering the charging and discharging power of energy storage and the charging state constraints to obtain the optimal hybrid-energy storage configuration. Finally, the simulation results show that, in the step disturbance, the Δfmax of the hybrid-energy storage mode is reduced by 37.9% and 15.3%, respectively, compared with single-energy storage. Under continuous disturbance conditions, compared with the single-energy storage mode, the Δfp_v is reduced by 52.73%, 43.72%, 60.71%, and 47.62%, respectively. The frequency fluctuation range is obviously reduced, and the frequency stability is greatly improved.

Participation of wind-storage combined system in the secondary frequency regulation control strategy of power grid

Abstract The secondary frequency modulation of the unit, that is, the automatic generation control (AGC), is the process of increasing or decreasing the power of the power generation unit by the power plant unit according to the dispatching command issued by the power grid dispatching center, and then using the frequency modulator to restore the frequency. Based on the principle of AGC, this paper establishes a frequency dynamic response model of the secondary frequency modulation of the traditional unit and the wind storage participation system including load frequency control (LFC) and traditional proportional-integral-derivative (PID) controllers, determines the frequency modulation control strategy of wind storage, and uses the distribution mode based on Area Control Error (ACE) signal to assist in the secondary frequency modulation. In order to solve the parameter optimization problem of the classical PID controller when the wind-storage combined system participates in the secondary frequency modulation under the large load disturbance, a parameter optimization model of the controller with PID was established, and the ITAE evaluation index was finally selected as the fitness function by comparing different fitness evaluation indexes. To overcome the problem that the conventional Particle Swarm Optimization (PSO) is prone to local extremum, the inertia weights and learning factors are adjusted nonlinearly to balance and optimize the global and local optimization capabilities and improve the search efficiency, and the parameters of the PID controller are optimized by the improved PSO algorithm. The simulation results show that the proposed algorithm improves the secondary frequency modulation effect under the background of a high proportion of renewable energy connected to the power grid.

Life prediction method of battery energy storage system in frequency modulation application

Abstract To tackle the challenge of lifespan reduction in lithium batteries during frequency modulation, this study introduces a novel Remaining Useful Life (RUL) prediction methodology. The proposed approach integrates Variational Mode Decomposition (VMD) with Gated Recurrent Unit (GRU) networks, thereby efficiently synthesizing data from both operational parameters and capacity metrics. Firstly, VMD is utilized to decompose the initial capacity data of lithium batteries into separate components characterized by high and low frequencies. Subsequently, for the high-frequency elements, GRU is employed for rolling iterative prediction, while for the low-frequency elements, features are extracted from the operational data and inputted into GRU for prediction. Finally, the component prediction results are restored to obtain capacity prediction values. Validation conducted using the NASA dataset shows that the root mean square error of capacity prediction is minimized to 0.0122, with a corresponding minimum average absolute error of 0.0096, and RUL prediction errors are generally within 2 cycles.

Improvement Underwater Acoustic Signal De-Noising Based on Dual-Tree Complex Wavelet Transform

Underwater Acoustic signal denoising is encountering high demand due to the extensive use of acoustic in a lot of underwater applications. Underwater acoustic noise (UWAN) has a high effect on the quality of the acoustic signal therefore, it is always preferred to use a de-noising filter to remove it. In this paper, we propose a filter that utilizes a Complex wavelet transform (CWT) to remove UWAN and help improve the signal-to-noise ratio (SNR) of the detected acoustic signal. CWT is nearly shift-invariant and offers a good directionality in contrast to normal wavelet transform (DWT). The proposed method was tested using a real recorded UWAN for three depths from the Tigris River. The proposed method was compared with a more conveniently used discrete wavelet transform. The test included using Two signals: fixed frequency and linear modulation signal. De-noising was performed using a soft thresholding technique based on level-dependent threshold estimation. The proposed method showed supreme performance in terms of SNR and root mean square error (RMSE). When the input signal was 5.9 dB and -13.2 dB for SNR and RMSE respectively, the results were 10.9 dB for SNR and -15.7 dB for RMSE in the case of fixed frequency.

Abstract P103: Assessment of Angiotensin II-induced Calcium Signals in Primary Human Adrenocortical Cells

Background: Cytosolic and mitochondrial Ca 2+ concentrations are key signals for triggering the secretion of aldosterone in primary aldosteronism (PA), the most common form of secondary hypertension. Aim: To investigate [Ca 2+ ] i transients and oscillations in human CD56 + cells isolated from aldosterone producing adenoma (APA) and normal surrounding adrenocortical (AAC) cells. Methods: We assessed [Ca 2+ ] i in CD56 + APA and APA-adjacent cells (AAC) in basal conditions and after angiotensin II (Ang II) stimulation using Fura-2 dye, live confocal microscopy, and an ad hoc developed custom-made pipeline to analyze [Ca 2+ ] i signals in terms of frequency and peak parameters as amplitude, full width at half maximum (FWHM) and area under the curve (AUC). As the two-pore domain K + TASK- 2 channels are under expressed in APA, we used quinidine (20 μM), 20’ prior to [Ca 2+ ] i imaging acquisition to examine the effect of the pharmacological inhibition of this channel. Results: Resting [Ca 2+ ] i basal levels were higher in AAC (n=11) (0.75, IQR;0.90-0.56) than in APA (n=11) (0.36 IQR;0.69-0.33), (p < 0.02). We detected spontaneous Ca 2+ activity, during resting conditions, in both cell types without significant difference in peak parameters. Upon 1 nM Ang II simulation, AAC showed elevated FWHM, amplitude, and AUC peak parameters of first Ca 2+ transients. However, APA cells exhibited elevated peak parameters of subsequent Ca 2+ oscillations. Ca 2 oscillations frequency and degree of oscillating cells were significantly higher in APA cells than in AAC. After 24 hours in culture, both AAC and APA cells developed rosette-like cell structure resembling the “glomeruli” of the intact zona glomerulosa clusters. Functional Statistics and clustering analysis showed synchronous behavior of cells belonging to the same cluster without significant differences between AAC and APA. In AAC, Task-2 Inhibition with quinidine tended to increase spontaneous activity and altered peak’s parameters but did not influence frequency of oscillation. Conclusion: Quantitative assessment of [Ca 2+ ] i signals unveiled significant differences in [Ca 2+ ] i dynamics between human AAC and APA cells. These results suggest the concurrent modulation of frequency and amplitude of [Ca 2+ ] I subsequent oscillations as a potential driver of increased rate of aldosterone production.

