Time-domain Measurements Research Articles

Design and offline tests of a resonant stripline cavity kicker for longitudinal feedback in the HEPS Booster

Resonant stripline cavity kicker was first proposed by Spring-8 as a highly efficient longitudinal feedback kicker, since the shunt impedance per length of this type of kicker is higher than that of the widely-used waveguide-loaded cavity kicker. This paper presents the design of a resonant stripline cavity kicker for the HEPS Booster with a smaller beampipe compared to Spring-8. Based on the time domain measurements and the particle-in-cell simulation results, the designed kicker with a length of 402 mm is expected to achieve a peak shunt impedance of 4140 Ω and a minimum shunt impedance of 2700 Ω within the bandwidth from 1.5 GHz to 1.75 GHz, demonstrating itself a higher efficiency over the waveguide-loaded cavity kicker. Besides, the analyzed coupling beam impedance of this kicker indicates it not a source of beam instability. All these results suggest the resonant stripline cavity kicker an ideal choice to simultaneously fulfill feedback requirements and save installation space even on a smaller size scale.

A Method to Assess Granger Causality, Isolation and Autonomy in the Time and Frequency Domains: Theory and Application to Cerebrovascular Variability.

Concepts of Granger causality (GC) and Granger autonomy (GA) are central to assess the dynamics of coupled physiologic processes. While causality measures have been already proposed and applied in time and frequency domains, measures quantifying self-dependencies are still limited to the time-domain formulation and lack of clear spectral representation. We embed into the linear parametric framework for computing GC from a driver X to a target process Y a measure of Granger Isolation (GI) quantifying the part of the dynamics of Y not originating from X, and a new spectral measure of GA assessing frequency-specific patterns of self-dependencies in Y. The measures are illustrated in theoretical simulations and applied to time series of arterial pressure and cerebral blood flow obtained in syncope subjects and healthy controls. Simulations show that GI is complementary to GC but not trivially related to it, while GA reflects the regularity of the internal dynamics of the target process. In the application to cerebrovascular interactions, spectral GA quantified the physiological response to postural stress of slow cerebral blood flow oscillations, while spectral GC and GI detected an altered response to orthostasis in syncope subjects, likely related to impaired cerebral autoregulation. The new spectral measures of GI and GA are useful complements to GC for the analysis of interacting oscillatory processes, and detect pathophysiological responses to postural stress which cannot be traced in the time domain. The thorough assessment of causality, isolation and autonomy opens new perspectives for the analysis of coupled processes in both physiological and clinical investigations.

Disaggregation and fibrillation during sol-gel transition of alginate hydrogels

The rheological and morphological characteristics of Ca-crosslinked alginate hydrogels with two different M/G ratios, α-L-guluronate (G)-rich and β-D-mannuronate (M)-rich, each with one alginic acid concentration, were investigated. It was found that the stiffness and elasticity of alginate hydrogels are derived from the thickness and density of the fibril network structures. In aqueous alginate solution, ball-like aggregates of alginates are present. Time-resolved small-angle X-ray scattering and time-domain nuclear magnetic resonance measurements suggest that the disaggregation of alginate aggregates and loose fibrillation occur in the early stage of the sol-gel transition. After these induction stage, direct gelation is finally caused by the formation of the egg-box junction. G-rich alginate hydrogel has a higher stiffness and a thicker and denser fibril network structure than M-rich alginate hydrogel. The former also exhibits faster and more significant changes in physical properties during the sol-gel transition.

