Accurate Amplitude Research Articles

Elastic full‐waveform inversion based on the double‐cross‐shaped discrete flux‐corrected transport

AbstractMulti‐parameter elastic full‐waveform inversion is a technique that utilizes both P‐ and S‐waves of observed seismic data to produce high‐resolution velocity and density models with accurate amplitude information by minimizing the discrepancy between the predicted and observed multi‐component data. However, due to the nonlinear nature of the multi‐parameter inverse problem, elastic full‐waveform inversion is prone to local minima and ‘cycle‐skipping’. To overcome these challenges, this paper proposes an elastic full‐waveform inversion method that incorporates a double‐cross‐shaped discrete flux‐corrected transport. This method additionally introduces diffusion fluxes in two diagonal directions, which helps to capture low‐frequency information in the observed seismic data and maintain forward modelling stability. Multi‐scale inversion is achieved by gradually decreasing the diffusion flux correction parameter. Numerical experiments on both two typical models and a field data example demonstrate the effectiveness of the proposed elastic full‐waveform inversion method based on the double‐cross‐shaped discrete flux‐corrected transport in generating high‐precision velocity and density models.

High-fidelity time-series data synthesis based on finite element simulation and data space mapping

Dynamic responses can provide rich information for supporting the entire life cycle of structures, and they can either be measured from actual structures or simulated using the finite element (FE) method. For the FE simulation, insufficient fidelity of simulation data can significantly affect the confidence of analysis results, while FE model updating methods can partially address this problem by reducing the simulation error. However, most FE model updating methods inevitably update the hyperparameters of FE models using sophisticated algorithms with high computational complexities. Thus, one question was raised: whether there is a mapping that can transfer the FE simulation data to the corresponding measurement data directly without performing FE model updating? To achieve this, we proposed a data synthesis method using FE simulation and deep learning space mapping, which can be used to synthesise high-fidelity dynamic responses excited by some unseen load patterns in the measurement. A Dilated Causal Convolutional Neural Network (DCCNN) was designed for realising space mapping. Vibration experiments were conducted on both an I-shaped steel beam and the corresponding FE model to establish datasets and test the proposed method. The quality of the synthetic data was analysed in both the time domain and the frequency domain. The accurate amplitudes, natural frequencies, and mode shapes of the synthetic data successfully demonstrate the effectiveness of the proposed high-fidelity data synthesis method.

ETAM: Next Generation Event Timer for Picosecond-Precision Time and Amplitude Measurements.

Riga Event Timers have the ability to measure the interval between events with high resolution, on the order of picoseconds. However, they have several drawbacks, such as sensitivity to environmental temperature changes and an inability to capture the amplitude of the events. In this work, we present the ETAM: a next generation Event Timer. Its innovative features include adaptive correction of measurement errors based on an internal temperature sensor, and integrated peak-detector circuit to determine the amplitude of nanosecond-duration pulses. Evaluation shows that the ETAM has high thermal stability with a root mean square error (RMSE) of <3 ps in a temperature range between 0 and +40 °C, and accurate event amplitude measurement capability, with <2.3 mV RMSE in the 100-1000 mV range. These improvements allow the ETAM to be used in satellite laser ranging, optical time-domain reflectometry, and other field applications that require temperature- and amplitude-based time correction in addition to high robustness, performance, and stability.

A stable downward continuation method for processing gravity data using the equivalent sources with compactness and smoothing constraints

The downward continuation of the potential field is often a necessary step in data processing and interpretation, in which equivalent source is an available method. Unfortunately, due to the physical property distribution of the equivalent source obtained from the observed data inversion, this is an unstable operation. Particularly in the case of noisy data, the generation of false signals can severely obscure the useful information in the original data. To deal with the instability fundamentally, we have developed a constrained equivalent-source method to improve the physical property distribution in the equivalent layer for stable downward continuation of the gravity anomaly. In this method, the compactness constraint is applied to reduce divergent signals, and multiple smoothing is used to further eliminate the signals causing instability. Experiments on synthetic gravity anomalies show that the proposed method yields cleaner images of the physical properties and more accurate amplitudes of the downward-continuing gravity field. Application to measured data also shows that the proposed method can significantly attenuate the divergent signals and enhance the amplitude of the effective signals.

