Mobile Universal Device for Monitoring Frequency of Electrical Signal

2018 ◽  
Author(s):  
A.V. Batalin ◽  
A.V. Ershov
Keyword(s):  
Electrical Signal ◽  
Monitoring Frequency ◽  
Universal Device

Analysis of magneto rheological elastomers for energy harvesting systems

2020 ◽  
Vol 64 (1-4) ◽  
pp. 439-446
Author(s):  
Gildas Diguet ◽  
Gael Sebald ◽  
Masami Nakano ◽  
Mickaël Lallart ◽  
Jean-Yves Cavaillé
Keyword(s):  
Magnetic Field ◽  
Energy Harvesting ◽  
Shear Strain ◽  
Magnetic Induction ◽  
Magnetic Particles ◽  
Homogeneous Magnetic Field ◽  
Electrical Signal ◽  
Harvesting Systems ◽  
Dc Bias ◽  
Magneto Rheological

Magneto Rheological Elastomers (MREs) are composite materials based on an elastomer filled by magnetic particles. Anisotropic MRE can be easily manufactured by curing the material under homogeneous magnetic field which creates column of particles. The magnetic and elastic properties are actually coupled making these MREs suitable for energy conversion. From these remarkable properties, an energy harvesting device is considered through the application of a DC bias magnetic induction on two MREs as a metal piece is applying an AC shear strain on them. Such strain therefore changes the permeabilities of the elastomers, hence generating an AC magnetic induction which can be converted into AC electrical signal with the help of a coil. The device is simulated with a Finite Element Method software to examine the effect of the MRE parameters, the DC bias magnetic induction and applied shear strain (amplitude and frequency) on the resulting electrical signal.

Adaptive identification methods of nonlinear random electrical signal

2020 ◽  
Vol 64 (1-4) ◽  
pp. 431-438
Author(s):  
Jian Liu ◽  
Lihui Wang ◽  
Zhengqi Tian
Keyword(s):  
Wavelet Transform ◽  
Electric Vehicle ◽  
Signal To Noise Ratio ◽  
Sudden Change ◽  
Electrical Signal ◽  
Signal Recognition ◽  
State Variable ◽  
Signal Characteristics ◽  
The Matrix ◽  
Kalman Filter Algorithm

The nonlinearity of the electric vehicle DC charging equipment and the complexity of the charging environment lead to the complex and changeable DC charging signal of the electric vehicle. It is urgent to study the distortion signal recognition method suitable for the electric vehicle DC charging. Focusing on the characteristics of fundamental and ripple in DC charging signal, the Kalman filter algorithm is used to establish the matrix model, and the state variable method is introduced into the filter algorithm to track the parameter state, and the amplitude and phase of the fundamental waves and each secondary ripple are identified; In view of the time-varying characteristics of the unsteady and abrupt signal in the DC charging signal, the stratification and threshold parameters of the wavelet transform are corrected, and a multi-resolution method is established to identify and separate the unsteady and abrupt signals. Identification method of DC charging distortion signal of electric vehicle based on Kalman/modified wavelet transform is used to decompose and identify the signal characteristics of the whole charging process. Experiment results demonstrate that the algorithm can accurately identify ripple, sudden change and unsteady wave during charging. It has higher signal to noise ratio and lower mean root mean square error.

METHOD FOR IDENTIFICATION OF ELECTRICAL SIGNAL DISORDERS BASED ON ADISCRETE WAVELET TRANSFORM

2020 ◽  
Vol 2 (1) ◽  
pp. 016-021
Author(s):  
B. Yu. Kisselyov ◽  
◽  
L. A. Faifer ◽  
G. Yu. Kisselyov ◽  
◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Electrical Signal

Characteristics of the dynamics of the central nervous system and att ention function in workers of shoe production

2020 ◽  
pp. 64-68
Author(s):  
F. L. Azizova ◽  
U. A. Boltaboev
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Women Workers ◽  
Functional State ◽  
The Body ◽  
Conflict Of Interests ◽  
Professional Groups ◽  
Universal Device ◽  
The Central Nervous System ◽  
Working Day

The features of production factors established at the main workplaces of shoe production are considered. The materials on the results of the study of the functional state of the central nervous system of women workers of shoe production in the dynamics of the working day are presented. The level of functional state of the central nervous system was determined by the speed of visual and auditory-motor reactions, installed using the universal device chronoreflexometer. It was revealed that in the body of workers of shoe production there is an early development of inhibitory processes in the central nervous system, which is expressed in an increase in the number of errors when performing tasks on proofreading tables. It was found that the most pronounced shift s in auditory-motor responses were observed in professional groups, where higher levels of noise were registered in the workplace. The correlation analysis showed a close direct relationship between the growth of mistakes made in the market and the decrease in production. An increase in the time spent on the task indicates the occurrence and growth of production fatigue.Funding. The study had no funding.Conflict of interests. The authors declare no conflict of interests.

