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At least 1,243 records · Page 69

Adaptive Envelope Detector-Based Phase Fault Detection Method for Power System Grid Distortions

In this study, a phase fault detection algorithm is developed by employing the envelope detector method. The proposed method diagnoses faults among phases and defines fault areas in the incoming signal. The designed algorithm consists of three steps: analytical signal conversion, complex magnitude, and fault detection. Initially, an analytical signal is obtained from the incoming power signal to determine the instantaneous amplitude and phase of the signal. A complex magnitude operation is applied to analytical signals to display changes in amplitude. On the basis of the threshold values specified by the user, the last step identifies the distortion signal in terms of the type of error and size. The proposed method is tested with realistically simulated substation power signal data and real power system data from the Grid Event Signature Library. The obtained results revealed that the proposed method detects distortions accurately.

Alaca, Ozgur↗

Precise Timing Based on Pulsar Observation for Grid Synchronization

While Global Positioning System signals are widely used as the synchronized timing Sources for wide-area measurement systems for power grid monitoring and control, they are vulnerable to failures and malicious attacks. To address this Problem, an alternative kind of timing sources, the millisecond pulsars, were proposed to serve the power grid as they are more precise and physically indestructible. Millisecond pulsars are a kind of neutron stars that emit radio pulse signals that have extremely stable periods of milliseconds. However, the observed pulse Signals from pulsars cannot be directly used for timing because of their low signal-to-noise ratio and the dispersion effects of interstellar medium. In this paper, the precise timing method based on pulsar observation data is proposed to interpret the pulsar observation data and therefrom to generate precise timing signal for the power grid synchronization. In our proposed method,. incoherent de-dispersion is used on the observation data to mitigate the effect of interstellar medium. dispersion. Then spectrum analysis and segment folding are used to precisely estimate the local pulsar period. Finally the standard pulse per second signal is generated from. the estimated pulsar period and its precision. is analyzed. Experiments with the observation data of the pulsar based timing signal can be more accurate compared to GPS timing signals.

Luo, Xiqian↗

Designing an Intrusion Proof Adjustable Speed Drive System Controlling a Critical Process

In this paper, an intrusion proof adjustable speed drive system controlling a critical process in an industrial control system is detailed. In such a system, should the motor speed sensor signal data be compromised and/or altered via a cyber-attack, the system can potentially be unregulated, over speed and/or malfunction thereby disrupting the critical process. The proposed active detection scheme detailed in this paper introduces a private (secret) random signal termed as "watermark" into the inverter control signal that determines the PWM gating signals of the DC-AC inverter powering the motor. The watermarking signal introduced into the PWM modulation for the DC-AC inverter is shown to propagates its unique signature, which appears in all sensors signals at the inverter output such as voltage/current/speed used to control the motor. Now employing the measured data (from sensors), two statistical variance tests are conducted to identify anomalies if any in the presence of the watermarking signal. It is shown when an intrusion occurs to manipulate the sensor data to disturb and/or destabilize the process, the proposed tests immediately display a high value indicating a compromise in sensor data. It is shown that the proposed system is capable of immediate detection of a sophisticated attacks such as record/reply attack in which the actual speed sensor is disconnected and a prerecorded speed signal from the past of the same magnitude is played back to the controller. Several types of cyber-attacks such as speed reduction/increase including vibration have been tested. Extensive simulation results verify the proposed concepts. Experimental results will be discussed in the conference presentation.