A fast and robust sliding mode controller for automatic voltage regulators in electrical power systems

In this paper, a fast and robust sliding mode controller (SMC) based on a novel multi-variable sliding function is proposed for Automatic Voltage Regulators (AVRs) in electrical power systems. Lyapunov stability theorem is used to guarantee the asymptotic stability of the proposed controller. As the proposed controller is multi-variable, there may be different optimum controller parameter sets that result in performance close to each other. Hence, two optimum sets of parameters are explored by two well-known algorithms, namely, Sine Cosine Algorithm and Grey Wolf Optimization. A new objective function is considered for the optimizations, including an overshoot constraint. The performance of the proposed controller with the optimum parameter sets is evaluated for five different parameter uncertainties and load disturbance scenarios, and the resulting time domain measurements are compared with the results of recently published SMCs. A 38.36 % improvement in settling time was observed compared to the most recent study using the same realistic AVR model. In addition, the proposed controller suppressed different load disturbances, including parasitic ones, and quickly recovered the AVR output. All results revealed that the proposed controller achieved the best performance in terms of speed and robustness compared to existing controllers, despite the controller and exciter limitations.

Dynamic transient response measurement method for parity-time-symmetric LC telemetry sensors

Parity-time symmetry concept has been utilized to develop high precision LC passive wireless sensors. However, they often use the traditional frequency sweeping method for measurements, thus the measurement precision and speed are strongly influenced by the performance of the frequency domain analysis instrument. To solve this issue, herein we proposed a time domain measurement method and extracted sensing information from the transient response signals of the reader. Its measurement speed was much faster than that using the frequency domain analysis instrument. A distance sensing system was developed to demonstrate the feasibility of the new method. It showed a resolution of less than 300 nm for detections of centimeter range, and the measurement time was as short as 100 μs, which was at least 1000 times faster than that using the traditional method. This technology can be explored as an innovative strategy for LC passive telemetry sensing.

Exploratory analysis of spontaneous versus paced breathing on heart rate variability in veterans with combat-related traumatic injury.

Respiration is a crucial determinant of autonomic balance and heart rate variability (HRV). The comparative effect of spontaneous versus paced breathing on HRV has been almost exclusively explored in healthy adults and never been investigated in an injured military cohort. To examine the effect of spontaneous versus paced breathing on HRV in veterans with combat-related traumatic injury (CRTI). Observational cohort study. ArmeD serVices trAuma rehabilitatioN outComE (ADVANCE) study, Stanford Hall, UK. The sample consisted of 100 randomly selected participants who sustained CRTI (eg, amputation) during their deployment (Afghanistan 2003-2014) and were recruited into the ongoing ADVANCE prospective cohort study. Not applicable. HRV was recorded using a single-lead ECG. HRV data were acquired during a sequential protocol of 5-minute spontaneous breathing followed immediately by 5 minutesof paced breathing (six cycles/minute) among fully rested and supine participants. HRV was reported using time domain (root mean square of successive differences), frequency domain (low frequency and high frequency) and nonlinear (sample entropy) measures. The agreement between HRV during spontaneous versus paced breathing was examined using the Bland-Altman analysis. The mean age of participants was 36.5 ± 4.6 years. Resting respiratory rate was significantly higher with spontaneous versus paced breathing (13.4 ± 3.4 vs. 7.6 ± 2.0 breaths/minute; p < .001), respectively. Resting mean heart rate and root mean square of successive differences were significantly higher with paced breathing than spontaneous breathing (p < .001). Paced breathing significantly increased median low frequency power than spontaneous breathing (p < .001). No significant difference was found in the absolute power of high frequency between the two breathing protocols. The Bland-Altman analysis revealed poor agreement between HRV values during spontaneous and paced breathing conditions with wide limits of agreement. Slow-paced breathing leads to higher HRV than spontaneous breathing and could overestimate resting "natural-state" HRV.

