Series Arc Fault Identification Method Based on Multi-Feature Fusion

With the increase of various loads connected to the low-voltage distribution system, the difficulty of identifying low-voltage series fault arcs has greatly increased, which seriously threatens the electricity safety. Aiming at such problems, a neural network algorithm based on multi-feature fusion is proposed. The fault current has the characteristics of randomness, high frequency noise, and singularity. A GA-BP neural network model is built, and the wavelet analysis method (based on singularity), Fourier transform method (based on high frequency noise), current cycle difference method (based on randomness), and current cycle similarity derivation method (based on randomness) are used for feature extraction and can more comprehensively reflect the characteristics of arc faults. Simulation results show that the multi-feature fusion algorithm has a higher recognition rate than other algorithms. Moreover, compared with the support vector machine model, logistic regression model, and AlexNet model, the GA-BP neural network model has a higher recognition accuracy than the other three models, which can reach 99%.

Reconfigurable Architectures with High-Frequency Noise Suppression for Wearable ECG Devices

Recent advances in electronics and microelectronics have aided the development of low-cost devices that are widely used as well-being or preventive monitoring devices by many people. Remote health monitoring, which includes wearable sensors, actuators, and modern communication and information systems, offers effective programs that allow people to live peacefully in their own homes while also being protected in some way. High-frequency noise, power-line interface, and baseline drift are prevalent during the data-acquisition system of an ECG signal, and they can limit signal understanding. They (noises) must be isolated in order to provide an appropriate diagnostic of the patient. When removing high-frequency components (noise) from an ECG signal with an FIR filter, the critical path delay increases considerably as the filter's duration increases. To reduce high-frequency noise, simple moving average filters with pipelining and look-ahead transformation techniques are extensively used in this study. With the use of pipelining and look-ahead techniques, the only objective is to increase the clock speed of the designs. The moving average filters (conventional and proposed) were created on an Altera Cyclone IV FPGA EP4CE115F29C7 chip using the Quartus II software v13.1 tool. Finally, performance metrics such logic elements, clock speed, and power consumption were compared and studied thoroughly. The recursive pipelined 8-tap MA filter with look-ahead approach outperforms the other designs (685.48 MHz) in this investigation.

Features of time variations of microseismic noise at seismic stations in Tajikistan

The spectral structure of microseismic noise in the frequency range of 0.01-40 Hz at different times of the day and year, recorded by broadband equipment at eight IRIS group seismic stations in Tajikistan in 2005-2020, was analyzed. Two disjoint frequency ranges are distinguished, which we conditionally call "high-frequency" (2-40 Hz) and "low-frequency" (0.01-0.75 Hz) noise, separated by a natural drop in the noise amplitude to 20-30 Db. It is assumed that the high-frequency range of noise has a local nature, due to exogenous sources of natural origin in the form of wind gusts, concussions from powerful watercourses and fluctuations in the level of large reservoirs, as well as man-made in-terference due to road and quarry explosions, the work of large industrial enterprises and concussions from road traffic. Low-frequency noise is most likely caused by global storm microseisms. High-frequency noise has a well-defined daily frequency, which is completely absent in low-frequency noise. At the same time, in both frequency ranges, the existence of a clearly pronounced seasonal peri-odicity has been established, the amplitude of which reaches 6-7 Db for high-frequency noise and about half as much for low-frequency noise. However, at the same time, the seasonal frequency of high frequency and low-frequency noise turns out to be antiphase, which indicates in favor of the different genesis of these two components of microseismic noise. The amplitude of the diurnal periodicity in variations of the high-frequency noise level is maximal during the daytime, remaining approximately constant for 8-10 hours. At the same time, the decline in the noise amplitude in the evening lasts longer than the steeper morning growth. The time intervals of a sharp increase and decrease in the intensity of the discussed daily extreme are quite well correlated, respectively, with morning and evening twilight at different times of the year. This is reflected in the wider flat part of the maximum noise level in summer compared to winter and the differences in its level up to 6 Db in favor of summer time. This observation can be considered as a manifestation of the deep influence of the Sun on the oscillatory processes that generate high-frequency microseismic noise.

Fractional Control of a Lightweight Single Link Flexible Robot Robust to Strain Gauge Sensor Disturbances and Payload Changes

In this paper, a method to control one degree of freedom lightweight flexible manipulators is investigated. These robots have a single low-frequency and high amplitude vibration mode. They hold actuators with high friction, and sensors which are often strain gauges with offset and high-frequency noise. These problems reduce the motion’s performance and the precision of the robot tip positioning. Moreover, since the carried payload changes in the different tasks, that vibration frequency also changes producing underdamped or even unstable time responses of the closed-loop control system. The actuator friction effect is removed by using a robust two degrees of freedom PID control system which feeds back the actuator position. This is called the inner loop. After, an outer loop is closed that removes the link vibrations and is designed based on the combination of the singular perturbation theory and the input-state linearization technique. A new controller is proposed for this outer loop that: (1) removes the strain gauge offset effects, (2) reduces the risk of saturating the actuator due to the high-frequency noise of strain gauges and (3) achieves high robustness to a change in the payload mass. This last feature prompted us to use a fractional-order PD controller. A procedure for tuning this controller is also proposed. Simulated and experimental results are presented that show that its performance overcomes those of PD controllers, which are the controllers usually employed in the input-state linearization of second-order systems.