Adaptive adjustment method of segment linear frequency modulation excitation for wideband dipole logging

Abstract Wideband dipole signal is the basis for dipole dispersion correction and near-borehole imaging. Segment linear frequency modulation (SLFM) sound source signal is an effective method to broaden the dipole frequency band. In the actual logging process, the formation environment changes in real time, and the SLFM sound source with fixed parameters cannot compensate the bending wave excitation intensity curve at any time, which affects the quality of logging. This paper presents a method for adaptive adjustment of the SLFM sound source signal. Adaptive parameter adjustment can be made according to the change of downhole environment, so that the signal can be adapted to the changing downhole geological environment.

Joint waveform design of radar detection, wireless communication and jamming based on chaotic composite modulation

AbstractIn this letter, we address the problem of designing the joint waveform of radar detection, wireless communication and jamming. In the current most powerful filter‐bank multi‐carrier comb spectrum framework, a parameter‐agile time–frequency structure between symbols is elaborated to improve the uncertainty of waveform generation architecture. Furthermore, a novel composite modulation strategy that combines intra‐symbol chaos‐based radar frequency modulation and inter‐symbol chaos‐based phase modulation is proposed for a substantial jamming performance improvement. Simulation results verify that the proposed joint waveform produces a superior jamming performance while satisfying the requirements of radar detection and wireless communication.

Real-Time Millimeter-Wave Imaging With Linear Frequency Modulation Radar and Scattered Power Mapping

Real-Time Millimeter-Wave Imaging With Linear Frequency Modulation Radar and Scattered Power Mapping

Influence of the magnetic field on the shunt resistance of an n+p-p+ silicon solar cell in the frequency modulation

A photovoltaic cell is a device that generates electricity directly from visible light. Several factors affect the conversion efficiency of solar cells. Parasitic resistances such as the shunt resistance is a fundamental parameter of the equivalent electrical model of the solar cell, which induces the leakage current of electrical charges when its value is low. It represents all leakage currents within the solar cell. It is also an indicator of good or poor quality of a solar cell, since a high value indicates low leakage current through the cell, and vice versa. A number of measurement techniques are used to determine the leakage current, in particular electrical current and voltage.

Performance analysis of quantum harmonic Otto engine and refrigerator under a trade-off figure of merit

Abstract We investigate the optimal performance of the quantum Otto engine and refrigeration cycles of a time-dependent harmonic oscillator under a trade-off figure of merit for both adiabatic and nonadiabatic (sudden-switch) frequency modulations. For heat engines (refrigerators), the chosen trade-off figure of merit is an objective function defined by the product of efficiency (coefficient of performance) and work output (cooling load), thus representing a compromise between them. We obtain analytical expressions for the efficiency and coefficient of performance of the harmonic Otto cycle for the optimal performance of the thermal machine in various operational regimes. Particularly, in the sudden-switch regime, we discuss the implications of the nonadiabatic driving on the performance of the thermal machine under consideration and obtain analytic expressions for the maximum achievable efficiency and coefficient of performance of the harmonic Otto thermal machine. Particularly, we show that the quantum harmonic Otto cycle driven by sudden-switch protocol cannot work as a heat engine or refrigerator in the low-temperature limit. Finally, we show that in the high-temperature limit, the frictional effects give rise to a richer structure of the phase diagram of the harmonic Otto cycle. We identify the parametric regime for the operation of the Otto cycle as a heat engine, refrigerator, accelerator, and heater.

Psychometric evaluation of high-resolution electrotactile interface for conveying 3D spatial information

This study presents a detailed psychometric evaluation of a novel high-resolution electrotactile interface, which is developed to provide users with 3D spatial information and facilitate enhanced interaction with a Supernumerary Robotic Limb (SRL). The research introduces a novel electrotactile system that employs a multi-pad electrode configuration on the thigh, aimed at delivering intuitive feedback to users about the position of the SRL in a three-dimensional space. The interface's effectiveness was assessed through a series of psychometric tests, including static spatial discrimination, target-reaching with spatial feedback, frequency discrimination, and combined spatial/frequency modulation. The key findings demonstrate that participants could differentiate between 30 electrode pads with an average success rate of 62.7% when they were activated statically, while in the dynamic target-reaching task, the success rate increased to 88.1%. Frequency discrimination tests further revealed that four frequency levels could be distinguished with 86.0% success rate in single-pad feedback while the performance decreased to 74.3% in multi-pad distributed feedback. Finaly, in the closed-loop test with mixed spatial and frequency modulation, participants achieved an overall success rate of 78.8% in target reaching across 10 × 4 discrete 2D space. These results highlight the interface’s capability to transmit high-resolution spatial information through electrotactile feedback, offering a foundation for future applications in tactile-based navigation and control systems.