Zero-crossing Algorithm Research Articles

Thermal stress estimation of a constrained metallic plate using symmetric and antisymmetric Lamb wave group velocities

This paper presents a technique for estimating thermal-induced stress in constrained metallic plates using the group velocity of Lamb waves, the accuracy of which is crucial for assessing the structural integrity and serviceability of metallic structures. However, without the ability to gauge the current stress levels, obtaining such measurements is technically challenging. To overcome this, we propose a thermal stress estimation technique that uses changes in the group velocities of the fundamental symmetric (S0) and antisymmetric (A0) Lamb wave modes caused by thermal and stress variations. First, this study introduces a theoretical-based zero-crossing algorithm to measure the group velocities of S0 and A0 Lamb wave modes. Next, leveraging the acoustoelastic coefficients corresponding to the S0 and A0 modes, which are determined before the plate’s installation, this study generates the lines depicting the changes in group velocity induced by temperature variations (CT) for both the S0 and A0 modes. These CT lines are derived from the lines illustrating changes in group velocity due to thermal stress variations (CTS), which are obtained after plate installation. Ultimately, the generated CT lines can be used to estimate thermal stress throughout the entirety of the plate’s operational life span by isolating the distinct stress variation effects from the CTS lines. The numerical validation results show favorable accuracy in thermal stress estimation in a constrained plate subjected to temperature variation using both S0 and A0 Lamb wave modes, with average errors of 0.63 % and 0.91 %, respectively.

Validation of Automatically Quantified Swim Stroke Mechanics Using an Inertial Measurement Unit in Paralympic Athletes.

Biomechanics and training load monitoring are important for performance evaluation and injury prevention in elite swimming. Monitoring of performance and swim stroke parameters is possible with inertial measurement units (IMU) but has not been validated in para-swimmers. The purpose of this study was to validate a single IMU-based system to accurately estimate pool-swam lap time, stroke count (SC), stroke duration, instantaneous stroke rate (ISR), and distance per stroke (DPS). Eight Paralympic athletes completed 4 × 50 m swims with an IMU worn on the sacrum. Strokes cycles were identified using a zero-crossing algorithm on the medio-lateral (freestyle and backstroke) or forward-backward (butterfly and breaststroke) instantaneous velocity data. Video-derived metrics were estimated using Dartfish and Kinovea. Agreement analyses, including Bland-Altman and Intraclass Correlation Coefficient (ICC), were performed on all outcome variables. SC Bland-Altman bias was 0.13 strokes, and ICC was 0.97. ISR Bland-Altman biases were within 1.5 strokes/min, and ICCs ranged from 0.26 to 0.96. DPS Bland-Altman biases were within 0.20 m, and ICCs ranged from 0.39 to 0.93. A single-IMU system can provide highly valid performance and swim stroke monitoring data for elite para-swimmers for the majority of strokes, with the exception of backstroke. Future work should improve bilateral stroke detection algorithms in this population.

Measurements of nearshore ocean-surface kinematics through coherent arrays of free-drifting buoys

Abstract. Surface gravity wave breaking occurs along coastlines in complex spatial and temporal patterns that significantly impact erosion, scalar transport, and flooding. Numerical models are used to predict wave breaking and associated processes but many lack sufficient evaluation with observations. To fill the need for more nearshore wave measurements, we deployed coherent arrays of small-scale, free-drifting buoys named microSWIFTs. The microSWIFT is a small buoy equipped with a GPS module to measure the buoy's position, horizontal velocities, and an inertial measurement unit (IMU) to directly measure the buoy's rotation rates, accelerations, and heading. Measurements were collected over a 27 d field experiment in October 2021 at the US Army Corps of Engineers Field Research Facility in Duck, NC. The microSWIFTs were deployed as a series of coherent arrays, meaning they all sampled simultaneously with a common time reference, leading to a rich spatial and temporal dataset during each deployment. Measurements spanned offshore significant wave heights ranging from 0.5 to 3 m and peak wave periods ranging from 5 to 15 s over the entire experiment. The completed dataset consists of 67 deployment files that contain 971 drift tracks that contain all associated data. We use an attitude and heading reference system (AHRS) 9-degrees-of-freedom Kalman filter to rotate the measured accelerations from the reference frame of the buoy to the Earth reference frame. We then use the corrected accelerations to compute the vertical velocity and sea-surface elevation. We give example evaluations of wave spectral energy density estimates from individual microSWIFTs compared with a nearby acoustic wave and current (AWAC) sensor. A zero-crossing algorithm is applied to each buoy time series of sea-surface elevation to extract realizations of measured surface gravity waves, yielding 116 307 wave realizations throughout the experiment. We also compute significant wave height estimates from the aggregate wave realizations and compare these estimates with the nearby AWAC estimates. An example of spatial variability in cross-shore velocity and vertical acceleration is explored. Wave-breaking events, detected by high-intensity vertical acceleration peaks, are explored, and the cross-shore distribution of all breaking events detected in the experiment is shown. A total of 3419 wave-breaking events were detected across the entire experiment. These data are available at https://doi.org/10.5061/dryad.hx3ffbgk0 (Rainville et al., 2023) and will be used to investigate nearshore wave kinematics, transport of buoyant particles, and wave-breaking processes.