Investigation of Maximum Voluntary Contraction Activity during Robotic Gait

The purpose of this study is to investigate healthy people’s and patients’ lower extremity muscle activities during robotic gait using kinesiology analysis. Initially, muscle signals were taken from 6 paraplegic patients such as spinal cord injury (SCI) and stroke patients, 2 hemiplegic patients and 4 healthy persons. Then, signals were analyzed by using signal processing techniques such as filtering, rectifying, Root Mean Square (RMS) and also by calculating the Max Voluntary Contraction (MVC). As a result, it was seen that hip muscles such as the Gluteus Maximus (GMA), Gluteus Medius (GM) and Iliopsoas (ILP) had lower MVC values in the hemiplegic patients than those of the SCI patients and the healthy persons. Additionally, when the signals that were obtained were analyzed, it was found that the activity of the Medial Gastrocnemius (MG) muscle could be used in determination of movement path and movement intention. Moreover, the EMG results of gait motion may be helpful in applying accurate amplitude and frequency stimulation in epidural stimulation (ES) therapy.

A Fast, Low-Jitter, and Low-Time-Walk Multi-Channel Front-End IC for Diamond and Silicon Radiation Detectors

This paper presents the design and implementation of a radiation-hardened analog front-end (AFE) integrated circuit (IC) developed for interfacing with solid state ionizing radiation detectors, providing accurate amplitude and time-of-arrival measurements. The AFE is designed for use in the Beam Conditions Monitor Prime (BCM’) of the ATLAS experiment at the Large Hadron Collider (LHC). The proposed AFE is comprised of four channels, allowing for re-configuration to operate as either a low-noise high-gain amplifier for beam luminosity measurements, or a high-linearity low-gain amplifier for beam abort functionality. Each of the AFE channels consists of a low noise trans-impedance amplifier (TIA) optimized for minimal jitter and amplitude noise, a second stage differential amplifier, followed by a fully differential Constant Fraction Discriminator (CFD) to provide an amplitude independent time pick-off with a wide dynamic range. The CFD utilizes a new all-pass filter delay topology and high-performance zero-crossing detector to minimize time-walk. The core of each AFE channel occupies an area of 0.06 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> in a 65 nm CMOS technology and consumes 57 mW, including the drivers. The measured AFE chips achieve 1 ns pulse rise time, 130 electron baseline equivalent noise charge (ENC), and <25 ps RMS jitter at 1 fC input charge. To the authors’ best knowledge, this work demonstrates the lowest published time-walk of ±6 ps across 30 dB signal dynamic range. Furthermore, irradiated AFEs are shown to tolerate up to 225 Mrad total ionizing dose with no significant degradation in measured performance characteristics.

Capturing ultra-broadband complex-fields of arbitrary duration using a real-time spectrogram

One of the most intuitive representations of a waveform is achieved through time-frequency analysis, which depicts how the frequency components of a wave evolve over time. Time-frequency representations, such as the spectrogram, are well-known for allowing full-field characterization of a signal in terms of amplitude and phase. However, present methods to capture the spectrogram of a waveform are only suited for either relatively slow (&amp;lt;GHz bandwidth) waveforms of arbitrary duration or fast (&amp;gt;THz bandwidth) waveforms of short duration. It remains very challenging to capture the time-frequency representation of broadband waves extending over long durations, as required for many important fields in science and technology. Here, we introduce a linear optics temporal imaging concept based on electro-optic time-lensing and dispersive propagation to map the 2D spectrogram as a 1D waveform along the temporal domain. This technique enables ultra-broadband spectrogram analysis without any gaps in the acquisition and with no inherent limitation on maximum signal duration. The spectrogram is captured at unmatched processing rates, up to 16 × 109 Fourier transforms per second (∼60 ps per spectral frame), using a single photodetector and in a fully self-referenced manner. Under certain conditions, we show how this method enables the single-shot full-field characterization of optical waveforms spanning multiple THz. The method is further showcased through accurate amplitude and phase recovery of high-speed complex-modulated optical telecommunication signals using direct intensity detection. This concept will enable the study of physical phenomena unreachable to date and disruptive advancements in high-speed communications, sensing, and information processing.