Rigid DNA nanotube tethers suppress high frequency noise in dual-trap optical tweezers systems

Dual trap optical tweezers are a powerful tool to trap and characterize the biophysical properties of single biomolecules such as the folding pathways of proteins and nucleic acids, and the chemomechanical activity of molecular motors. Despite its vastly successful application, noise from drift and fluctuation of the optics, and Brownian motion of the trapped beads still hinder the technique's ability to directly visualize folding of small biomolecules or the single nucleotide stepping of polymerases, especially at low forces (<10 pN) and sub-millisecond timescales. Rigid DNA nanotubes have been used to replace the conventional dsDNA linker to reduce optical tweezers noise in the low force range. However, optical tweezers are used to study a wide range of biophysical events, with timescales ranging from microseconds to seconds, and length changes ranging from sub nanometers to tens of nanometers. In this study, we systematically evaluate how noise is distributed across different frequencies in dual trap optical tweezers systems and show that rigid DNA nanotube tethers suppress only high frequency noise (kHz), while the low frequency noise remains the same when compared to that of dsDNA tethers.

Impact of effective mass changes with mole-fraction on the analog/radio frequency benchmarking parameters in junctionless GaxIn1−xAs/GaAs field-effect transistor

In this paper, for the first time, changes in the effective mass (EM) of electron and hole with mole fraction are taken into account for extracting the benchmarking parameters of analog/radio frequency (RF) and high-frequency noise performance of junctionless (JL)-Ga[Formula: see text]In[Formula: see text]As/GaAs via simulation. In the JL-Ga[Formula: see text]In[Formula: see text]As/GaAs structure, considering changes in the effective mass with mole fraction is called a with-EM state, while the JL-Ga[Formula: see text]In[Formula: see text]As/GaAs structure without considering the changes in effective mass with mole fraction is called a without-EM state. The simulation results show that, per [Formula: see text], the maximum transconductance in the with-effective mass (EM) state is [Formula: see text] mS/[Formula: see text]m, which is reduced by 8% compared to the without-EM state. The JL-Ga[Formula: see text]In[Formula: see text]As/GaAs device in the with-EM state has the unity gain cutoff frequency of [Formula: see text] GHz, minimum noise figure of [Formula: see text] db, and available associated gain of [Formula: see text] db. The [Formula: see text] and [Formula: see text] parameters in the with-EM state decreased by 10% and 38%, respectively, compared to the without-EM state. Moreover, [Formula: see text] in the with-EM state increased by 65% compared to the without-EM state. Our simulation results indicated that an increase in electron effective mass with the increased [Formula: see text] can limit the analog/RF frequency and high-frequency noise performance of the JL-Ga[Formula: see text]In[Formula: see text]As/GaAs device.

A Feasibility Study to Reduce Infrasound Emissions from Existing Wind Turbine Blades Using a Biomimetic Technique

Infrasound, i.e., low-frequency noise in the frequency range of 10–200 Hz, produced by rotating wind turbine blades has become a matter of concern because it is harmful to human health. Today, with the rapid increase of wind turbine size, this kind of noise is more worrying than ever. Although much effort has been made to design quiet wind turbine blades, today there is still a lack of effective techniques to reduce infrasound emissions from existing blades. To fill this gap in technology, a biomimetic technique that can be readily applied to reduce infrasound emissions of existing wind turbine blades is studied in this paper using both numerical simulation and experimental testing approaches. The numerical study of the technique is based on the analysis of the sound field distribution near the blade, which is derived by performing both aerodynamic and acoustic simulations of the blade. The experimental study of the technique is based on laboratory tests of two scale models of the blade. Both numerical and experimental studies have shown that the shedding vortices behind the blade can be successfully suppressed by semi-cylindrical rings wrapped on the blade. Consequently, both infrasound and the overall sound pressure level of the noise produced by the blade are significantly reduced. Although the rings fail to show good performance in reducing high-frequency noise, it is not a problem for human health because high-frequency noise is weak and moreover it attenuates rapidly as distance increases. The research also showed that the proposed technique can, not only reduce the infrasound produced by the blade, but can also improve the power coefficient of wind turbines.

On the resonance sound generated in a vehicle cabin moving at low speed due to breaking force

To improve the comfortability in a vehicle cabin, unwanted noise which is recognized as an allophone generated from automobile wheels was experimentally studied to investigate its generation mechanism and to develop its reduction countermeasures. In this experiment, simultaneous measurements of sound pressure and vibrational acceleration of the wheel surface were performed. Then, frequency analysis, vibrational modal analysis and operational transfer path analysis were performed by using measured data. The results show that this kind of noise started in a low frequency first and then became higher. Furthermore, the high-frequency noise was mainly generated by vibrational acceleration at its center and near the rim when the wheel spoke gets close to the brake caliper. The high-frequency noise is around 250Hz, 750Hz, 1000Hz and 1250Hz, and the wheel spoke easily gets vibration and resonance mainly from around 750Hz and 1000Hz. Vibration at 750Hz occurs on the side of the wheel spoke in the rotation direction, while vibration at 1000Hz occurs at the midpoint of the wheel spoke. The closer to the brake caliper, louder noise was generated at the wheel spoke.