A Differential Confocal Sensor for Simultaneous Position and Slope Acquisitions Based on a Zero-Crossing Prediction Algorithm.

A new sensor type is proposed to accurately detect the surface profiles of three-dimensional (3D) free-form surfaces. This sensor is based on the single-exposure, zero-crossing method and is used to measure position and angle simultaneously. First, the field intensity distribution in the posterior focal plane of the confocal microscope's objective was modeled accurately. Second, because the camera needs to trigger acquisition when the surface (to be measured) reaches the focal position of the sensor, a zero-crossing prediction method based on a sliding window was proposed. Third, a fast, spatially convergent, peak-extraction algorithm was proposed to improve the accuracy and efficiency of peak extraction. This scheme reduces system installation and adjustment difficulties, and the single-exposure, zero-crossing method achieves high-speed, real-time image acquisitions. The experimental results indicate that the average error of the zero-crossing prediction system was 17.63 nm, the average error of the tilt degree measurement was 0.011° in the range of 0-8°, and the prediction error of the tilt direction measurement was 0.089° in the range of 0-360°. The sensor can measure the slope and can be potentially used for 3D surface precision detection.

Zero-Additional-Hardware Power Line Communication for DC–DC Converters

A power line communication (PLC) solution to provide a data link between two or more dc–dc power converters is proposed. The approach does not require additional analog circuitry or high-sample-rate analog-to-digital converters to be added on top of the original system. A modulation and signal injection method for the transmitter, and a sampling and demodulation strategy for the receiver are developed. The PLC frequency band is placed between the control loop cutoff frequency and the power electronics circuit cutoff frequency, in a region that we identify as the “intermediate frequency band”. The transmitter modulates the converter voltage or current output by injecting perturbations into the control loop at the input to the PWM unit. To tolerate unsynchronized transmitter and receiver clocks, a virtual zero-crossing location algorithm is combined with long/short pulse identification to achieve demodulation at the receiver. The solution is verified experimentally and achieves reliable bidirectional PLC communication at 2 kb/s with an 8 kHz receiver sampling frequency.

Grid Frequency Measurement through a PLHR Analysis Obtained from an ELF Magnetometer.

The stability of the power grid’s frequency is crucial for industrial, commercial, and domestic applications. The standard frequency in Europe’s grid is 50 Hz and it must be as stable as possible; therefore, reliable measurement is essential to ensure that the frequency is within the limits defined in the standard EN 50160:2010. In this article, a method has been introduced for the measurement of the grid frequency through a power line harmonics radiation analysis. An extremely low-frequency magnetometer was developed with the specific purpose of monitoring, in real time, the electromagnetic field produced by electrical installations in the range from 0 to 2.2 kHz. Zero-crossing and Fast Fourier transform algorithms were applied to the output signal to calculate the grid frequency as a non-invasive method. As a final step, data for a complete month (May 2021) were compared with a commercial power quality analyzer connected to the main line to validate the results. The zero-crossing algorithm gave the best result on 3 May 2021, with a coefficient of determination (R2) of 0.9801. Therefore, the indirect measurement of the grid frequency obtained through this analysis satisfactorily fits the grid frequency.

Research and implementation of a highly reliable transient and same source data comparison method based on fault recorder documents

Abstract The existing fault recording analysis system has powerful functions in the analysis of fault characteristic factors such as waveform analysis, vector analysis, and harmonic analysis. However, it uses redundant fault recording data to analyze, compare and locate faults in the power system. Rarely involved, far from reaching the level it should be, and even wasting fault recording data with large amounts of data and rich information content. A highly reliable transient homology data comparison based on recording files is given. Analytical method. Introduced the comparison method of the recording data from the same source, the content involves how to match the channel waveform of fault recorder documents, how to use the zero-crossing algorithm to align, how to find the starting point of the protection action through the mutation amount algorithm, and how to pass the cubic spline The interpolation algorithm obtains valid data, how to compare the valid data, and finally obtain the comparison result, and give advice on operation and maintenance.