A Novel Power Measurement Method Using Lock-In Amplifiers with a Frequency-Locked Loop

The extensive use of renewable energy systems with grid-connected inverters (GCIs) causes harmonic injection. Similarly, the imbalance in energy demand and supply causes frequency fluctuations. As a result of the increased harmonics and frequency fluctuations, the accuracy of power measurement using conventional methods continues to decline. Precision in power measurement is an essential factor for the billing and management of power supply and demand. Moreover, it is challenging to build a supply plan for the power demand and to manage the billing for the power consumption. To solve these problems, this paper proposes a novel method based on Lock-in Amplifier (LIA) and Lock-in Amplifier Frequency-Locked Loop (LIA-FLL) to measure the power with high precision and accuracy. The proposed method first tracks the variations in the input signal frequency using LIA-FLL and generates the updated reference signals for LIA. After that, the LIA is used to extract the accurate amplitude of each frequency component. The proposed method results in accurate and precise measurement, even with harmonics and frequency fluctuations. The validity of the proposed method is verified by comparing the power measurement results with the classical method, FFT, and ZERA COM3003 (a commercially available power measurement reference instrument).

An MPC based active and reactive power coordinated control strategy of PMSG wind turbines to enhance the support capability

As wind turbines are constantly replacing traditional units, it is becoming a consensus that wind turbines should participate in the grid support that was only responsible by traditional units in the past. In order to enhance the grid support capabilities (including active power support and reactive power support) of permanent magnet synchronous generator (PMSG) based wind turbines, this paper constructs an active and reactive power coordinated control strategy. Compared with the current active and reactive power coordinated control strategy of PMSG wind turbines, the method of the proposed one innovatively considers the climbing coordinated restriction between active and reactive power, flexible prioritization arrangement between active and reactive power, the accurate amplitude and climbing constraints of grid-side converters’ output voltage, and the model predictive control (MPC) technique. The simulation results verify that the proposed power control strategy can make PMSG wind turbines achieve excellent power output performance and thus better meet the requirements of power grid support.

Performance Analysis of Notch Filter in ECG Signal Noise Reduction

An electrocardiogram (ECG) is a medical test that records the normal and abnormal condition of the heart. It is an essential tool for identifying vari- ous cardiac related issues. However, ECG wave are often distorted by diverse noise sources, such as movement artifacts or electrical interference. To remove these artifacts and enhance the quality of the ECG signal, various filters are commonly used. The choice of filter type depends on the definite necessities of the application. FIR filters are used in the area that needs linear time response and accurate amplitude response. They have a stable and predictable response and are more robust to coefficient quantization errors. However, they require a larger number of coefficients to achieve the desired frequency response, which can lead to increased computational complexity. The use of digital filters, specifically notch filters, for denoising ECG signals is an effective technique. Adders are essential components in the design of notch filters, and researchers have been exploring different types of adders to improve the parameters of these filters. In this paper, the Ripple carry adder, Carry select Adder, and adder using Carry skip are compared in terms of their performance parame- ters, including area, delay, and power consumption. The RCA is a basic adder, while the C-Skip and C-Select adder are designed to reduce the delay of the addition operation. The results of the study showed that the C-Skip and C- Select adder outperformed the R-Carry adder in terms of delay and power con- sumption. The C-select adder had the lowest delay, while the C-Skip adder had the lowest power consumption. However, the area of the C-select Adder was larger compared to the other adders. Overall, the selection of adder depends on the particular need of the application. Notch filter used for ECG noise removal designed using these adders and its performance is analyzed.