Studies and Application of Auger Monitoring System for Quality Control and Assurance of Al Bondpads

2016 ◽  
Author(s):  
Hua Younan
Keyword(s):  
Quality Control ◽  
Sample Preparation ◽  
Monitoring System ◽  
Failure Mechanisms ◽  
Wafer Fabrication ◽  
Contamination Level ◽  
Auger Analysis ◽  
Low Level ◽  
Monitoring Frequency ◽  
Control Procedures

Abstract In wafer fabrication (Fab), Fluorine (F) based gases are used for Al bondpad opening process. Thus, even on a regular Al bondpad, there exists a low level of F contamination. However, the F level has to be controlled at a lower level. If the F level is higher than the control/spec limits, it could cause F-induced corrosion and Al-F defects, resulting in pad discoloration and NSOP problems. In our previous studies [1-5], the theories, characteristics, chemical and physical failure mechanisms and the root causes of the F-induced corrosion and Al-F defects on Al bondpads have been studied. In this paper, we further study F-induced corrosion and propose to establish an Auger monitoring system so as to monitor the F contamination level on Al bondpads in wafer fabrication. Auger monitoring frequency, sample preparation, wafer life, Auger analysis points, control/spec limits and OOC/OOS quality control procedures are also discussed.

scholarly journals A Theoretical Analysis of Relations between Pressure Changes along Xylem Vessels and Propagation of Variation Potential in Higher Plants

Plants ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 372
Author(s):  
Ekaterina Sukhova ◽  
Elena Akinchits ◽  
Sergey V. Gudkov ◽  
Roman Y. Pishchalnikov ◽  
Vladimir Vodeneev ◽  
...  
Keyword(s):  
Higher Plants ◽  
Initial Point ◽  
Electrical Signal ◽  
Terminal Point ◽  
Hydraulic Pressure ◽  
Long Distance ◽  
Variation Potential ◽  
Damaged Zone ◽  
Pressure Dynamics ◽  
The Impact

Variation potential (VP) is an important long-distance electrical signal in higher plants that is induced by local damages, influences numerous physiological processes, and participates in plant adaptation to stressors. The transmission of increased hydraulic pressure through xylem vessels is the probable mechanism of VP propagation in plants; however, the rates of the pressure transmission and VP propagation can strongly vary. We analyzed this problem on the basis of a simple mathematical model of the pressure distribution along a xylem vessel, which was approximated by a tube with a pressure gradient. It is assumed that the VP is initiated if the integral over pressure is more than a threshold one, taking into account that the pressure is transiently increased in the initial point of the tube and is kept constant in the terminal point. It was shown that this simple model can well describe the parameters of VP propagation in higher plants, including the increase in time before VP initiation and the decrease in the rate of VP propagation with an increase in the distance from the zone of damage. Considering three types of the pressure dynamics, our model predicts that the velocity of VP propagation can be stimulated by an increase in the length of a plant shoot and also depends on pressure dynamics in the damaged zone. Our results theoretically support the hypothesis about the impact of pressure variations in xylem vessels on VP propagation.

scholarly journals A High Sensitivity Self-Powered Wind Speed Sensor Based on Triboelectric Nanogenerators (TENGs)

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2951
Author(s):  
Yangming Liu ◽  
Jialin Liu ◽  
Lufeng Che
Keyword(s):  
Wind Speed ◽  
High Sensitivity ◽  
Electrical Signal ◽  
Geometrical Parameters ◽  
Sensor Systems ◽  
Speed Sensor ◽  
Speed Range ◽  
Self Powered ◽  
Triboelectric Nanogenerators ◽  
Application Prospects

Triboelectric nanogenerators (TENGs) have excellent properties in harvesting tiny environmental energy and self-powered sensor systems with extensive application prospects. Here, we report a high sensitivity self-powered wind speed sensor based on triboelectric nanogenerators (TENGs). The sensor consists of the upper and lower two identical TENGs. The output electrical signal of each TENG can be used to detect wind speed so that we can make sure that the measurement is correct by two TENGs. We study the influence of different geometrical parameters on its sensitivity and then select a set of parameters with a relatively good output electrical signal. The sensitivity of the wind speed sensor with this set of parameters is 1.79 μA/(m/s) under a wind speed range from 15 m/s to 25 m/s. The sensor can light 50 LEDs at the wind speed of 15 m/s. This work not only advances the development of self-powered wind sensor systems but also promotes the application of wind speed sensing.

