Frequency Measurements Research Articles

LC dynamic signal modeling and analysis of resonant frequency measurement error under rapid eye movements interference

Abstract LC resonant wireless passive intraocular pressure (IOP) sensors measure IOPs by mapping them to LC resonance frequencies. However, during the sweeping acquisition process of each LC signal frame, possible rapid eye movement (REM) can interfere with the wireless mutual inductance coupling, leading to the signal distortion and resulting in the error of resonance frequency measuring. Currently, there is a lack of modelling analysis of the errors generated by REM effect, resulting in an absence of guidance for reducing the impact. Therefore, here, we start from the perspective of the signal model and establish the LC dynamic signal model for sweeping acquisition. By means of the limit state analysis and Monte Carlo simulation, we analyze the influence of external REM parameters (including REM range and velocity) and internal parameters of the LC sensing system (including the quality coefficient of LC sensor, diameter, and number of turns of the reader coil, signal sweep acquisition speed and period) on the errors. We demonstrated theoretical relationship between the extreme errors with these parameters and verify it through a computer simulation. Based on the results, we propose to optimize the internal parameters of the LC sensing system to reduce the REMs effect on errors, safeguarding the quality of signal acquisition and improving the measurement accuracy.

A Review of the Measurement of the Multiphase Slug Frequency

The slug frequency (SF), which refers to the number of liquid slugs passing through a pipe during a specific time, is an important parameter for characterizing the multiphase intermittent flows and monitoring some process involving this kind of flow. The simplicity of the definition of SF contrasts with the difficulty of correctly measuring it. This manuscript aims to review and discuss the various techniques and methods developed to determine the slug frequency experimentally. This review significantly reveals the absence of a universal measurement method applicable to a wide range of operating conditions. Thus, the recourse to recording videos with high-speed cameras, which can be used only at a laboratory scale, remains often necessary. From the summarized state-of-the-art, it appears that correctly defining the threshold values for detecting the liquid slugs/elongated bubbles interface from physical parameters time series, increasing the applicability of instrumentations at industrial scales, and properly estimating the uncertainties are the challenges that have to be faced to advance in the measurement of SF.

Absolute frequency measurements on the 5s5p3P0 → 5s6d3D1 transition in strontium

We report the first absolute frequency measurements for the 5s5p3P0→5s6d3D1 transition at 394 nm for all the stable strontium isotopes by utilizing repumping induced spectroscopy in a magneto-optical trap. Absolute transition frequency is measured to be 760524409251(25) kHz for Sr88. With reference to Sr88, the isotope shifts are measured to be 91052(35), 54600(33), and 51641(28) kHz for Sr84, Sr86, and Sr87, respectively. We calculate the hyperfine constants A and B for the fermionic isotope Sr87 at kHz level. Furthermore, we perform King plot analysis by combining isotope shifts on the 689-nm transition to our data. Published by the American Physical Society 2024

High-precision IFM receiver based on random forest algorithm

Abstract The six-port network-based Instantaneous Frequency Measurement (IFM) receiver is widely utilized in industrial applications for signal frequency demodulation. However, current IFM receivers face the issue of low algorithmic demodulation accuracy (ACC). According to the four-channel output characteristics of the IFM receiver, we use the Random Forest algorithm to extract features, train and test the output voltage data set, and recognize frequency labels. The experimental results show that the ACC of the proposed algorithm reaches 0.9583, which is 13.99% higher than that of the traditional polynomial fitting algorithm. To evaluate the noise reduction performance of the algorithm, we add Gaussian white noise to the original data and demodulate the signal with noise. Comparative tests prove the advantages of the algorithm in high stability and flexibility. Finally, multiple model evaluation indicators demonstrate that the algorithm features strong applicability and robustness to the experimental data with IFM receiver.