Alotaibi, Faris↗

Subseasonal Variability of U.S. Coastal Sea Level from MJO and ENSO Teleconnection Interference

Abstract Climate variability affects sea levels as certain climate modes can accelerate or decelerate the rising sea level trend, but subseasonal variability of coastal sea levels is underexplored. This study is the first to investigate how remote tropical forcing from the MJO and ENSO impact subseasonal U.S. coastal sea level variability. Here, composite analyses using tide gauge data from six coastal regions along the U.S. East and West Coasts reveal influences on sea level anomalies from both the MJO and ENSO. Tropical MJO deep convection forces a signal that results in U.S. coastal sea level anomalies that vary based on MJO phase. Further, ENSO is shown to modulate both the MJO sea level response and background state of the teleconnections. The sea level anomalies can be significantly enhanced or weakened by the MJO-associated anomaly along the East Coast due to constructive or destructive interference with the ENSO-associated anomaly, respectively. The West Coast anomaly is found to be dominated by ENSO. We examine physical mechanisms by which MJO and ENSO teleconnections impact coastal sea levels and find consistent relationships between low-level winds and sea level pressure that are spatially varying drivers of the variability. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts. Significance Statement Coastal flooding due to sea level rise is increasingly threatening communities, but natural fluctuations of coastal sea levels can exacerbate the human-caused sea level rise trend. This study assesses the role of tropical influences on coastal subseasonal (2 weeks–3 months) sea level heights. Further, we explore the mechanisms responsible, particularly for constructive interference of signals contributing to coastal flooding events. Subseasonal signals amplify or suppress the lower-frequency signals, resulting in higher or lower sea level heights than those expected from known climate modes (e.g., ENSO). Low-level onshore winds and reduced sea level pressure connected to the tropical phenomena are shown to be indicators of increased U.S. coastal sea levels, and vice versa. Two case studies reveal how MJO and ENSO teleconnection interference played a role in notable coastal flooding events. Much of the focus on sea level rise concerns the long-term trend associated with anthropogenic warming, but on shorter time scales, we find subseasonal climate variability has the potential to exacerbate the regional coastal flooding impacts.

Meteorology & Atmospheric Sciences↗

Denoising Seismic Waveforms Using a Wavelet-Transform-Based Machine-Learning Method

Seismic waveform data recorded at stations can be thought of as a superposition of the signal from a source of interest and noise from other sources. Frequency‐based filtering methods for waveform denoising do not result in desired outcomes when the targeted signal and noise occupy similar frequency bands. Recently, denoising techniques based on deep‐learning convolutional neural networks (CNNs), in which a recorded waveform is decomposed into signal and noise components, have led to improved results. These CNN methods, which use short‐time Fourier transform representations of the time series, provide signal and noise masks for the input waveform. These masks are used to create denoised signal and designaled noise waveforms, respectively. However, advancements in the field of image denoising have shown the benefits of incorporating discrete wavelet transforms (DWTs) into CNN architectures to create multilevel wavelet CNN (MWCNN) models. The MWCNN model preserves the details of the input due to the good time–frequency localization of the DWT. In this report we use a data set of over 382,000 constructed seismograms recorded by the University of Utah Seismograph Stations network to compare the performance of CNN and MWCNN‐based denoising models. Evaluation of both models on constructed test data shows that the MWCNN model outperforms the CNN model in the ability to recover the ground‐truth signal component in terms of both waveform similarity and preservation of amplitude information. Model evaluation of real‐world data shows that both the CNN and MWCNN models outperform standard band‐pass filtering (BPF; average improvement in signal‐to‐noise ratio of 9.6 and 19.7 dB, respectively, with respect to BPF). Evaluation of continuous data suggests the MWCNN denoiser can improve both signal detection capabilities and phase arrival time estimates.

58 GEOSCIENCES↗

VPS26 Moonlights as an Arrestin-like Adapter for a 7-transmembrane RGS 2 protein in Arabidopsis thaliana