Prediction and Detection of Ventricular Fibrillation Using Complex Features and AI-Based Classification

We analyzed the possibility of detecting and predicting ventricular fibrillation (VF), a medical emergency that may put people’s lives at risk, as the medical prognosis depends on the time in which medical personnel intervene. Therefore, besides immediate detection of VF, the possibility of predicting VF 40 or even 50 min in advance was analyzed. For testing the proposed algorithm, we used ECG signals taken from the MIT-BIH database, namely, Malignant Ventricular Ectopy Database, Sudden Cardiac Death Holter Database and Normal Sinus Rhythm Database. The presented method is based on features extracted from the ECG signals in the time domain, frequency domain and complexity measures. For VF detection, the possibility of identifying the VF episode in the first 3 s after its occurrence was tested. For this, the first 3 s immediately after the appearance of VF were cut out and the features were computed on these sections. For VF prediction, 3 min of the ECG signal clipped 40 or 50 min before VF onset was used. Then, on these pieces of ECG signal, the specific features were calculated for 1 s segments. For the normal signal situation, 3 min was randomly selected from the database with normal ECGs. For the classification or detection stage, both an MLP-type neural network and the classifiers from the Machine Learning toolbox of the MATLAB® environment were used. The results obtained for both detection and classification are over 94% in both cases. The novelty of our results compared to those previously obtained is the time interval with which the possibility of prediction was analyzed, namely, 50 min in advance of the VF installation date. This means that the patient will be informed that it is possible to suffer a VF and has time to take the necessary measures to overcome a possible medical emergency.

A method to assess linear self-predictability of physiologic processes in the frequency domain: application to beat-to-beat variability of arterial compliance.

The concept of self-predictability plays a key role for the analysis of the self-driven dynamics of physiological processes displaying richness of oscillatory rhythms. While time domain measures of self-predictability, as well as time-varying and local extensions, have already been proposed and largely applied in different contexts, they still lack a clear spectral description, which would be significantly useful for the interpretation of the frequency-specific content of the investigated processes. Herein, we propose a novel approach to characterize the linear self-predictability (LSP) of Gaussian processes in the frequency domain. The LSP spectral functions are related to the peaks of the power spectral density (PSD) of the investigated process, which is represented as the sum of different oscillatory components with specific frequency through the method of spectral decomposition. Remarkably, each of the LSP profiles is linked to a specific oscillation of the process, and it returns frequency-specific measures when integrated along spectral bands of physiological interest, as well as a time domain self-predictability measure with a clear meaning in the field of information theory, corresponding to the well-known information storage, when integrated along the whole frequency axis. The proposed measure is first illustrated in a theoretical simulation, showing that it clearly reflects the degree and frequency-specific location of predictability patterns of the analyzed process in both time and frequency domains. Then, it is applied to beat-to-beat time series of arterial compliance obtained in young healthy subjects. The results evidence that the spectral decomposition strategy applied to both the PSD and the spectral LSP of compliance identifies physiological responses to postural stress of low and high frequency oscillations of the process which cannot be traced in the time domain only, highlighting the importance of computing frequency-specific measures of self-predictability in any oscillatory physiologic process.

A 56‐GBaud lumped linear push–pull driver for Mach–Zehnder modulator in 130‐nm SiGe technology

AbstractA fully differential lumped linear driver for Mach–Zehnder modulator has been presented and assessed in 130‐nm SiGe BiCMOS technology. Multitopology peaking techniques, especially T‐coil peaking method, have been employed to flatten the frequency response and increase the bandwidth. Degeneration resistors have been used to enhance circuit linearity. Simultaneously, improvements have been made to the output stage of the conventional single emitter follower push–pull) circuit to enhance the output eye diagram quality at higher transmission rates. The fabricated driver achieved a differential gain of 16.2 dB with a bandwidth of over 50 GHz, corresponding to a fixed output swing of over 3.2 Vppd within the automatic gain control loop. Time domain measurements, limited in speed by the measurement setup, reported a data rate up to 56 Gb/s none return to zero and 40‐GBaud 4‐levels pulse amplitude modulation with a bit error rate less than 10−12.