scholarly journals Low-Frequency Signal Sampling Method Implemented in a PLC Controller Dedicated to Applications in the Monitoring of Selected Electrical Devices

Electronics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 442
Author(s):  
Marcin Jaraczewski ◽  
Ryszard Mielnik ◽  
Tomasz Gębarowski ◽  
Maciej Sułowicz
Keyword(s):  
Power System ◽  
Reactive Power ◽  
Low Frequency ◽  
Sampling Frequency ◽  
Electrical Signal ◽  
Distortion Factor ◽  
Electrical Devices ◽  
Frequency Sampling ◽  
Sampled Signal ◽  
Band Limited

High requirements for power systems, and hence for electrical devices used in industrial processes, make it necessary to ensure adequate power quality. The main parameters of the power system include the rms-values of the current, voltage, and active and reactive power consumed by the loads. In previous articles, the authors investigated the use of low-frequency sampling to measure these parameters of the power system, showing that the method can be easily implemented in simple microcontrollers and PLCs. This article discusses the methods of measuring electrical quantities by devices with low computational efficiency and low sampling frequency up to 1 kHz. It is not obvious that the signal of 50–500 Hz can be processed using the sampling frequency of fs = 47.619 Hz because it defies the Nyquist–Shannon sampling theorem. This theorem states that a reconstruction of a sampled signal is only guaranteed possible for a bandlimit fmax < fs, where fmax is the maximum frequency of a sampled signal. Therefore, theoretically, neither 50 nor 500 Hz can be identified by such a low-frequency sampling. Although, it turns out that if we have a longer period of a stable multi-harmonic signal, which is band-limited (from the bottom and top), it allows us to map this band to the lower frequencies, thus it is possible to use the lower sampling ratio and still get enough precise information of its harmonics and rms value. The use of aliasing for measurement purposes is not often used because it is considered a harmful phenomenon. In our work, it has been used for measurement purposes with good results. The main advantage of this new method is that it achieves a balance between PLC processing power (which is moderate or low) and accuracy in calculating the most important electrical signal indicators such as power, RMS value and sinusoidal-signal distortion factor (e.g., THD). It can be achieved despite an aliasing effect that causes different frequencies to become indistinguishable. The result of the research is a proposal of error reduction in the low-frequency measurement method implemented on compact PLCs. Laboratory tests carried out on a Mitsubishi FX5 compact PLC controller confirmed the correctness of the proposed method of reducing the measurement error.

scholarly journals Assessment of muscle activity using electrical stimulation and mechanomyography: a systematic review

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Raphael Uwamahoro ◽  
Kenneth Sundaraj ◽  
Indra Devi Subramaniam
Keyword(s):  
Electrical Stimulation ◽  
Processing Speed ◽  
Muscle Activity ◽  
Neuromuscular Electrical Stimulation ◽  
Voluntary Contraction ◽  
Electrical Signal ◽  
Muscle Performance ◽  
Inclusion Criteria ◽  
Activity Assessment ◽  
Experimental Protocols

AbstractThis research has proved that mechanomyographic (MMG) signals can be used for evaluating muscle performance. Stimulation of the lost physiological functions of a muscle using an electrical signal has been determined crucial in clinical and experimental settings in which voluntary contraction fails in stimulating specific muscles. Previous studies have already indicated that characterizing contractile properties of muscles using MMG through neuromuscular electrical stimulation (NMES) showed excellent reliability. Thus, this review highlights the use of MMG signals on evaluating skeletal muscles under electrical stimulation. In total, 336 original articles were identified from the Scopus and SpringerLink electronic databases using search keywords for studies published between 2000 and 2020, and their eligibility for inclusion in this review has been screened using various inclusion criteria. After screening, 62 studies remained for analysis, with two additional articles from the bibliography, were categorized into the following: (1) fatigue, (2) torque, (3) force, (4) stiffness, (5) electrode development, (6) reliability of MMG and NMES approaches, and (7) validation of these techniques in clinical monitoring. This review has found that MMG through NMES provides feature factors for muscle activity assessment, highlighting standardized electromyostimulation and MMG parameters from different experimental protocols. Despite the evidence of mathematical computations in quantifying MMG along with NMES, the requirement of the processing speed, and fluctuation of MMG signals influence the technique to be prone to errors. Interestingly, although this review does not focus on machine learning, there are only few studies that have adopted it as an alternative to statistical analysis in the assessment of muscle fatigue, torque, and force. The results confirm the need for further investigation on the use of sophisticated computations of features of MMG signals from electrically stimulated muscles in muscle function assessment and assistive technology such as prosthetics control.

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