Extracellular signals perceived by 7-transmembrane (7TM)-spanning receptors on the plasma membrane utilize a cytoplasmic adaptor that propagates signaling and initiates a feedback circuit for desensitization by removal of these receptors at the plasma membrane leading to desensitization to that signal. Signal (agonist) binding often evokes phosphorylation at the C-terminal tail of many 7TM G-protein-coupled receptors in animal cells which then recruits a cytoplasmic intermediate adaptor, β-arrestin, that sets in motion clathrin-mediated endocytosis (CME). Some 7TM receptors have agonist-induced phosphorylation and CME that do not involve β-arrestin, therefore it is unclear how these phosphorylated 7TM receptors are internalized. Arrestins, neither α– or β-types, are not encoded in the Arabidopsis genome, yet Arabidopsis cells have a well characterized signal-induced CME of a 7TM protein, Regulator of G Signaling 1 (AtRGS1). We show that a component of the retromer complex, VPS26, moonlights as an arrestin-like adapter. VPS26A and VPS26B form heterodimer instead of homodimer or monomer. flg22, a bacterium-derived signal that alerts plant cells of the presence of a potential pathogen, induces phosphorylation of AtRGS1 within a cluster of serines in its C-terminal tail, dimerization, and its CME. The phosphorylated C-terminal tail peptide binds to VPS26A/B heterodimer with greater affinity than the unphosphorylated peptide. We propose that VPS26 serves as an arrestin-like adaptor in the CME of AtRGS1 dimerization biased for VPS26 signaling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Nondestructive Evaluation (NDE) of Cable Anomalies using Frequency Domain Reflectometry (FDR) and Spread Spectrum Time Domain Reflectometry (SSTDR)

This report presents a comparative assessment of the performance of frequency domain reflectometry (FDR) and spread spectrum time domain reflectometry (SSTDR) in detecting a wide range of electrical cable anomalies. All tests and results reported herein were performed at the PNNL Accelerated and Real-Time Environmental Nodal Assessment (ARENA) cable and motor test bed. The primary objective of this work was to evaluate the effectiveness of SSTDR, a fledgling cable monitoring technique that shows promise for application in online monitoring of energized cable systems, against FDR, an offline technique widely employed in the nuclear power plant (NPP) industry. FDR tests are becoming more widely used in nuclear power plant cable aging management and test programs – particularly for low voltage cables. FDR capabilities for these kinds of tests have been reported by PNNL and others. The FDR test is performed on de-energized cables by connecting the FDR instrument to two of the cable conductors, or one conductor and the shield. A broad band low voltage (< 5 V) chirp is introduced in the cable, and any reflected response is captured in the frequency domain. The captured reflection is then processed by performing an inverse Fourier transform to a time domain response which can then be converted to a distance response based on the cable velocity of propagation (VoP). SSTDR measurements are functionally similar to FDR measurements in that a broad-band voltage signal composed of a square or sine wave modulated pseudo-random sequence of chips (< 5 volts), is injected onto one of the cable conductors. The injected signal will experience partial energy reflection and transmission at each impedance discontinuity along the transmission line. Any reflected response is detected by computing a cross-correlation between the reflected signals and a delayed copy of the incident SSTDR signal. the time delay for the reflected signal to experience the best matched correlation with the incident signal, indicates the travel time for the signal to reach a change in impedance. By knowing this time delay and velocity of propagation (VoP) of the signal, one can compute the physical distance. A big advantage that SSTDR measurements have over other methods is the ability to be connected to energized or live wires (currently up to 1kV) thereby enabling online monitoring of cables. SSTDR has been used successfully in several applications, e.g., aircraft, rail, and photovoltaic systems. In this work FDR and SSTDR cable assessment techniques were used to characterize a variety of cable anomalies and faults including: (1) Presence or absence of a motor; (2) Ground faults and short circuit faults; (3) Moist environments and water ingress faults; (4) Accelerated thermal aging. Both shielded and non-shielded cables were evaluated in this report. Offline measurements were made using FDR and online measurements were made by SSTDR for a range of test scenarios. Based on the results across all cable anomalies evaluated in this study, FDR displayed high sensitivity towards cable condition assessment, while SSTDR showed promise for future application in monitoring NPP cable systems. However, further developments are suggested to improve the resolution and sensitivity of SSTDR towards faults and anomalies in low voltage cables.rt presents a comparative

42 ENGINEERING↗

System and method for all optical electrode interface for bioengineering application

The present disclosure relates to an electro-optical modulator system having a source laser which generates an input optical signal. The input optical signal is received by an electro-optical module. The electro-optical module is implantable into an anatomy and includes a plurality of pixels. Each pixel has associated therewith an electrode and an optical modulator subsystem. The electrode receives electrical signals from the anatomy. The optical modulator subsystem receives the input optical signal and modulates the input optical signal to generate modulated optical output signals in relation to the received electrical signals. A detector subsystem may be used to receive and collect the modulated optical output signals.