PERSEPSI MASYARAKAT TERHADAP KEBERADAAN RUMAH WALET DI DESA WATUTAU KECAMATAN LORE PEORE KABUPATEN POSOSULAWESI TENGAH

This research aims to determine the public's perception of the existence of swallow houses in Watutau Village, Lore Peore District, Poso Regency, and the factors that influence people's perceptions of swallow houses. In this research, the population was taken from a community located at a radius of 250 meters, namely 31 heads of families, the number of samples taken was 31 respondents. This research is a qualitative descriptive research. The research method used by the survey method is one of the information collection techniques carried out by compiling a list of questions asked to respondents at the research location. The data analysis used is descriptive statistics using grouping, simplification and presentation of data such as frequency distribution tables and measurements using the likert and chi- square scales. Based on the results of the study, the perception of the community in Watutau Village, Lore Peore District, Poso Regency, is in the category of Disturbed / Disagreed with the exis tence of swallow houses and the most influential factors in the perception of the community in Watutau Village, Lore Peore District, Poso Regency are the distance of houses on sound and socio-cultural indicators on community perceptions.

Monitoring the Wake of Low Reynolds Number Airfoils for Their Aerodynamic Loads Assessment

Experimental investigations are carried out to explore the aerodynamic performance and vortex shedding characteristics of S5010 and E214 airfoil-based wings to provide guidance for the design of MAVs and other low-speed vehicles. Force and wake shedding frequency measurements are carried out in a subsonic wind tunnel in the Reynolds number (Re) range of 4 × 104 - 1 × 105. The measurements with increasing Re show that the slope of the lift curve in the linear region increases by 14% for S5010, while this increment is 11% for E214. The peak lift coefficient of both airfoils reduces with reducing Re. For lower pitch angles, the influence of Re on drag coefficients is less significant, but at higher angles, the drag increases as the Re drops. Unlike pre-stall mountings, the pitch-down propensity of the airfoil enhances in the post-stall region for high Re flows. Moreover, the frequency of shed vortices reduces with rising angle of attack at a given Re. In contrast, the Strouhal number almost remains constant with varying Re at a fixed angle of attack. For S5010 and E214 airfoils, the Strouhal number is noticed to vary between 0.68 - 0.36 and 0.58 - 0.36, respectively, for pitch angle variation of 12°- 28°. The airfoils show a higher Strouhal number than the bluff body wakes, but this difference decreases for high angles of attack mountings. This finding reveals that the wake structure of the airfoil at a high post-stall angle behaves as bluff body wakes.

Characterization of the Power Distribution Network for Commercialized STM32s Using a Resonance Frequency Measurement Method

Power integrity is a critical aspect of microcontroller (MCU) system design. The present tendency of increasing current density and operating frequency, along with decreasing operating voltage, significantly diminishes voltage margins. Given the cost efficiency required for MCU systems, this context places important constraints on the design of the power distribution network (PDN), which directly impacts power supply noise. Therefore, characterizing the PDN is necessary. This paper introduces a cost-effective measurement and modeling method to estimate the die-package resonance frequency of the PDN, a major threat to power integrity. The method, applied to two 32-bit MCUs from STMicroelectronics with varying PDN configurations, enables the identification of the die-package resonance frequency. The results lead to the refinement of the die capacitance model for both cases, with a maximum relative error of less than 7%. The final objective is to implement the measurement system in the die in order to adjust the PDN if necessary.

Frequency dependence of reflections on radar landmarks

Purpose. Reducing the dispersion of radar reflections from local objects, with multi-frequency sensing, to solve the problem of orientation by radar reflections from objects. Methodology. Reflections from local objects in the entire frequency range of the radar station (RS) at the same radio engineering position were measured by three independent radars of the same type on different days and at different antenna elevations. The deviation of the radar stations in the position did not exceed 500 meters. Coordinates (azimuth, range) of reflections of several separate local objects were allocated for each radar. The average values of reflections from local objects and their dispersion in the frequency range were calculated. Using various algorithms, individual frequencies were sampled and the reflected signals were averaged at these frequencies. The decrease in the dispersion of the reflected signal from the number of frequencies at which reflections were measured and from the algorithm for selecting these frequencies was investigated. Findings. Averaging the values of reflections from local objects for several frequencies leads to a decrease in dispersion and, as a result, to a more accurate correspondence of the reflected signal level to the geometric size of the local object. The variance decreases most rapidly for a small number of frequencies selected for averaging when selecting frequencies located in an interval of at least 1% relative to each other. Originality. To solve the problem of orientation based on radar reflections from local objects, it is necessary to identify the landmarks selected on a digital terrain model. Due to the fact that local objects (hills) are a collection of many reflectors falling into the allowed volume of the radar, with different levels of reflections and random phases, there may not be radar reflection from a local object at a certain frequency, or it may be very small. In order to unambiguously identify all landmarks, measurements must be carried out at several frequencies. The work has established how many frequencies measurements should be performed at and on what principle these frequencies should be selected. Practical value. The advent of digital terrain models made it possible to solve the problem of terrain orientation by comparing radar reflections from local objects with reflection models based on digital terrain maps. Radar reflection models use mathematical expectations of reflection values, unlike real reflections, which have random deviations in signal levels depending on the operating frequency. Reducing the variance of these deviations increases the accuracy of identifying characteristic local objects (landmarks) used to orient the radar in the absence of data from satellite navigation systems.