Secure image hiding in speech signal by steganography-mining and encryption

<span>Information hiding techniques are constantly evolving due to the increased need for security and confidentiality. This paper proposes a working mechanism in three phases. The first phase includes scrambling the values of the gray image depending on a series of keys that are generated using a quantum chaotic map. The second phase generates hybrid keys by mixing a Zaslavsky and a 3D Hanon map that are used to encrypt the gray image values produced after the scramble. Finally, in the third phase, a new algorithm is suggested to hide the encrypted gray image at random locations within a speech file. This algorithm includes the LSB algorithm to determine the hidden bits and the zero-crossing K-means algorithm in selecting locations mining in a scattered manner so that hackers cannot easily retrieve the hidden data of any hacked person. Also used a fractional fourier transform to choose magnitude value as specific data to hide encoded image data. The measures MSE, PSNR, NSCR, and UACI are using to measure the work efficiency in the encryption algorithm, and in measuring the efficiency of the hidden algorithm, use the measures SNR, PSNR, and MSE. The results of the paper are encouraging and efficient compared to other algorithms that performed the same work. Hence our results show the larger the image dimensions used, the better the values.</span>

Robust Intra-Body Communication Using SHA1-CRC Inversion-Based Protection and Error Correction for Securing Electronic Authentication.

The explosive increase in the number of IoT devices requires various types of communication methods. This paper presents secure personal authentication using electrostatic coupling Intra-body communication (IBC) based on frequency shift keying (FSK) and error correction. The proposed architecture uses GPIO for a transmitter and analog-to-digital conversion (ADC) for a receiver. We mplemented FSK modulation, demodulation, data protection, and error correction techniques in the MCU software without applying hardware devices. We used the characteristic that the carrier signal is 50% duty square wave for 1-bit error correction and applied a method of randomly inverting SHA1 hash data to protect user authentication data during transmission. The transmitter modulates binary data using a square wave as a carrier signal and transmits data through the human body. The receiver demodulates the signal using ADC and decrypts the demodulated binary data. To determine the carrier frequency from ADC results, we applied a zero-crossing algorithm which is used to detect edge characteristics in image processing. When calculating the threshold value within the zero-crossing algorithm, we implemented an adaptive threshold setting technique utilizing Otsu’s binarization technique. We found that the size of the electrode pad does not affect the signal strength, but the distance between the electrode pad and the skin has a significant effect on the signal strength. Our results show that binary data modulated with a square wave can be successfully transmitted through the human body, and, when 1-bit error correction is applied, the byte error rate on the receiver side is improved around 3.5% compared to not applying it.

Modeling and Optimization for Fault Diagnosis of Electromechanical Systems Based on Zero Crossing Algorithm

The demand of system security and reliability in the modern industrial process is ever-increasing, and fault diagnosis technology has always been a crucial research direction in the control field. Due to the complexity, nonlinearity, and coupling of multitudinous control systems, precise system modeling for fault diagnosis is attracting more attention. In this paper, we propose an improved method of electromechanical systems fault diagnosis based on zero-crossing (ZC) algorithm, which can present the calculation model of zero-crossing rate (ZCR) and optimize the parameters of ZC algorithm by establishing a criterion function model to improve the diagnosis accuracy and robustness of ZC characteristic model. The simulation validates the influence of different signal-to-noise ratio (SNR) on ZC feature recognition ability and indicates that the within-between distance model is effective to enhance the diagnose accuracy of ZC feature. Finally, the method is applied to the diagnosis of motor fault bearing, which confirms the necessity and effectiveness of the model improvement and parameter optimization and verifies the robustness to the load.

A zero-crossing point prediction algorithm of short-circuit current for mine-used phase-controlled switching

A zero-crossing point prediction algorithm of short-circuit current for mine-used phase-controlled switching

Recent Development of Frequency Estimation Methods for Future Smart Grid

The frequency estimated by the Phasor Measurement Unit (PMU) is a critical index of power system status and supports many smart grid applications. The future smart grid features high penetration of renewables and more fast-moving power electronics inverters but raises challenges to the reliable frequency estimation. This article presents three methods to address these challenges. First, an enhanced zero-crossing algorithm was developed to track the fast-changing frequency in system dynamics. Second, we propose a technology that can tolerate the system transient and suppress the outliers. Third, an algorithm was developed to export high time-resolution frequency estimations with minimum computational effort. All of the proposed methods are realized in hardware and compared with classical frequency estimation methods. The testing results indicate that the proposed methods have excellent performance. They can be used in future PMUs and provide reliable and high time resolution data for smart grid applications.