Patra, Susant K.↗

Hardware intrusion detection system

An apparatus for intrusion detection includes processing circuitry, a switch, signal detection circuitry, and an analog-to-digital converter (“ADC”). The processing circuitry is coupled to send a challenge signal to a device when the device is coupled to the processing circuitry. The switch is coupled to be enabled and disabled by the processing circuitry. The switch is for coupling to the device to receive a response signal in response to the challenge signal sent by the processing circuitry. The signal detection circuitry is coupled to receive the response signal in via the switch, when the processing circuitry enables the switch. The ADC is coupled to take measurements of the signal detection circuitry at a first output. The processing circuitry is coupled to the ADC and configured to analyze whether an intruder is present in the device based on the measurements of the signal detection circuitry.

Edwards, Nathan J.↗

Detection of an internal short circuit in a battery

An electrical device comprises a battery cell; a pressure sensor for measuring swelling forces of the battery cell, optionally with voltage, temperature and current sensors, and a battery management system including a controller. The controller executes a program to: (i) determine a reference swelling force corresponding to a reference electrical signal received from the pressure sensor at an earlier reference time, (ii) determine a second swelling force corresponding to a second electrical signal received from the pressure sensor at a later second time, and (iii) determine whether a risk of internal short circuit of the battery cell exists by comparing a reference level of the reference electrical signal and a signal representative of the second electrical signal. When the signal representative of the second electrical signal exceeds the reference level of the reference electrical signal by a threshold amount, a risk of internal short circuit of the cell exists.

Stefanopoulou, Anna G.↗

Systems and methods for optical sensor protection

The present disclosure relates to an optical sensor protection system. The system may have a sensor for receiving an incoming optical signal, a passive sensing and modulation component, and an active sensing and modulation subsystem. The passive sensing and modulation component is configured to sense when a first characteristic is associated with the incoming optical signal is present that adversely affects operation of the sensor, and redirects at least a portion of the incoming optical signal thereof away from the sensor to thus reduce an intensity of the incoming optical signal reaching the sensor. The sensor is located on an image plane downstream of the ISM subsystem, relative to a path of travel of the incoming optical signal. The active sensing and modulation subsystem has an active modulation component and is located upstream of the passive sensing and modulation component, relative to the path of travel of the incoming optical signal, and is also located on a conjugate image plane, and is configured to use the redirected portion of the incoming optical signal as feedback in controlling a modification of the incoming optical signal to reduce a risk of damage to the passive sensing and modulation component.

Panas, Robert Matthew↗

Physics-guided dual implicit neural representations for source separation

Significant challenges exist in efficient data analysis of most advanced experimental and observational techniques because the collected signals often include unwanted contributions, such as background and signal distortions, that can obscure the physically relevant information of interest. To address this, we have developed a self-supervised machine-learning approach for source separation using a dual implicit neural representation framework that jointly trains two neural networks: one for approximating distortions of the physical signal of interest and the other for learning the effective background contribution. Our method learns directly from the raw data by minimizing a reconstruction-based loss function without requiring labeled data or pre-defined dictionaries. We demonstrate the effectiveness of our framework by considering a challenging case study involving large-scale simulated, as well as experimental, momentum-energy-dependent inelastic neutron scattering data in a four-dimensional parameter space, characterized by heterogeneous background contributions and unknown distortions to the target signal. The method is found to successfully separate physically meaningful signals from a complex or structured background even when the signal characteristics vary across all four dimensions of the parameter space. An analytical approach that informs the choice of the regularization parameter is presented. Our method offers a versatile framework for addressing source separation problems across diverse domains, ranging from superimposed signals in astronomical measurements to structural features in biomedical image reconstructions.

