Active Magnetoelectric Motion Sensing: Examining Performance Metrics with an Experimental Setup

Magnetoelectric (ME) sensors with a form factor of a few millimeters offer a comparatively low magnetic noise density of a few pT/Hz in a narrow frequency band near the first bending mode. While a high resonance frequency (kHz range) and limited bandwidth present a challenge to biomagnetic measurements, they can potentially be exploited in indirect sensing of non-magnetic quantities, where artificial magnetic sources are applicable. In this paper, we present the novel concept of an active magnetic motion sensing system optimized for ME sensors. Based on the signal chain, we investigated and quantified key drivers of the signal-to-noise ratio (SNR), which is closely related to sensor noise and bandwidth. These considerations were demonstrated by corresponding measurements in a simplified one-dimensional motion setup. Accordingly, we introduced a customized filter structure that enables a flexible bandwidth selection as well as a frequency-based separation of multiple artificial sources. Both design goals target the prospective application of ME sensors in medical movement analysis, where a multitude of distributed sensors and sources might be applied.

Numerical Model on the Dynamic Behavior of a Prototype Kaplan Turbine Runner

Experimental and numerical investigations of the modal behavior of a prototype Kaplan turbine runner in air have been conducted in this paper. The widely used roving accelerometer method was used in the experimental modal analysis. A systematic approach from a single blade model to the whole runner has been used in the simulation to get a thorough understanding. The experimental results show that all the detected modes concentrate their displacements on the impacted blade. The numerical results show that the modes of the single blade form different mode families of the runner, and each mode family corresponds to a narrow frequency band. Harmonic response analysis shows that, at the response peak point, the single blade excitation can only get mode shapes with concentrations on the exciting blade due to the superposition of the close modes in each mode family, which explains the experimental results well, while the mode superposition can be avoided by the order excitation method. With the reduction of the connection stiffness between the blades and hub/control system, the frequencies of most modes change from insensitive to more and more sensitive to the connection stiffness change, which results in a sensitive area and an insensitive area. Through comparison with the experimental results, it is indicated that the natural frequencies of the runner can probably be predicted by merging the runner into a whole body.

New Sensor for Medium- and High-Voltage Measurement

Measurements of medium and high voltages in a power grid are normally performed with large and bulky voltage transformers or capacitive dividers. Besides installation problems, these devices operate in a relatively narrow frequency band, which limits their usability in modern systems that are saturated with power electronic devices. A sensor that can be installed directly on a wire and can operate without a galvanic connection to the ground may be used as an alternative voltage measurement device. This type of voltage sensor can complement current sensors installed on a wire, forming a complete power acquisition system. This paper presents such a sensor. Our sensor is built using two dielectric elements with different permeability coefficients. A finite element method simulation is used to estimate the parameters of a constructed sensor. Besides simulations, a laboratory model of a sensor was built and tested in a medium-voltage substation. Our results provide a proof of concept for the presented sensor. Some errors in voltage reconstruction have been traced to an oversimplified data acquisition and transmission system, which has to be improved during the further development of the sensor.

Filter Bank Multi Carrier Signal System for Frequency Selective Channels

Filter Bank Multicarrier (FBMC) frameworks are a subclass of multicarrier (MC) frameworks. The essential guideline, separating spectrum into many thin sub channels, may not be new, MC frameworks have seen wide appropriation. These days, multicarrier regulation frameworks dependent on the discrete Fourier transforms are usually used to transmit over recurrence particular channels subject to forceful noise aggravations. In any case, these handsets experience the ill effects of poor sub channel spectral control, that is, the measure of inter channel impedance isn't unimportant. It very well may be indicated that the framework execution reduces when it is dependent upon an unsettling influence with a large portion of its energy focused on a narrow frequency band. This Paper aims that identify the Filter Bank Multi Carrier (FBMC) performance. The MIMO system combined with the FBMC then identifies the over Frequency Selective Channel (FSC). Here the analysis for FSC, Flat fading model FBMC and system with MMSE equalization. The Prototype filters are analyzing the system performance characteristics. The Power Spectral Density (PSD) of the MIMO FBMC system for the given spectrum. The proposed systems are best to compare all existing technique and we measure the spectral efficiency of the system.

