Sinusoidal Signal Research Articles

Comparison of winding configurations of a 3-phase system for generating a rotating magnetic field powered by rectangular signals

The article compares two versions of 3-phase system for generating a rotating high-frequency magnetic field f = 100 kHz powered by rectangular signals with appropriately shifted phases. Obtaining sinusoidal signals from square waveforms was obtained using passive filters consisting of capacitors and inductors. The magnetic system was housed in a ferrite torus. In one version the filter branches were connected in a delta-system (Δ) and in the other version they were connected in a (Y)-system. The delta-system delivered a 72% higher magnetic field strength than the (Y)-system at the same supply voltage. Similarly, it turned out that the delta-system gives more than 3.5 times the temperature increase rate dT/dt compared to the (Y)-system. The advantage of the delta-system is its high efficiency, which can be used in magnetic hyperthermia as a treatment supporting radio- or chemo-therapy.

A Portable Self‐Powered Turbine Spirometer for Rehabilitation Monitoring on COVID‐19

AbstractCoronavirus disease 2019 (COVID‐19) patients may experience persistent impairment of the lungs after recovery and discharge, which can cause a decline in pulmonary function. Therefore, regular pulmonary function tests are essential for COVID‐19 recovered patients, and portable, home‐based pulmonary function test devices are of great significance during the pandemic. Herein, a portable self‐powered turbine spirometer (PSTS) is designed for respiratory flow measurement and assessment of pulmonary function with high accuracy, humidity resistance, good durability, and low cost. The respiratory airflow can directly drive PSTS to produce a sinusoidal signal with a signal‐to‐noise of 40.64 dB. By utilizing the long short‐term memory (LSTM) model, the flow is successfully predicted, and the “lag‐before‐start” and “spin‐after‐stop” defects of the turbine spirometer are eliminated effectively. For pulmonary function tests, the flow‐volume loop curve can be obtained from PSTS, and pulmonary function parameters such as inspiratory capacity (IC), forced vital capacity (FVC) and forced expiratory volume in the first 1 s (FEV1) can be calculated. The accuracy of IC is over 95%, and others can reach over 97%. A portable smart pulmonary function assessment system is further developed and used to test the pulmonary function of COVID‐19 patients one month after symptom onset, demonstrating potential for assessing rehabilitation trends and long‐term follow‐up of COVID‐19 recovered patients.

Bipedal driven inertial type piezoelectric motor working under quasi-static and resonant states

An inertia piezoelectric motor based on bipedal driven, which can work in not only quasi-static but also resonant states, is proposed, designed, fabricated and studied considering the high resolution of quasi-static piezoelectric motor and the high speed of resonant piezoelectric motor. The two stators of the piezoelectric motor are drived by two sinusoidal electrical signals with 1:2 frequency ratio to generate sinusoidal vibration on the corresponding driving foot. A continuous step motion without frequency limitation is realised under the action of inertia and friction forces after synthesising the sinusoidal vibration of different frequencies into mechanical sawtooth vibration. The natural resonant frequencies of the piezoelectric motor are adjusted to a specific proportion to combine the vibrations in the resonant state through finite element analysis. In the structure of two stators, each stator has a corresponding inertia block, and the corresponding resonant frequency can be altered by adjusting the mass of the inertial block without affecting the other resonant frequency, thus markedly simplifying the design difficulty of the piezoelectric motor which can work in quasi-static and resonant states. The motion characteristics of the prototype are tested by building the prototype and experimental platform. Experimental results show that the maximum speed of the prototype is 29.3 mm s−1 and the maximum load is 2 N in the resonant state, the minimum displacement resolution of prototype motor is 0.26 μm in the quasi-static state. The motion characteristics of the prototype are consistent with the theoretical analysis, which provides an effective idea to improve the comprehensive performance of the piezoelectric motor.