47 OTHER INSTRUMENTATION↗

Robust inference of ecosystem soil water stress from eddy covariance data

Eddy covariance data are invaluable for determining ecosystem water use strategies under soil water stress. However, existing stress inference methods require numerous subjective data processing and model specification assumptions whose effect on the inferred soil water stress signal is rarely quantified. These uncertainties may confound the stress inference and the generalization of ecosystem water use strategies across multiple sites and studies. In this research, we quantify the sensitivity of soil water stress signals inferred from eddy covariance data to the prevailing data and modeling assumptions (i.e., their robustness) to compile a comprehensive list of sites with robust soil water stress signals and assess the performance of current stress inference methods. To accomplish this, we identify the most prevalent assumptions from the literature and perform a digital factorial experiment to extract probability distributions of plausible soil water stress signals and model performance at 151 FLUXNET2015 and AmeriFlux-FLUXNET sites. Here, we develop a new framework that summarizes these probability distributions to classify and rank the robustness of each site’s soil water stress signal, which we display with a user-friendly heat map. We estimate that only 5%–36% of sites exhibit a robust soil water stress signal due to deficient model performance and poorly constrained ecosystem water use parameters. We also find that the lack of robustness is site-specific, which undermines grouping stress signals by broad ecosystem categories or comparing results across studies with differing assumptions. Lastly, existing stress inference methods appear better suited for eddy covariance sites with grass/annual vegetation. Our findings call for more careful and consistent inference of ecosystem water stress from eddy covariance data.

54 ENVIRONMENTAL SCIENCES↗

Polarized $\mathrm{NORTIA}$ accumulation in response to pollen tube arrival at synergids promotes fertilization

Signal-mediated regulation of protein trafficking is an elegant mechanism for controlling the delivery of molecules to a precise location for critical signaling events that occur over short time frames. During plant reproduction, the FERONIA receptor complex is critical for intercellular communication that leads to gamete delivery; however, the impact of the FERONIA signal transduction cascade on protein trafficking in synergid cells remains unknown. Live imaging of pollen tube reception has revealed that a key outcome of FERONIA signaling is polar accumulation of the MLO protein NORTIA at the filiform apparatus in response to signals from an arriving pollen tube. Artificial delivery of NORTIA to the filiform apparatus is sufficient to bypass the FERONIA signaling pathway and to promote interspecific pollen tube reception. We propose that polar accumulation of NORTIA leads to the production of a secondary booster signal to ensure that pollen tubes burst to deliver the sperm cells for double fertilization.

59 BASIC BIOLOGICAL SCIENCES↗

Listening for the Landing: Seismic Detections of Perseverance's Arrival at Mars With InSight

The entry, descent, and landing (EDL) sequence of NASA's Mars 2020 Perseverance Rover will act as a seismic source of known temporal and spatial localization. We evaluate whether the signals produced by this event will be detectable by the InSight lander (3,452 km away), comparing expected signal amplitudes to noise levels at the instrument. Modeling is undertaken to predict the propagation of the acoustic signal (purely in the atmosphere), the seismoacoustic signal (atmosphere-to-ground coupled), and the elastodynamic seismic signal (in the ground only). Our results suggest that the acoustic and seismoacoustic signals, produced by the atmospheric shock wave from the EDL, are unlikely to be detectable due to the pattern of winds in the martian atmosphere and the weak air-to-ground coupling, respectively. However, the elastodynamic seismic signal produced by the impact of the spacecraft's cruise balance masses on the surface may be detected by InSight. The upper and lower bounds on predicted ground velocity at InSight are 2.0 × 10 -14 and 1.3 × 10 -10 m s -1 . The upper value is above the noise floor at the time of landing 40% of the time on average. The large range of possible values reflects uncertainties in the current understanding of impact-generated seismic waves and their subsequent propagation and attenuation through Mars. Uncertainty in the detectability also stems from the indeterminate instrument noise level at the time of this future event. A positive detection would be of enormous value in constraining the seismic properties of Mars, and in improving our understanding of impact-generated seismic waves.