Winding Response under Difference Effective Inductance for Single Phase High Voltage Transformer

Early studies of transformer winding parameters were focused on the determination via its physical dimensions and empirical formulas. In most cases it is divided into several parts namely coil section pairs, coils distance, disc coils diameter and thickness of insulation. Maxwell’s equations are often the solution to the problem, which satisfy related boundary conditions between conductors for mutual inductance and capacitor equations. Such solutions often led to errors and hence its mathematical model. To counter the problem, it was suggested that such approximations must be conducted with experimental model windings at the same time. Frequency domain measurements and time domain measurements can be conducted to effectively determine these parameters. This in turn will investigate the behaviour of transformer winding electromagnetic transient at high frequency. From theoretical point of view, predominantly capacitive winding model often considered to represent its behaviour at high frequency and will give the results of its initial distribution. Under this consideration, a single phase plain winding is considered for investigation. A single rectangular wave was considered to represent infinitive impinge incident wave, injected at one end of transformer winding and the measured response signals of the wavetail were considered for measurement. The experimental response and modelling results were compared and proved to have high agreement between the two.

Work stress and changes in heart rate variability among employees after first acute coronary syndrome: a hospital-based longitudinal cohort study.

Work stress is considered as a risk factor for coronary heart disease, but its link with heart rate variability (HRV) among heart attack survivors is unknown yet. The aim of this study was to investigate associations between baseline work stress and the changes of HRV over one-year after onset of acute coronary syndrome (ACS). Hundred and twenty-two patients with regular paid work before their first ACS episode were recruited into this hospital-based longitudinal cohort study. During hospitalization (baseline), all patients underwent assessments of work stress by job strain (JS) and effort-reward imbalance (ERI) models, and were assigned into low or high groups; simultaneously, sociodemographic and clinical data, as well depression, anxiety, and job burnout, were collected. Patients were followed up 1, 6, and 12 months after discharge, with HRV measurements at baseline and each follow-up point. Generalized estimating equations were used to analyze the effects of baseline work stress on HRV over the following 1 year. After adjusting for baseline characteristics and clinical data, anxiety, depression, and burnout scores, high JS was not associated with any HRV measures during follow-up (all p > 0.10), whereas high ERI was significantly related to slower recovery of 5 frequency domain HRV measures (TP, HF, LF, VLF, and ULF) (all p < 0.001), and marginally associated with one time domain measure (SDNN) (p = 0.069). When mutually adjusting for both work stress models, results of ERI remained nearly unchanged. Work stress in terms of ERI predicted lower HRV during the one-year period after ACS, especially frequency domain measures.

Research on online passive electrochemical impedance spectroscopy and its outlook in battery management

Current lithium-ion battery (LIB) management technique relying solely on the limited time-domain measurements appears to reach its limit, and incorporating new sensing information, particularly the impedance of LIB, offers a promising path for improvement. Using the non-stationary random driving profile of electric vehicle (EV), a method to extract online passive electrochemical impedance spectroscopy (OPEIS) is proposed and validated, with relevant factors influencing its efficacy also investigated. The particularity of actual driving profile is revealed both theoretically and experimentally, and beyond expectation, the highly differentiated driving profiles yield a similar spectral pattern, which facilitates the acquisition of OPEIS. Continuous OPEIS characterized by the distribution of relaxation time (DRT) ranging from 0.2 Hz to 3 kHz are analyzed in detail under different battery conditions. Compared with offline reference EIS, most of the measurement errors are <3%. Based on the acquired spectral information and OPEIS, a safety-relevant detector and an internal temperature estimator for LIB are presented, and they can both realize a near instant electrochemical sensing up to 1 Hz. As the underlying opportunities of OPEIS are outlined, challenges in its reliable acquisition and engineering implementation are evaluated as well. By comprehensively discussing the realization of OPEIS, research in this paper is expected to provide valuable references for a more effective battery management.

Development, Validation, and Comparison of a Novel Nociception/Anti-Nociception Monitor against Two Commercial Monitors in General Anesthesia.