Optimized breath detection algorithm in electrical impedance tomography

Objective: This paper defines a method for optimizing the breath delineation algorithms used in electrical impedance tomography (EIT). In lung EIT the identification of the breath phases is central for generating tidal impedance variation images, subsequent data analysis and clinical evaluation. The optimisation of these algorithms is particularly important in neonatal care since the existing breath detectors developed for adults may give insufficient reliability in neonates due to their very irregular breathing pattern. Approach: Our approach is generic in the sense that it relies on the definition of a gold standard and the associated definition of detector sensitivity and specificity, an optimisation criterion and a set of detector parameters to be investigated. The gold standard has been defined by 11 clinicians with previous experience with EIT and the performance of our approach is described and validated using a neonatal EIT dataset acquired within the EU-funded CRADL project. Main results: Three different algorithms are proposed that improve the breath detector performance by adding conditions on (1) maximum tidal breath rate obtained from zero-crossings of the EIT breathing signal, (2) minimum tidal impedance amplitude and (3) minimum tidal breath rate obtained from time-frequency analysis. As a baseline a zero-crossing algorithm has been used with some default parameters based on the Swisstom EIT device. Significance: Based on the gold standard, the most crucial parameters of the proposed algorithms are optimised by using a simple exhaustive search and a weighted metric defined in connection with the receiver operating characterics. This provides a practical way to achieve any desirable trade-off between the sensitivity and the specificity of the detectors.

IMU-based gait analysis in lower limb prosthesis users: Comparison of step demarcation algorithms

BackgroundInertial Measurement Unit (IMU)-based gait analysis algorithms have previously been validated in healthy controls. However, little is known about the efficacy, performance, and applicability of these algorithms in clinical populations with gait deviations such as lower limb prosthesis users (LLPUs). Research questionTo compare the performance of 3 different IMU-based algorithms to demarcate steps from LLPUs. MethodsWe used a single IMU sensor affixed to the midline lumbopelvic region of 17 transtibial (TTA), 16 transfemoral (TFA) LLPUs, and 14 healthy controls (HC). We collected acceleration and angular velocity data during overground walking trials. Step demarcation was evaluated based on fore-aft acceleration, detecting either: (i) maximum acceleration peak, (ii) zero-crossing, or (iii) the peak immediately preceding a zero-crossing. We quantified and compared the variability (standard deviation) in acceleration waveforms from superposed step intervals, and variability in step duration, by each algorithm. ResultsWe found that the zero-crossing algorithm outperformed both peak detection algorithms in 65% of TTAs, 81% of TFAs, and 71% of HCs, as evidenced by lower standard deviations in acceleration, more consistent qualitative demarcation of steps, and more normally distributed step durations. SignificanceThe choice of feature-based algorithm with which to partition IMU waveforms into individual steps can affect the quality and interpretation of estimated gait spatiotemporal metrics in LLPUs. We conclude that the fore-aft acceleration zero-crossing serves as a more reliable feature for demarcating steps in the gait patterns of LLPUs.

Carbon Cantilever Beam Health Inspection Using a Polymer Fiber Bragg Grating Array

We demonstrate a quasi-distributed sensor for cantilever health inspection measurements using a fiber Bragg grating (FBG) array inscribed in a polymer optical fiber. The FBGs were characterized and calibrated for axial strain, temperature, and relative humidity prior to their mounting on a carbon cantilever beam, the tail rotor of a helicopter. By using the zero-crossing demodulation algorithm, we recovered the time-dependent, wavelength response from each Bragg grating sensor and the vibration response of the beam was extracted. We used the response of the beam to study how the addition of masses at different positions on the beam influences the vibrational behavior and mimics the location of “damage” through the time-dependent results. We show that health inspection measurements are feasible with polymer-based fiber Bragg gratings, offering accurate and rapid detection of damage points on a structural beam.