Least‐squares reverse time migration with flux‐corrected transport technique

AbstractDue to high computational costs and memory requirements, it is necessary to use coarse grids for least‐squares reverse time migration when processing large‐scale field data. According to the dispersion relation, strong numerical dispersion will occur in least‐squares reverse time migration images when the migration velocity of the shallow strata is low, reducing the resolution of the migration results. To overcome this shortcoming, we propose new least‐squares reverse time migration implementation method with a modified flux‐corrected transport technique. This algorithm involves two main steps: obtain an appropriate calibration parameter for flux‐corrected transport through forward modelling and perform least‐squares reverse time migration using flux‐corrected transport. We remove the non‐linear processing from conventional flux‐corrected transport algorithm often used in computational fluid dynamics based on the assumption that the seismic wavefield is relatively continuous and smooth without strong ripples, which makes it possible to apply flux‐corrected transport to least‐squares reverse time migration without increasing too much computation complexity. To suppress the numerical dispersion more effectively, the diffusion fluxes along the diagonal direction are added to flux‐corrected transport. Numerical tests on synthetic data and field data illustrate that compared to the conventional least‐squares reverse time migration method, the proposed method produces images with fewer migration artefacts, more accurate amplitudes and faster convergence speed on the coarse grids.

A Systematic Approach to Design Amplitude Estimators for NTD-PLL: Performance Improvement Under Abnormal Grid Disturbances

Nonfrequency-dependent transport delay-phase-locked loop (NTD-PLL) is one of the simple grid synchronization approaches that aims to improve the phase and frequency estimation under frequency deviation. However, its amplitude estimation still exhibits double-frequency oscillations that are larger in magnitude as compared to the conventional transport delay (TD)-PLL counterpart. To overcome this challenge, two systematic approaches to design amplitude estimators (AEs) for NTD-PLL are presented in this article. One approach includes eliminating double-frequency oscillation error present in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{dq}$</tex-math></inline-formula> -frame component <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\boldsymbol{\upsilon }}_{\boldsymbol{d}}$</tex-math></inline-formula> , whereas another uses Pythagorean trigonometric identity in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{\alpha \beta }$</tex-math></inline-formula> -frame for accurate amplitude estimation. Due to the general form of AE proposed in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{\alpha \beta }$</tex-math></inline-formula> -frame, it can be easily applied in the design of other TD-based PLLs. The design aspects of these methods are discussed in detail, and the efficacy of the proposed structures is finally evaluated through numerical and experimental results. Some methods to enhance the performance of the AEs are explored and analyzed. This article provides useful insight to the designers regarding the advantages and disadvantages associated with the proposed AEs for their specific applications.

Toward earthquake early warning: A convolutional neural network for rapid earthquake magnitude estimation

Earthquake early warning (EEW) is one of the important tools to reduce the hazard of earthquakes. In contemporary seismology, EEW is typically transformed into a fast classification of earthquake magnitude, i.e., large magnitude earthquakes that require warning are in the positive category and vice versa in the negative category. However, the current standard information signal processing routines for magnitude fast classification are time-consuming and vulnerable to data imbalance. Therefore, in this study, Deep Learning (DL) algorithms are introduced to assist with EEW. For the three-component seismic waveform record of 7 s obtained from the China Earthquake Network Center (CENC), this paper proposes a DL model (EEWMagNet), which accomplishes the extraction of spatial and temporal features through DenseBlock with Bottleneck and Multi-Head Attention. Extensive experiments on Chinese field data demonstrate that the proposed model performs well in the fast classification of magnitude. Moreover, the comparison experiments demonstrate that the epicenter distance information is indispensable, and the normalization has a negative effect on the model to capture accurate amplitude information.