In this paper, we present the development and the validation of a novel index of nociception/anti-nociception (N/AN) based on skin impedance measurement in time and frequency domain with our prototype AnspecPro device. The primary objective of the study was to compare the Anspec-PRO device with two other commercial devices (Medasense, Medstorm). This comparison was designed to be conducted under the same conditions for the three devices. This was carried out during total intravenous anesthesia (TIVA) by investigating its outcomes related to noxious stimulus. In a carefully designed clinical protocol during general anesthesia from induction until emergence, we extract data for estimating individualized causal dynamic models between drug infusion and their monitored effect variables. Specifically, these are Propofol hypnotic drug to Bispectral index of hypnosis level and Remifentanil opioid drug to each of the three aforementioned devices. When compared, statistical analysis of the regions before and during the standardized stimulus shows consistent difference between regions for all devices and for all indices. These results suggest that the proposed methodology for data extraction and processing for AnspecPro delivers the same information as the two commercial devices.

An Analysis of the WPT Function for Pattern Optimization to Detect Defects in Bearings

New trends in maintenance techniques are oriented to digitization and prognosis. The new electronic devices based on IoT (Internet of Things) technology among others that support the industry 4.0 paradigm let enhance the traditional condition monitoring techniques to better understand and predict the state of a machine in service. Related to maintenance applications, one of the important steps in condition monitoring tasks for fault diagnosis is the selection of the optimal pattern to provide accurate results (avoiding fault positives/negatives) with adequate computation time. When implementing this, the selection of optimal parameters and thresholds for setting alarms are important to detect problems in the machine before the failure occurs. Vibratory signals have been proved to be a good variable to determine their mechanical behavior. Nevertheless, parameters obtained from time domain measurements are not computationally efficient nor good patterns to compare different machine conditions. In this sense, tools that represent the frequency domain or time–frequency domain have been useful to detect defects in rotating elements such as bearings. In this work, defects in ball bearings are studied using wavelet packet transform. For this, a methodology will be developed for the optimal selection of the mother wavelet, incorporating intelligent classification systems, and using a medium Gaussian support vector machine model. In this way, it will be verified that the correct selection of this function influences both the results and the ease and reliability of detection. The results using the selected mother wavelet will be compared to those using Daubechies 6, since it is the mother wavelet that has been used in previous works and which was selected based on experience. For it, vibratory signals are obtained from a testbench with different bearing conditions: healthy bearings and defective bearings (inner and outer race).

Air-coupled ultrasound for testing of batteries and components

This work describes the use of an air-coupled and through transmission ultrasonic (0.2–1.5 MHz) technique, both at normal and oblique incidence, for the characterization and test of pouch-cell Li-ion (and similar types) batteries and components. Time domain measurements show that it is possible to measure ultrasonic velocity in the battery. Frequency domain measurements reveal the generation of thickness resonances. From them, solution of the inverse problem permit to extract: ultrasound velocity and attenuation (and variation with frequency), thickness and density. At normal incidence, these resonances provide information about the compressional wave. At oblique incidence, it is first observed that there is a range of incidence angles where propagation is no permitted. This response can be explained in terms of the battery layered structure, once these angles are exceeded, the shear wave is generated, propagated and observed, giving rise to the generation of thickness resonances. Shear wave propagation is strongly anisotropic: lower velocity in the direction of the battery plane, compared with a higher velocity in the direction normal to the battery plane. No limit angle for the shear wave is observed. Possibilities of this technique for the testing of new batteries, continuous state monitoring and battery sorting for re-use or recycling are discussed.

Non-Linear Simulation by Harmonic Balance Techniques of Load Modulated Power Amplifier Driven by Random Modulated Signals