58 GEOSCIENCES↗

Modeling active control of resistive wall mode with power saturation and sensor noise on HL-2M

The resistive wall mode (RWM) control on the HL-2M tokamak is simulated with the MARS-F code (Liu et al 2000 Phys. Plasmas 7 3681), aiming at quantifying control current and voltage requirements when more realistic issues are taken into account, i.e. the control power saturation and the sensor signal noise. The fluid model predicts a narrow stability region for the n = 1 RWM without magnetic feedback, in the 2D parameter space of the plasma pressure versus the toroidal flow speed. Magnetic feedback can fully stabilize the RWM on HL-2M. Without considering the voltage limitation and the sensor signal noise, it is found that plasma flow helps active control of the mode, by reducing the required critical feedback gain for both flux-to-current and flux-to-voltage control schemes. In the absence of the sensor signal noise, the lowest control voltage saturation level, below which the RWM control is lost, is found to roughly satisfy a linear relation to the plasma flow frequency, indicating that subsonic plasma flow is effective in relaxing the control power requirement for the RWM feedback stabilization. The presence of the sensor signal noise substantially modifies the feedback results. A statistical study finds that the sensor signal noise, with the standard deviation of 0.1 G on HL-2M, roughly doubles the required control voltage for successful mode control. The synergistic stabilization effect due to plasma flow is somewhat weakened by the presence of the sensor signal noise. At a given rotation, the tolerable voltage limit generally increases with increasing feedback gain due to the sensor signal noise.

Physics↗

Methods for the robust computation of the long-period seismic spectrum of broad-band arrays

SUMMARY We describe array methods to search for low signal-to-noise ratio (SNR) signals in long-period seismic data using Fourier analysis. This is motivated by published results that find evidence of solar free oscillations in the Earth's seismic hum. Previous work used data from only one station. In this paper, we describe methods for computing spectra from array data. Arrays reduce noise level through averaging and provide redundancy that we use to distinguish coherent signal from a random background. We describe two algorithms for calculating a robust spectrum from seismic arrays, an algorithm that automatically removes impulsive transient signals from data, a jackknife method for estimating the variance of the spectrum, and a method for assessing the significance of an entire spectral band. We show examples of their application to data recorded by the Homestake Mine 3-D array in Lead, SD and the Piñon Flats PY array. These are two of the quietest small aperture arrays ever deployed in North America. The underground Homestake data has exceptionally low noise, and the borehole sensors of the PY array also have very low noise, making these arrays well suited to finding very weak signals. We find that our methods remove transient signals effectively from the data so that even low-SNR signals in the seismic background can be found and tested. Additionally, we find that the jackknife variance estimate is comparable to the noise floor, and we present initial evidence for solar g-modes in our data through the T2 test, a multivariate generalization of Student's t-test.

Caton, Ross C.↗

Seismoacoustic analysis of underground explosions using the Rayleigh integral

SUMMARY A coupled seismoacoustic model is developed for the analysis of acoustic signals produced by underground explosive events with an aim to develop a means of improving estimated depth and yield for explosion monitoring. A ground spall model is used to predict surface motion characteristics produced by an underground explosion and the Rayleigh integral is applied to relate the surface motion to the acoustic signal some distance from surface ground zero. The low-frequency component of the ground motion associated with the prolonged free fall of lofted material during spall is found to dominate the acoustic signal propagating away from surface ground zero at shallow angles. The model is applied to observed ground motion and acoustic signals recorded during the Source Physics Experiment (SPE) with promising results. In addition to accurately predicting characteristics of the observed acoustic signals from several of the SPE events, the model provides a means of explaining the lack of signals observed during several events in the SPE due to the directionality of the higher frequency acoustic signals associated with the uplift and closure components as well as the lack of a spatially localized, longer duration dwell.

58 GEOSCIENCES↗