Application of Seismic Waveform Indicator Inversion in the Depth Domain: A Case Study of Pre-Salt Thin Carbonate Reservoir Prediction

Prestack depth-migrated seismic data, having more accurate imaging position and amplitude fidelity than prestack time-migrated seismic data, are supposed to produce a higher quality reservoir prediction result by using depth-domain inversion. Some researchers have developed different methods of depth-domain seismic inversion. However, it has not been widely used in the industry probably because of two reasons: (1) it is a complex process to conduct depth-domain seismic inversion due to the nonstationary depth-domain seismic wavelet; and (2) time-domain seismic inversion is considered capable of solving the problem with less cost, both in regard to time and the economy. In this paper, we try to use the seismic waveform indicator inversion method in the depth domain. First, a forward model was built to demonstrate that seismic waveforms both in the time domain and the depth domain are highly correlated with lithologic associations. Second, a quantitative evaluation method of seismic data for reservoir prediction was proposed, which can help geophysicists estimate time-domain and depth-domain inversion effects before inversion. Finally, the seismic waveform indicator inversion method was implemented for presalt thin carbonate reservoir prediction in the Central Block at the eastern margin of the Pre-Caspian Basin. The depth-domain inversion result shows a relatively true structure and higher resolution validated by wells.

Parameter Identification of Wheel Polygonization Based on Effective Signal Extraction and Inertial Principle

Violent interactions between wheel and rail caused by the polygonal wheels can strongly influence the operational comfort and safety of railway vehicles. It is an effective tool to dynamically detect wheel defects with the axle box acceleration signals. However, since the onboard vibration signals of the axle box are mixed with abundant noise from track irregularity and vehicle components, it is difficult to ensure the detection accuracy of the polygonal wheel. A novel strategy is proposed to extract the effective signal components and quantitatively identify the polygonal wheel parameters. First, the genetic mutation particle swarm optimization (GMPSO) algorithm is developed to search for optimization parameters of variational mode decomposition (VMD). Specifically, the minimum approximate entropy is adopted for the objective function, and the over-decomposition issue of VMD is addressed by the criterion of center frequencies ratio. Then, the independent components (ICs) are separated from VMD modes and the original signal by fast independent component analysis (FastICA). The dominated signal components related to the polygonal wheels can be decided by the proposed criterion. Finally, the order and amplitude of the wheel polygonal wear are obtained from the effective IC based on the inertial principle. The effectiveness of the proposed parameter identification algorithm is verified by the dynamics simulation and field test, and the estimation accuracy of wear amplitudes outperforms the comparison methods.

A probability density model of stress amplitude under bimodal vibration response

In order to improve the fatigue life prediction of engineering structures under bimodal vibration response stress power spectra, a new probability density model of stress amplitude is proposed in this paper, which is composed of an exponential distribution and a two-parameter Weibull distribution. Under ideal bimodal response stress power spectra with different bandwidths, the connection between the first three order moments of rain-flow amplitude distributions and the spectral parameters is found. Then, according to the equations between the first three order moments of stress amplitude distributions of the model and those of rain-flow amplitude distributions, combined with the numerical optimization method, the relationship between model parameters and spectral parameters is established. Through comparative studies, the model in this paper leads to more accurate stress amplitude distributions and fatigue damage, which is very close to those obtained from time domain approach. Through the stochastic vibration fatigue test of aluminum alloy notched specimens, the high accuracy of the proposed model for estimating fatigue life is further verified.

In-vivo along muscle fascicle strain heterogeneity is not affected by image registration parameters: Robustness testing of combined magnetic resonance-diffusion tensor imaging method

Coupled with diffusion tractography, non-rigid registration of high-resolution anatomical MR images allows the calculation of local strains along human skeletal muscle fascicles in-vivo. A reference study (passively imposed lengthening of gastrocnemius medial muscle) reported local shortening and lengthening occurring along the same muscle fascicles. However, the robustness of strain amplitudes and distribution patterns should be studied, as the heterogeneity of local length changes has major implications for muscle function. Using a previous image set of human medial gastrocnemius (GM) we aimed at testing: (1) the consistency of our MRI-DTI analysis workflow against changes made to the software environments, (2) the hypothesis that non-rigid demons algorithm tuning parameters (16 paired combinations were tested) are not a significant determinant of muscle fiber direction strain heterogeneity caused by passive knee extension. A profoundly altered analysis workflow did reproduce the original results well, showing a general pattern of proximally lengthened and distally shortened muscle fascicles (strain amplitude range: 21%–67%). Hierarchical shift function analyses and pairwise comparison of strain distributions between 10 equal parts of the tracked GM fascicles confirmed the hypothesis showing no significant effects of tuning parameters determining the in-vivo deformation field inhomogeneity. The findings show the robustness of the MRI-DTI method, and confirming the hypothesis, also the consistency of along muscle fascicle strain heterogeneity patterns against parameter selection. However, the strain amplitudes do vary with parameter choices. New studies are indicated to determine optimal tuning parameters to achieve accurate strain amplitudes compared to exact strains.