Precision Agriculture Using Hanging Robot

The precision agriculture monitoring system is an emerging concept. The sensors are capable of providing information about agricultural fields and then Artificial Intelligence takes decision automatically based on the sensor values. Monitoring environmental conditions is the major factor to improve yield of the efficient crops. In this project, we present a new approach by using hanging robot with virtual assistance in the agriculture field by monitoring moisture, temperature etc.It further provides a review on the most common sensing principles that can be used for in-situ and real-time temperature and and humidity level, as well as an overview of the difficulties for deploying these sensing systems and their electronic interfaces in the harsh soil environment. It reviews existing agricultural circuits and sensing systems designed for agricultural monitoring and their limitations whilst highlighting remaining challenges in order to make automated, decision- making systems for precision agriculture, a reality. Key Word: Integrated circuit, Motor driver supply, Sinusoidal signal, Communication port, Integrated Development Environment.

Block-MUSIC in blade tip timing: Performance study of block snapshot matrix

Periodic nonuniform sampling can be viewed as a combination of uniform sampling and non-uniform sampling. Blade tip timing (BTT) technique conforms to this sampling pattern, where non-uniformity and uniformity are caused by non-uniform probe layout and rotational motion, respectively. By introducing block structure into multiple signal classification (MUSIC) for the extension of snapshot matrix, Block-MUSIC has been proved to be anti-aliasing and can filter out synchronous frequency in BTT application. However, the theoretical justification of the block structure is lacking. In this paper, a performance study of Block-MUSIC is conducted from three aspects: identifiability, stability, and resolution. Additionally, a pseudo 2-dimensional signal model is proposed to represent the periodic nonuniform sampled signal under the assumption of equally spaced probes. To support the performance study, simulations and experiments are carried out to demonstrate how the size of the snapshot matrix, the noise level, and the amplitude of sinusoidal signals affect algorithm performance. Simulation codes are available at https://github.com/superjdg/block-music4btt.

A New Algorithm for Estimating a Noiseless, Evenly Sampled, Heart Rate Modulating Signal.

Heart rate variability (HRV) is commonly intended as the variation in the heart rate (HR), and it is evaluated in the time and frequency domains with various well-known methods. In the present paper, the heart rate is considered as a time domain signal, at first as an abstract model in which the HR is the instantaneous frequency of an otherwise periodic signal, such as with an electrocardiogram (ECG). In this model, the ECG is assumed to be a frequency modulated signal, or carrier signal, where HRV or HRV(t) is the time-domain signal which is frequency modulating the carrier ECG signal around its average frequency. Hence, an algorithm able to frequency demodulate the ECG signal to extract the signal HRV(t) is described, with possibly enough time resolution to analyse fast time-domain variations in the instantaneous HR. After exhaustive testing of the method on simulated frequency modulated sinusoidal signals, the new procedure is eventually applied on actual ECG tracings for preliminary nonclinical testing. The purpose of the work is to use this algorithm as a tool and a more reliable method for the assessment of heart rate before any further clinical or physiological analysis.

T-S Fuzzy Tracking Control Based on H∞ Performance with Output Feedback for Pendulum-Cart System

In some practices, not all state variables are available because of limited or noisy measurements. Thus, via output feedback, an observer is used to estimate the unmeasured states. To apply linear controllers to the pendulum-cart system, the Takagi-Sugeno fuzzy model is utilized by linearizing the system in more than one operating point. The effect of disturbances on tracking performance is reduced to the prescribed attenuation level by H∞ performance. The stability of the whole closed-loop system is investigated using the Lyapunov function. Sufficient conditions are derived in terms of a set of Linear Matrix Inequality (LMI) to obtain the controller and observer gain. Simulation results show that the proposed control method can make the system track the sinusoidal reference signal, maintain stability, and attenuate the effect of disturbances to less than the prescribed attenuation level measured by L2 gain. In the implementation process, an adjustment is needed to move the observer’s pole and speed up the observer’s responses.