Broadband photonic frequency measurement based on the frequency-to-carrier phase-shifted mapping and finite extinction ratio

A novel frequency measurement is proposed based on frequency-to-carrier phase-shifted mapping and finite extinction ratio. Due to the frequency dependence of the dispersion phase shift, carrier phase-shifted double-sideband modulation and dispersive effect are combined for effective mapping. Additionally, the finite extinction ratio is introduced to mitigate the influence of unideal parameters on measurement error. To achieve this, a dual-parallel Mach-Zehnder modulator and a dispersion compensating fibre are combined, and a power minimization problem is formulated to establish a mapping table. Theoretical analysis and simulation results show the frequency measurement range over 30 GHz with errors below 180 MHz. Furthermore, the measurement error is reduced below 40 MHz after considering the finite extinction ratio.

DBPR116, a Prodrug of BPRMU191, in Combination with Naltrexone as a Safer Opioid Analgesic Than Morphine via Peripheral Administration.

The development of opioid analgesics with reduced adverse effects is an unmet need. In a previous study, we discovered a unique combination of BPRMU191 and morphinan antagonists that produced potent antinociception with reduced adverse effects after central administration (intrathecal or intracerebroventricular). BPRMU191/naltrexone exhibits notable in vitro and in vivo pharmacological properties. However, the poor blood-brain barrier penetrative ability of BPRMU191 restricts its clinical application. In this study, we utilized a prodrug strategy to deliver sufficient brain concentrations of BPRMU191 and selected compound 2 (DBPR116) with the best physicochemical and pharmacological properties among other in vivo active prodrugs. The in vivo pharmacological studies of compound 2/naltrexone, including thermally stimulated pain, cancer pain, constipation, sedation, psychological dependence, heart rate, and respiratory frequency measurements, demonstrated that it was a safer opioid analgesic than morphine in pain control.

Unravelling the Enigmatic Nexus: Black Holes, Dark Matter, and the Interplay of Light, Gravity, and Electromagnetic Forces in Astrophysics and Astronomy

This research introduces a mathematical model positioning our physical reality within a ten-dimensional hyperspace, in which time acts as the unifying coordinate linking three-dimensional electric, magnetic, and gravitational spaces. Each domain is characterized by its respective field—electric, magnetic, or gravitational—and governed by intrinsic divergences and rotations, leading to a universal property known as Force Density, expressed in [N/m³]. This Force Density facilitates interactions among the distinct spaces while adhering to the principle of equilibrium, which posits that cumulative force densities from disturbances must consistently sum to zero. Building upon Einstein's General Relativity—which describes the curvature of spacetime by gravitational fields and assumes a constant light speed—this study proposes a perspective wherein light speed may vary during coherent laser beam interactions, prompting a re-examination of gravitational and luminous interactions across scales. The proposed model integrates the Stress-Energy Tensor and Gravitational Tensor, introducing a new tensor representation for black holes, termed Gravitational Electromagnetic Confinements, incorporating electromagnetic energy gradients and Lorentz transformations. This framework transcends traditional General Relativity, particularly evident in gravitational lensing. By reinterpreting Einstein's incorporation of the Gravitational Constant within the Energy-Stress Tensor, this work harmonizes gravity and light, offering insights into black hole solutions resonating with John Archibald Wheeler's 1955 research. Empirical data from Galileo satellites and MASER frequency measurements underscore discrepancies between established theories and this new model, enhancing the precision of gravitational observations. Through the confluence of Quantum Physics and General Relativity, as seen in approaches like String Theory, this interdisciplinary endeavor revisits the gravitational constant "G," redefining it while bridging theoretical frameworks, thus paving the way for breakthroughs in astronomical and astrophysical sciences.

