Near-Zero Phase-Lag Hyperscanning in a Novel Wireless EEG System

Hyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with wireless electroencephalography (EEG) is increasingly popular owing to its mobility and ability to decipher social interactions in natural settings at the millisecond scale. To align multiple EEG time series with sophisticated event markers in a single time domain, a precise and unified timestamp is required for stream synchronization. This study proposed a clock-synchronized method using a custom-made RJ45 cable to coordinate the sampling between wireless EEG amplifiers to prevent incorrect estimation of interbrain connectivity due to asynchronous sampling. In this method, analog-to-digital converters are driven by the same sampling clock. Additionally, two clock-synchronized amplifiers leverage additional RF channels to keep the counter of their receiving dongles updated, guaranteeing that binding event markers received by the dongle with the EEG time series have the correct timestamp. The results of two simulation experiments and one video gaming experiment revealed that the proposed method ensures synchronous sampling in a system with multiple EEG devices, achieving near-zero phase-lag and negligible amplitude difference between signals. According to all of the signal-similarity metrics, the suggested method is a promising option for wireless EEG hyperscanning and can be utilized to precisely assess the interbrain couplings underlying social-interaction behaviors.

A High-Precision and Wideband Fundamental Frequency Measurement Method for Synchronous Sampling Used in the Power Analyzer

In the dedicated high-precision power quality analyzer, synchronous sampling is required to reduce the effect of spectrum leakage produced by the discrete Fourier transform process. Thus, accurate fundamental frequency measurement is urgently needed. However, due to the harmonics and noise in the power signal, it is difficult to achieve the accurate fundamental frequency measurement. Moreover, with the wide application of high-frequency programmable power supply, the fundamental frequency is gradually increasing, which requires power analyzers to have the abilities of both high precision and a wide range of the fundamental frequency measurement. To solve these issues, a new fundamental frequency measurement architecture used in synchronous sampling is proposed. This architecture consists of a small-point fast Fourier transform module, spectrum refinement algorithm, and a multimodal optimization method to calculate the accurate fundamental frequency under large harmonic conditions. In the practical hardware platform results, this architecture has a large fundamental frequency measurement range from 20 Hz to 200 kHz with a relative error which is <0.004%. The wideband fundamental frequency measurement structure proposed in this article achieves high measurement accuracy.

Technical note: Considerations on using uncertain proxies in the analogue method for spatiotemporal reconstructions of millennial-scale climate

Inferences about climate states and climate variability of the Holocene and the deglaciation rely on sparse paleo-observational proxy data. Combining these proxies with output from climate simulations is a means for increasing the understanding of the climate throughout the last tens of thousands of years. The analogue method is one approach to do this. The method takes a number of sparse proxy records and then searches within a pool of more complete information (e.g., model simulations) for analogues according to a similarity criterion. The analogue method is non-linear and allows considering the spatial covariance among proxy records. Beyond the last two millennia, we have to rely on proxies that are not only sparse in space but also irregular in time and with considerably uncertain dating. This poses additional challenges for the analogue method, which have seldom been addressed previously. The method has to address the uncertainty of the proxy-inferred variables as well as the uncertain dating. It has to cope with the irregular and non-synchronous sampling of different proxies. Here, we describe an implementation of the analogue method including a specific way of addressing these obstacles. We include the uncertainty in our proxy estimates by using “ellipses of tolerance” for tuples of individual proxy values and dates. These ellipses are central to our approach. They describe a region in the plane spanned by proxy dimension and time dimension for which a model analogue is considered to be acceptable. They allow us to consider the dating as well as the data uncertainty. They therefore form the basic criterion for selecting valid analogues. We discuss the benefits and limitations of this approach. The results highlight the potential of the analogue method to reconstruct the climate from the deglaciation up to the late Holocene. However, in the present case, the reconstructions show little variability of their central estimates but large uncertainty ranges. The reconstruction by analogue provides not only a regional average record but also allows assessing the spatial climate field compliant with the used proxy predictors. These fields reveal that uncertainties are also locally large. Our results emphasize the ambiguity of reconstructions from spatially sparse and temporally uncertain, irregularly sampled proxies.

Vibration-based synchronous sampling and its application in wind-turbine drive-train-condition monitoring

Utilizing shaft-speed information to analyse vibration signals is an important method for fault diagnosis and condition monitoring of rotating machineries, especially for those running at variable speeds. However, in many cases, shaft-speed information is not always available, for a variety of reasons. Fortunately, in most of the measurements, the shaft-speed information is embedded in the vibration response in many different forms, such as in the format of the fundamental shaft-rotation-frequency response and its harmonics, and the gear-meshing-frequency response and its harmonics, etc. Proper signal processing can be used to extract the shaft instantaneous speed from the measured vibration responses. In existing instantaneous shaft-speed-identification methods, a narrow-bandpass filtering technique is used explicitly or implicitly. In a complex gearbox system, such as that used in a wind turbine, the gear-meshing-response component could be modulated by many other shaft speeds, due to the configuration of the gearbox or due to the existence of component damage. As a result, it is very difficult to isolate a single vibration-response component for instantaneous shaft-speed detection. In this paper, an innovative approach is presented. The instantaneous shaft speed is extracted based on maxima tracking from the vibration-response spectrogram. A numerical integration scheme is employed to obtain the shaft instantaneous phase. Digital-domain synchronous resampling is then applied to the vibration data by using the instantaneous phase information. Due to the nature of noise suppression in the numerical integration, the accuracy of synchronous sampling is greatly improved. This proposed approach demonstrates the feasibility and engineering applicability through a controlled laboratory test case and two field wind-turbine cases. More detailed results and conclusions of this research are presented at the end of this paper.

Synchronous Sampling-Based Direct Current Estimation Method for Self-Sensing Active Magnetic Bearings

Active magnetic bearings (AMBs) commonly use pulse-width modulation to reduce analogous hardware and manufacturing costs, but they experience sensing process, sensing accuracy and stability problems. To address these issues, a synchronous sampling-based direct current estimation (SS-DCE) method is proposed herein with a bistate switching power amplifier. First—considering the reluctance evolution mechanism of AMBs—a coupling relation mathematical model between rotor displacement and voltage/current is presented to acquire the rotor position from the working coil current alone. Then—assuming that the switching current was an approximately triangular signal—a DCE for the rotor position was established based on the estimation inductance of the charging/discharging phase. Finally—to decrease the phase shift caused by the self-sensing filters and position estimation algorithms—the SS-DCE method was introduced to conduct precise position detection for rotors with high velocities. The simulation and experimental results indicated that the proposed method could improve the sensing accuracy and stability. Compared to other AMB position estimation methods, the simple linearity of the SS-DCE method was greatly improved and could be controlled below 4%. Evaluation using frequency response analysis showed that the SS-DCE method had excellent dynamic accuracy and could perform at a higher phase margin, especially for the uprising/landing transient state. Moreover, there was a phase margin of 158° at the natural frequency of 19.26 HZ, and the peak sensitivity in the 50–250 μm range reached 10.7 dB.