Effective Frequency Lock-In Changes of a Ring Laser Gyroscope Due to Harmonic Components of Dithering Signal

The frequency lock-in phenomenon is the most important error factor that degrades the performance of a ring laser gyroscope by causing a non-linear output to the rotational angular velocity input. To solve the problem of frequency lock-in, a mechanical dithering technique has been proposed and most successfully and widely applied to date. In addition, in the case of dithering with a sinusoidal signal of a single-frequency component, the theoretical background is well established. However, in actual applications, it is almost impossible to implement a perfect single sinusoidal signal owing to various electrical and mechanical constraints. In general, although the occupied portion is smaller than the fundamental frequency component, the dithering signal inevitably includes harmonics. Therefore, it is essential to analyze the influence of the corresponding harmonic component to accurately predict the frequency lock-in characteristics of a ring laser gyroscope. In this study, it is assumed that the dithering signal has odd harmonics, and through numerical experiments, the frequency lock-in widths of the ring laser gyroscope according to the dithering amplitude change and the effectiveness of improving the related characteristics according to the application of random dithering are analyzed. The analysis confirmed that the resonance condition, including the higher harmonics of mechanical dithering, can be a major variable that determines the frequency lock-in characteristics of the ring laser gyroscope. To improve the relevant performance of the ring laser gyroscope, in-depth research from that point of view is necessary.

Recurrent Neural Network-Based Autoencoder for Problems of Automatic Time Series Analysis at Power Facilities

Digitalization of the energy sector leads to an increase in the volume and rate of data collection. A primary barrier to the proper management of the technological data is the lack of data labeling corresponding to emergency modes, power equipment technical state, etc. Thus, despite the large amount of data, there is a shortage of labeled data suitable for training, validating and testing the machine learning models. Labeling by an expert takes too much time, so there is an actual task to automatically identify data fragments that are potentially of interest. The aim of the work is to develop an algorithm for prioritizing the fragments of the time series using the compact recurrent autoencoder. To achieve the goal, a neural network architecture was developed based on recurrent encoding and decoding cells, capable of unsupervised learning. The model was tested on two data sets: a synthetic sinusoidal signal with missing values and electric current measurements with thermal limit deviations. The substantial results of the work are the compact architecture of the autocoding model and the high interpretability of the output. The most significant achievements of the study are both the autocoding neural network model, which does not require initial assumption about the type of deviations, and the proposed algorithm for prioritizing the data fragments. The significance of the results is prooved by the reduction of the time for analyzing and labeling large data arrays with technological parameters of the electrical networks, which allows using these data for training, validating and testing.

A Sinusoidal Signal Generator Using a Delta-Sigma Modulated Look-Up Table and Analysis of Dither

Sinusoidal signal generators (SSG) are increasingly required for on-chip integration in impedance measurement architectures for bio-sensing and chemical sensing applications. For digital SSG architectures, there are inherent trade-offs among circuit area, power, and linearity. In this work, we present a new approach that encodes a delta-sigma-modulated look-up table (ΔΣM-LUT) to decrease digital circuit size and power while maintaining high linearity. In addition, we present a method for analyzing the combined periodicity of the modulator and the LUT for adding dither to further improve performance. The approach is demonstrated using a 5-bit, 2nd-order ΔΣM-LUT controlling a digital ΔΣ modulated SSG, where it enables a significant decrease in digital circuit area and power compared to state-of-the-art designs while achieving 64.6 dBc SFDR and 0.074% THD.

Application of electromagnetic disturbance technology in predicting ventriculoperitoneal shunt dependency after aneurysm-associated subarachnoid hemorrhage.