Comparison of the Young’s modulus of the lead free solder alloy Sn-Ag3.8-Cu0.7 determined by hot tensile tests, ultrasonic measurements and [formula omitted]-Sn single crystal calculations

Sn-based solders are known for their tendency to form coarse grained microstructures. In combination with the high elastic anisotropy of β-Sn, the overall elastic properties and their interpretation require a careful discussion of the structure–property-relationship as elastic constants are often important input parameters for creep or fatigue models. This study therefore investigates the influence of microstructure and testing method on the Young’s modulus E for the widespread lead free solder alloy Sn-Ag3.8-Cu0.7 (SAC387) using bulk specimens. Due to its already high homologous temperature at room temperature (Thom≈ 0.6 = T/Tm for Tm being the melting temperature), hot tensile tests generally bear the risk of superimposed creep deformation. Mechanical testing becomes even more challenging, since yield strengths are usually low for these alloys. Consequently, in addition to the hot tensile tests executed for the engineering strain rate ϵ̇e=1⋅10−3 s−1, two supplemental methods are used to determine the Young’s modulus comprising of the dynamic resonance frequency measurement and the calculation of the Young’s modulus based on single crystal compliance data of the majority phase β-Sn.Young’s moduli yielded from dynamic resonance frequency measurement and calculations based on single crystal compliance data showed comparable results of (E35 °C≈ 55 GPa, E80 °C≈ 51 GPa and E125 °C≈ 48 GPa). Hot tensile tests showed similar data with the largest deviation at 80 °C, where E80 °C≈ 53 GPa was determined. These absolute values and their temperature dependence can be attributed to the microstructure of the cast specimens which show a general preferred orientation of β-Sn grains close to <110> after analysis via electron backscattered diffraction (EBSD). A comparison with literature data revealed significant differences in the Young’s moduli which are likely to be attributed to differences in the preferred orientation of β-Sn grains.

Measurement of Electron Antineutrino Oscillation Amplitude and Frequency via Neutron Capture on Hydrogen at Daya Bay.

This Letter reports the first measurement of the oscillation amplitude and frequency of reactor antineutrinos at Daya Bay via neutron capture on hydrogen using 1958days of data. With over 3.6million signal candidates, an optimized candidate selection, improved treatment of backgrounds and efficiencies, refined energy calibration, and an energy response model for the capture-on-hydrogen sensitive region, the relative ν[over ¯]_{e} rates and energy spectra variation among the near and far detectors gives sin^{2}2θ_{13}=0.0759_{-0.0049}^{+0.0050} and Δm_{32}^{2}=(2.72_{-0.15}^{+0.14})×10^{-3} eV^{2} assuming the normal neutrino mass ordering, and Δm_{32}^{2}=(-2.83_{-0.14}^{+0.15})×10^{-3} eV^{2} for the inverted neutrino mass ordering. This estimate of sin^{2}2θ_{13} is consistent with and essentially independent from the one obtained using the capture-on-gadolinium sample at Daya Bay. The combination of these two results yields sin^{2}2θ_{13}=0.0833±0.0022, which represents an 8% relative improvement in precision regarding the Daya Bay full 3158-day capture-on-gadolinium result.

Advanced power quality monitoring with dilated convolutional neural networks for smart nanogrids

This study presents the development of an advanced power quality monitoring (PQM) system using dilated convolutional deep neural networks (DCDNN) for smart nanogrids. Traditional convolutional neural networks (CNNs) face challenges in efficiently handling high-dimensional data and identifying nuanced features due to their limited receptive field. To overcome these limitations, our DCDNN model employs a novel use of dilated convolutions to expand the receptive field without increasing network complexity, enabling the capture of long-range dependencies essential for accurate classification of power quality disturbances (PQDs). In addition, the integration of multi-channel time-series data processing, including voltage, current, and frequency measurements, is unique to our approach. The model processes multi-channel time-series data, including voltage, current, and frequency measurements, achieving an average accuracy of 98.9% across 29 PQD classes and 100% accuracy in 6 main classes, with a reduced detection time of 47 µs per segment. This approach not only improves real-time disturbance detection but also enhances the reliability and efficiency of electrical systems. The results demonstrate significant improvements over existing methods, underscoring the potential of DCDNNs in advancing PQM practices. Future work will focus on validating the model in real-world conditions and optimizing its computational efficiency.