A Charge-Redistribution Phase-Domain ADC Using an IQ-Assisted Binary-Search Algorithm

Phase-domain Analog-to-Digital Converters (Ph-ADCs) have been considered for power-efficient implementa-tion of body-area network transceivers employing phase demodulation. Conventional implementations of the Ph-ADCs, which work based on a full-flash zero-crossing algorithm, use linear resistive/current combiners to determine the thermometer digital code of the signal phase. These architectures suffer from high-accuracy requirements, high-circuit complexity, and high-power consumption. Therefore, in this paper, a new IQ-assisted binary-search algorithm is proposed for implementing the Ph-ADC. The proposed Ph-ADC architecture avoids employing the power-hungry linear combiner. Moreover, for an $N$ -bit Ph-ADC, the proposed algorithm requires only $N +1$ comparisons, whereas the conventional full-flash counterpart demands $2^{N-1}$ comparisons. Based on the proposed architecture, two different 5-bit charge-redistribution Ph-ADC s are designed and one of them is fabricated in a standard 0.18- $\mu \text{m}$ CMOS technology. The prototype achieves an ENOB of 4.85 bits at 1 MS/s, while dissipating $12.9~\mu \text{W}$ from a 1.2-V supply.

A Power Frequency Sensing Device Using an Arduino Device and Zero-Crossing Algorithm and Its Implementation on Android App

A Power Frequency Sensing Device Using an Arduino Device and Zero-Crossing Algorithm and Its Implementation on Android App

Road-frequency adaptive control for semi-active suspension systems

In this paper, a road-frequency adaptive control for semi-active suspension systems is investigated. The control aims to improve the vehicle suspension performance (ride comfort and wheel handling) for all frequency regions of road disturbances. In order to achieve this aim, the control law is extended from the conventional skyhook control, and the controller gains are scheduled for various frequency regions of road disturbances. By using the data measured from a relative displacement sensor, a state estimator based on a Kalman filter for estimating the required state variables is designed. Road disturbance frequencies are estimated by using a first order zero-crossing algorithm. The efficiency of the proposed control is shown through numerical simulations.

Multidimensional Separation of Chiral Amino Acid Mixtures in a Multilayered Three-Dimensional Hybrid Microfluidic/Nanofluidic Device

Microscale total analysis systems (microTAS) allow high-throughput analyses by integrating multiple processes, parallelization, and automation. Here we combine unit operations of microTAS to create a device that can perform multidimensional separations using a three-dimensional hybrid microfluidic/nanofluidic device composed of alternating layers of patterned poly(methyl methacrylate) and nanocapillary array membranes constructed from nuclear track-etched polycarbonate. Two consecutive electrophoretic separations are performed, the first being an achiral separation followed by a chiral separation of a selected analyte band. Separation conditions are optimized for a racemic mixture of fluorescein-isothiocyanate-labeled amino acids, serine and aspartic acid, chosen because there are endogenous D-forms of these amino acids in animals. The chiral separation is implemented using micellar electrokinetic chromatography using beta-cyclodextrin as the chiral selector and sodium taurocholate as the micelle-forming agent. Analyte separation is monitored by dual-beam laser-induced fluorescence detection. After separation in the first electrophoretic channel, the preselected analyte is sampled by the second-stage separation using an automated collection sequence with a zero-crossing algorithm. The controlled fluidic environment inherent to the three-dimensional architecture enables a series of separations in varying fluidic environments and allows sample stacking via different background electrolyte pH conditions. The ability to interface sequential separations, selected analyte capture, and other fluidic manipulations in the third dimension significantly improves the functionality of multilayer microfluidic devices.

Perceptual features for automatic speech recognition in noisy environments

The performances of two perceptual properties of the peripheral auditory system, synaptic adaptation and two-tone suppression, are compared for automatic speech recognition (ASR) in an additive noise environment. A simple method of synaptic adaptation as determined by psychoacoustic observations was implemented with temporal processing of speech utilizing a zero-crossing auditory model as a pre-processing front end. The concept is similar to RASTA processing, but instead of bandpass filters, a high-pass infinite impulse response (IIR) filter is used. It is shown that rapid synaptic adaptation may be implemented by temporal processing using the zero-crossing algorithm, not otherwise implementable in the spectral domain implementation. The two-tone suppression was implemented in the zero-crossing auditory model using a companding strategy. Recognition performances with the two perceptual features were evaluated on isolated digits (TIDIGITS) corpus using continuous density HMM recognizer in white, factory, babble and Volvo noise. It is observed that synaptic adaptation performs better in stationary white Gaussian noise. In presence of non-stationary non-Gaussian noise, however, no improvements or a degradation is observed. Moreover, a reciprocal effect is observed with two-tone suppression, with better performance in non-Gaussian real-world noise and degradation in stationary white Gaussian noise.