On the strength of the phase cross-correlation in retrieving the Green’s function information in a region affected by persistent aftershock sequences

Although research on seismic interferometry is now entering a phase of maturity, earthquakes are still the most troublesome issues that plague the process in real applications. To address the problems that arise from spatially scattered and temporally transient enormous earthquakes, preference is usually given to the use of time-dependent weights. However, small earthquakes can also have a disturbing effect on the accuracy of interpretations if they are persistently clustered right next to the perpendicular bisector of the line joining station pairs or in close proximity to one of the stations. With regard to the suppression of these cluster earthquakes, commonly used solutions for dealing with monochromatic microseismic cluster events (e.g., implementing a band-reject filter around a comparatively narrow frequency band or whitening the amplitude spectra before calculating the cross-spectrum between two signals) may not have the necessary efficiency since earthquake clusters are generally a collection of events with different magnitudes, each having its own frequency and energy contents. Therefore, the only solution left in such a situation is to use stronger non-linear time-dependent weights (e.g., square of the running average or one-bit normalization), which may cause Green’s function amplitude information to be lost. In this paper, by simulating the records of a benchmark earthquake MN 5.2 with the help of empirical Green’s functions (EGF) obtained after the Ahar-Varzeghan Earthquake Doublet (MN 6.4 and MN 6.3), it is shown that the amplitude-unbiased phase cross-correlation is a relatively efficient approach in the face of the issues concerning long-standing cluster events.

Interval and Point Direction Finding of Radio Emission Sources for Broadband Radio Monitoring

Introduction. The point and interval direction finding of radio sources is used for broadband radio monitoring in the frequency domain. The initial data for broadband radio monitoring are spectral samples obtained from an M-element antenna array by multichannel reception. Point direction finding is based on a grouping of point estimates of azimuth and elevation angle formed for each frequency sample, in which signal components are detected. A single estimate of azimuth and elevation angle is made based on the grouped point estimates in the range of neighbouring frequency samples. Interval direction finding is based on the azimuth and elevation estimates formed entirely from the interval of adjacent frequency samples, in which the signal components are found, and the subsequent refinement of frequency sample interval boundaries for each radio source in multisignal mode by spatial selection methods. Point direction finding is mainly implemented in single-signal mode in modern operating broadband radio monitoring complexes, while the multi-signal mode based on MUSIC or ESPRIT is implemented in the time domain in a narrow frequency band.Aim. Development and investigation of methods for point and interval direction finding in multi-signal mode, as well as development of recommendations for their practical application in multi-signal and single-signal modes.Methods. Multi-signal mode for point and interval direction finding was implemented using MUSIC and ESPRIT. An experimental study of the developed direction finding methods in single-signal and multi-signal (on ESPRIT) modes with overlapping signal spectra was carried out by processing the recorded real signals. The records were made using a seven-channel coherent synchronous receiver connected to a seven-element 60° angle antenna array.Results. The research results are presented by frequency-azimuth panoramas and estimates of the amplitude spectra of separated signals and direction finding accuracy indicators.Conclusion. It was experimentally demonstrated that point direction finding should be used in single-signal mode provided the absence of information on the number of signals in the observed data. Interval direction finding is recom-mended in multi-signal mode for improving the accuracy and real-time feasibility of the process.

A phase linearisation–based modulation signal bispectrum for analysing cyclostationary bearing signals

Bearings are used as the most important load-carrying transmission components in various machines, thus subjecting to a number of faults including wear, fatigue pitting, cracks and so on. Fault detection and diagnosis of bearings can effectively prevent the machine from such typical failures and subsequent consequences. The faults in bearings can lead to the vibration signals that exhibit cyclostationary characteristics due to the inevitably random phase noise (or slippage between bearing components). In this article, a phase linearisation–based modulation signal bispectrum is proposed to tune up the cyclostationary bearing signal into a periodic waveform by linearizing the instantaneous phase of the narrow frequency band signals. In this way, the signal becomes more deterministic and modulation signal bispectrum can be effectively applied to suppression noise and obtain accurate and robust diagnosis results. As a result, this fault detector can achieve high performance in characterising the nonstationary bearing vibration signals and hence diagnose the bearing faults even in the case of extremely low signal-to-noise ratio (<−20 dB), which is benchmarked by the method of conventional modulation signal bispectrum in both simulation and experiment studies.

Fabrication of MEMS Directional Acoustic Sensors for Underwater Operation

In this work, microelectromechanical systems (MEMS)-based directional acoustic sensors operating in an underwater environment are explored. The studied sensors consist of a free-standing single wing or two wings pivoted to a substrate. The sensors operate in a narrow frequency band determined by the resonant frequency of the mechanical structure. The electronic readout of the mechanical response is obtained using interdigitated comb finger capacitors attached to the wings. The characteristics of MEMS sensors immersed in silicone oil are simulated using finite element modeling. The performance of the sensors is evaluated both in air and underwater. For underwater testing and operation, the sensors are packaged in a housing containing silicone oil, which was specially developed to present near unity acoustic transmission. The measurements show that the resonant frequency of the sensors obtained in air shifts to a lower frequency when immersed in silicone oil, which is primarily due to the mass loading of the liquid. The peak sensitivity of the MEMS sensors is approximately 6 mV/Pa or −165 dB re 1 V/μPa, and the directional response shows a dipole pattern. The signal-to-noise ratio was found to be about 200 or 23 dB at 1 Pa incident sound pressure. The results show the potential of MEMS sensors to be used in underwater applications for sound source localization.