Fitness club adjacent to a quiet corporate office - Prototypes

There is a demand for fitness clubs in hotels, residential, and corporate buildings - sometimes adjacent to sensitive spaces. Activities involving weight drops and spinning bikes, among others, cause dynamic forces in the structure that propagate through the building's structure and radiate airborne sound. There is an effort by acousticians worldwide to establish a standardized method for measuring and rating the noise radiated by gyms into adjacent areas. This article describes the construction of a gym over a corporate office, occupying an area of 2100 m2 each. The gym's floor structure is a concrete and steel deck, and the office below has low sound levels. The goal of making gym activity inaudible in the office is undoable in practice. We tested several prototypes to arrive at a double insulation system with a floating slab with natural rubber mounts. A system of dynamic dampers was installed to reduce the movement of the floating slab with the dynamic excitation above it. The results of the prototype were auspicious. This paper presents the measurements of the natural frequency of the structure and the floating slab, the transmissibility of the system, and the differences in vibratory velocity from the floating floor to the structure.

Variability of low frequency laboratory measurements of acoustic isolation of floor/ceiling assemblies

It has long been recognized that building acoustics measurements performed in laboratories exhibit a high degree of variability between and within labs. Traditional metrics limited the use of data to above the 100Hz or 125Hz one-third octave bands. In recent years, focus has widened the range of frequencies of interest to the 50Hz one-third octave band or lower. Analyzing measurements of low frequencies in buildings is complicated by the physical reality of wavelengths that are similar in scale to common room dimensions resulting in modal behavior and the mathematical simplification of the wave equation in building acoustic calculations that assumes a diffuse field which discounts both phase and angle of incidence. Evaluation of common building isolation measurements of the same test floor/ceiling structure sample in the same lab and between labs across the frequency spectrum allows the comparison of the repeatability and reproducibility at low frequency ranges to those at high frequency ranges. Measurements and their associated metrics of various sources, including pink noise produced by loudspeakers, the standard tapping machine, and the impact ball are included in the analysis.

Evaluation of ANSI low frequency measurement standard S12.9 part 7 in light of current research

ANSI S12.9 Part 7 (2016) Measurement of Low-frequency Noise and Infrasound Outdoors in the Presence of Wind and Indoors in Occupied Spaces was developed over 2-3 years and was a much needed guide to standardize the measurement of low frequency sound and infrasound. Since then, research has advanced what are now considered best practices, and technology has advanced to make instrumentation available to consultants and researchers to help solve several limiting issues in measurements. This paper provides a review of the standard and recommends improvements to the techniques used in the measurement of low frequency-infrasound outdoors. These improvements include better assessment and understanding of wind noise, the importance of sensor placement, and advances in transducers, wind screening, arrays and calibration. The information provided includes best practice with a conceptual understanding of the interaction with the environment in low frequency-infrasound measurement; references are provided for a deeper dive into each topic.

High-Precision Photonics-Assisted Two-Step Microwave Frequency Measurement Combining Time and Power Mapping Method.

Photonics-assisted methods for microwave frequency measurement (MFM) show great potential for overcoming electronic bottlenecks and offer promising applications in radar and communication due to their wide bandwidth and immunity to electromagnetic interference. In common photonics-assisted MFM methods, the frequency-to-time mapping (FTTM) method has the capability to measure various types of signals, but with a trade-off between measurement error, measurement range, and real-time performance, while the frequency-to-power mapping (FTPM) method offers low measurement error but faces great difficulty in measuring signal types other than single-tone signals. In this paper, a two-step high-precision MFM method based on the combination of FTTM and FTPM is proposed, which balances real-time performance with measurement precision and resolution compared with other similar works based on the FTTM method. By utilizing high-speed optical sweeping and an optical filter based on stimulated Brillouin scattering (SBS), FTTM is accomplished, enabling the rough identification of multiple different signals. Next, based on the results from the previous step, more precise measurement results can be calculated from several additional sampling points according to the FTPM principle. The demonstration system can perform optical sweeping at a speed of 20 GHz/μs in the measurement range of 1-18 GHz, with a measurement error of less than 10 MHz and a frequency resolution of 40 MHz.