The simulation of the steady state and the non-linear stability of a load modulated power amplifier (LMPA) driven by a random modulated generator, fully performed in the frequency domain by harmonic balance (HB) techniques, is presented. The non-linear microwave circuit and the driving pseudo-random modulated (PRM) generator are integrally defined in the frequency domain. The simulation is implemented and performed using commercially available circuit simulation software. The demodulation of the output signal of the LMPA is implemented with optimally matched filters as software-defined demodulation. The simulated dynamic results of a Quasi-MMIC GaN Doherty power amplifier (DPA) are shown and compared to the measured results with a 16-QAM driving signal at 10 MS/s. The time-domain measurement allows the validation of the new simulation technique through the comparison of both the measured and the simulated error vector magnitude (EVM), the left and right adjacent channel power ratios (ACPRs) versus the average output power. This new simulation is then called pseudo-random modulated harmonic balance (PRM-HB) simulation. The full PRM-HB simulation of an LMPA driven by a random modulated signal, performed in the frequency domain at the design circuit level, results in an advanced simulation tool in the frame of the design of RF circuits and subsystems for telecommunication applications.

Acousto-optic-based time domain electric field sensor for magnetic resonance imaging applications.

An acousto-optic (AO)-based electric field sensor is presented for time domain measurement under magnetic resonance imaging (MRI). A fully MR-compatible sensor is designed and fabricated using a phase-shifted fiber Bragg grating mechanically coupled to a piezoelectric transducer. Mechanical resonance of the piezoelectric transducer is matched to the operating frequencies of commonly used MRI systems to increase the sensitivity of the sensor. Sensitivity of the sensor is measured as 1.27 mV/V/m, with a minimum detectable electric field of 4.4 mV/m/√/Hz. Directivity of the sensor is measured with a 18 dB orthogonal component rejection. The dynamic range of the sensor is calculated as 117 dB/Hz, which allows the measurement of electric fields up to 3.2 kV/m. In MRI studies, the AO sensor was able detect local hot spots around a reference implant accurately with high signal-to-noise ratio. AO sensor exhibited similar or better performance when compared with commercially available MRI compatible electric field sensors. Furthermore, the small size of the sensor with the flexible fiber optic link could allow in situ measurements of electric fields during critical interventional procedures such as pacemaker lead or deep brain stimulator placement as an MRI dosimeter during diagnostic scans.

Terahertz Spatiotemporal Wave Synthesis in Random Systems.

Complex media have emerged as a powerful and robust framework to control light-matter interactions designed for task-specific optical functionalities. Studies on wavefront shaping through disordered systems have demonstrated optical wave manipulation capabilities beyond conventional optics, including aberration-free and subwavelength focusing. However, achieving arbitrary and simultaneous control over the spatial and temporal features of light remains challenging. In particular, no practical solution exists for field-level arbitrary spatiotemporal control of wave packets. A new paradigm shift has emerged in the terahertz frequency domain, offering methods for absolute time-domain measurements of the scattered electric field, enabling direct field-based wave synthesis. In this work, we report the experimental demonstration of field-level control of single-cycle terahertz pulses on arbitrary spatial points through complex disordered media.

Quasi-ballistic thermal transport in silicon carbide nanowires

Silicon carbide (SiC) is an important industrial material that enables the thermal stability of power electronics. However, the nanoscale phenomenon of ballistic thermal conduction, which may further improve the thermal performance, remains unexplored in SiC. Here, we reveal the length and temperature scales at which SiC exhibits quasi-ballistic thermal conduction. Our time-domain thermoreflectance measurements probe the thermal conductivity of SiC nanowires as a function of their length and temperature. The deviation of the thermal conductivity from the diffusive limit in nanowires shorter than a few micrometers indicates the transition into a quasi-ballistic thermal conduction regime. Naturally, the deviation is greater at lower temperatures, yet the effect persists even above room temperature. Our Monte Carlo simulations of phonon transport support our experimental results and show how phonons with long mean free paths carry a substantial amount of heat, causing quasi-ballistic conduction. These findings show that quasi-ballistic heat conduction can persist at the microscale at operating temperatures of power devices, and thus may help improve the thermal design in electronics based on SiC.

Discerning rise time constants to quantify charge carrier extraction in perovskite solar cells

A method is developed to extract the rise time constant from frequency domain data of perovskite solar cells, which determines the charge extraction efficiency. The results show a good agreement with those obtained from time domain measurements.