Development of a mathematical model of a frequency-controlled electromagnetic vibration motor taking into account the nonlinear dependences of the characteristics of the elements

The wider application of vibration machines (VM) with electromagnetic motors (EMVM) in various industries, including in vibration test benches for telecommunication devices and equipment has been studied in the paper. Difficulties associated with maintaining their productivity and efficiency at a given level are largely hindered. These factors mainly depend on the determination of the degree of influence of the nonlinearities of the input-output characteristics on the output values of the VM, the possibilities of tuning into the resonance mode, and the control of the output values while ensuring the energy-saving mode of operation of the EMVM. The mathematical model has been developed for a frequency-controlled EMVM taking into account the nonlinear dependencies of the characteristics of the elements, which makes it possible to determine the most accurate amplitude of oscillations of the EMVM working body when passing through resonance, observed with changes in the voltage frequency. The analysis of the physical processes of the influence of nonlinear elements of the electric circuit of the EMVM on the electromagnetic quantities and the derived analytical expressions of these nonlinearities, which make it possible to determine the harmonic composition of the current of the EMVM winding, are made. The system of vector control of the EMVM and the inclusion of a mathematical model of the engine into the control system have been developed, which will allow calculating the frequencies of free oscillations of the working body for tuning into the resonance mode.

Assessment and application of optical flow in background-oriented schlieren for compressible flows

Optical flow provides an opportunity to elevate the resolution and sensitivity of deflection sensing in background-oriented schlieren (BOS). Despite extensive relevant literature within the field of computer vision, there is a lack of proper quantification of its abilities and limitations with regard to the state-of-the-art BOS experiments. Thus, this study performs an assessment of accuracy and resolution limits in different flow field scenarios utilizing background patterns generated with random dot and wavelet noise distributions. Accordingly, a synthetic assessment over a theoretically generated Prandtl–Meyer expansion fan is conducted with variations introduced in the background patterns and operational parameters of optical flow. A clear superiority of accuracy and resolvable range of density gradient amplitudes over cross-correlation is demonstrated. Moreover, an experimental assessment of supersonic flow features over multiple wind tunnel models is performed. The influence of experimental constraints, limitations and uncertainties related to the application of optical flow in BOS and its comparative performance against the block-matching counterpart is characterized.Graphical abstract

A novel tacholess order tracking method for gearbox vibration signal based on extremums search of gearmesh harmonic

Computed order tracking (COT) is an effective vibration analysis method for mechanical equipment operating at time-varying speed. The principle is to resample the time-domain sampled vibration data under the guidance of angle information of reference shaft. The rotation angle obtained from numerical integration is generally limited by the deviation of integration on rotation speed. To address this problem, a novel acquisition method of rotation angle is proposed to improve the precision of order tracking analysis. Based on the equi-angular relationship between adjacent peaks of a single gearmesh harmonic, the discrete shaft phase vs time map is directly established by obtaining the peak time. The process error is thoroughly investigated, and a designed scheme is provided to eliminate the effects of discrete sampling and amplitude modulation. Theoretically, the rotation angle can be correctly depicted, which is useful for a highly precise order-tracking analysis. The accurate amplitude and high condensed spectral lines of order spectrum are achieved both in the simulation and experiment signals, which verified the effectiveness and robustness of the proposed method. It is helpful for the accurate reconstruction of speed-related vibration signal in the order spectrum, and enhances the capability of condition monitoring on gear systems.