Investigation on intermittent flow characteristics in horizontal pipe by visualization measurement method

Accurate measurement and prediction of the intermittent flow characteristics in horizontal pipes is important for constructing multiphase flow models and ensuring pipe flow safety. In this paper, a quantitative image post-processing technique for intermittent flow characteristics based on gray histogram image similarity is proposed, which can realize the measurement of slug frequency. In addition, the technique also has the ability to classify a large number of images, and can quickly find the elongated bubble head, liquid film area and liquid slug area of intermittent flow. On the basis of this technique, combined with image post-processing methods such as gas–liquid interface feature analysis, a set of intermittent flow image processing technique with perfect route is formed. Based on this post-processing technique, the similarity image oscillation trajectories of plug flow and slug flow are obtained. There are differences in the similarity image oscillation trajectories of the two intermittent sub-flow patterns, and the similarity image of the plug flow has an obvious platform period and trailing rising line, which can be used as a basis for the classification of the two intermittent sub-flow patterns. A correlation for predicting the slug frequency of intermittent sub-flow patterns is developed. The accuracy of this slug frequency prediction correlation can be improved by about 10 % compared to not dividing the sub-flow patterns. When the mixture Froude number Frm is less than 5.0, the radial position of the elongated bubble head decreases linearly as the Frm increases. When the Frm is greater than 5.0, the elongated bubble head oscillates near the middle of the pipe. Prediction correlations for the radial position of the elongated bubble head and the slug velocity are established separately, and the maximum error is ± 10 %. The modified mixed Froude number is proposed, and based on this, a new prediction model for the transition from plug flow to slug flow is established.

Multi-Way adaptive Time Aware LSTM for irregularly collected sequential ICU data

In personalized predictive medicine, accurately modeling a patient’s illness and care processes is essential, given their inherent long-term temporal dependencies. However, electronic medical records contain episodic and irregularly timed data due to patients visiting hospitals based on treatment needs, resulting in unique patterns for each hospital stay. Consequently, when constructing a personalized predictive model, it is crucial to consider these factors in order to accurately capture the patient’s health journey.To address this challenge, we present a novel deep dynamic memory neural network called Multi-Way adaptive Time Aware LSTM (MWTA-LSTM). The primary objective of MWTA-LSTM is to leverage medical records, memorize illness trajectories and care processes, estimate current illness states, and predict future risks, thereby providing a high level of precision and predictive power. To enhance its capabilities, MWTA-LSTM extends the conventional Long Short-Term Memory (LSTM) model in two key ways. Firstly, it incorporates frequency measurement and the most recent observation(last observation) to enhance personalized predictive modeling of patient illnesses, enabling a more accurate understanding of the patient’s condition. Secondly, it parameterizes the cell state to handle irregular timing effectively, utilizing both frequency measurement and elapsed times. Furthermore, the model capitalizes on both to comprehend the impact of interventions on the course of illness on the cell state, facilitating the memorization of illness courses and improving its ability to capture the temporal dynamics of healthcare data, accommodating variations and irregularities in event and observation timing. Lastly, we introduce a novel adaptive pooling strategy that specifically targets and resolves outlier issues that can potentially occur during the analysis of EHR data. By incorporating these features, MWTA-LSTM significantly improves its ability to capture the temporal dynamics of healthcare data, accommodating variations and irregularities in event and observation timing.We validate the effectiveness of our proposed model through empirical experiments conducted on two real-world clinical datasets and three real-world time series datasets. Our results demonstrate the superiority of MWTA-LSTM over current state-of-the-art models and other robust baselines. This showcases the potential of MWTA-LSTM in advancing personalized predictive medicine by offering a more accurate and comprehensive approach to modeling patient health trajectories.