The aim of this study was to evaluate the predictive power of electromagnetic disturbance technology in patients with hydrocephalus after subarachnoid hemorrhage. This prospective, observational cohort study was conducted at The First Affiliated Hospital of Zhengzhou University and Nanfang Hospital. A total of 155 patients with subarachnoid hemorrhage (SAH) were enrolled in this study. Disturbance coefficients were recorded using a continuous sinusoidal signal in real time after SAH. The patients were divided into two groups: hydrocephalus group (patients who underwent shunt insertion within a month after SAH) and non-hydrocephalus group (patients without need for a ventriculoperitoneal shunt). We used SPSS to draw a ROC Curve to assess the ability of disturbance coefficients to predict the probability of hydrocephalus. Hydrocephalus occurred in 37 patients after SAH. The average disturbance coefficient of patients with hydrocephalus decreased by 25.14±9.78, and the disturbance coefficient of patients with no hydrocephalus decreased by 6.58±10.10 (one aspect of the present invention is a system of non-invasively monitoring hydrocephalus, cerebral edema, and intracranial bleeding comprising of a source emitting electromagnetic waves to brain tissue, a detector detecting said wave that propagates through said tissue, a signal conditioning unit amplifying and filtering said wave, a quadrature detector estimating magnitude and phases of said wave, and a parameter estimator calculating the complex wave number, relative attenuation coefficient (RAC), relative phase shift (RPS), wave speed change (WSC), and travel-time difference (TTD) of said brain, and assessing status of hydrocephalus and cerebral edema). The difference was statistically significant (t=9.825, P<0.001). The decrease in disturbance coefficient can be used to predict the occurrence of hydrocephalus, and if the disturbance coefficient decreases by more than 15.5 (sensitivity, 92.37%; specificity, 86.49%), it can be used to indicate the occurrence of hydrocephalus. The disturbance coefficient can predict the occurrence of hydrocephalus. The greater decline of the disturbance coefficient, the greater probability of occurrence of intracranial hydrocephalus. Hydrocephalus can be early detected. However, the CT scan is necessary to confirm the occurrence of hydrocephalus. Early diagnosis and early treatment may improve the prognosis of patients with hydrocephalus after subarachnoid hemorrhage.

Low-Cost Indirect Measurements for Power-Efficient In-Field Optimization of Configurable Analog Front-Ends with Self-X Properties: A Hardware Implementation

This paper presents a practical implementation and measurement results of power-efficient chip performance optimization, utilizing low-cost indirect measurement methods to support self-X properties (self-calibration, self-healing, self-optimization, etc.) for in-field optimization of analog front-end sensory electronics with XFAB 0.35 µm complementary metal oxide semiconductor (CMOS) technology. The reconfigurable, fully differential indirect current-feedback instrumentation amplifier (CFIA) performance is intrinsically optimized by employing a single test sinusoidal signal stimulus and measuring the total harmonic distortion (THD) at the output. To enhance the optimization process, the experience replay particle swarm optimization (ERPSO) algorithm is utilized as an artificial intelligence (AI) agent, implemented at the hardware level, to optimize the performance characteristics of the CFIA. The ERPSO algorithm extends the selection producer capabilities of the classical PSO methodology by incorporating an experience replay buffer to mitigate the likelihood of being trapped in local optima. Furthermore, the CFIA circuit has been integrated with a simple power-monitoring module to assess the power consumption of the optimization solution, to achieve a power-efficient and reliable configuration. The optimized chip performance showed an approximate 34% increase in power efficiency while achieving a targeted THD value of −72 dB, utilizing a 1 Vp-p differential input signal with a frequency of 1 MHz, and consuming approximately 53 mW of power. Preliminary tests conducted on the fabricated chip, using the default configuration pattern extrapolated from post-layout simulations, revealed an unacceptable performance behavior of the CFIA. Nevertheless, the proposed in-field optimization successfully restored the circuit’s performance, resulting in a robust design that meets the performance achieved in the design phase.

Feasibility of Stress Wave-Based Debond Defect Detection for RCFSTs Considering the Influence of Randomly Distributed Circular Aggregates with Mesoscale Homogenization Methodology.

In order to efficiently investigate the effect of the mesoscale heterogeneity of a concrete core and the randomness of circular coarse aggregate distribution on the stress wave propagation procedure and the response of PZT sensors in traditional coupling mesoscale finite element models (CMFEMs), firstly, a mesoscale homogenization approach is introduced to establish coupling homogenization finite element models (CHFEMs) with circular coarse aggregates. CHFEMs of rectangular concrete-filled steel tube (RCFST) members include a surface-mounted piezoelectric lead zirconate titanate (PZT) actuator, PZT sensors at different measurement distances, a concrete core with mesoscale homogeneity. Secondly, the computation efficiency and accuracy of the proposed CHFEMs and the size effect of representative area elements (RAEs) on the stress wave field simulation results are investigated. The stress wave field simulation results indicate that the size of an RAE limitedly affects the stress wave fields. Thirdly, the responses of PZT sensors at different measurement distances of the CHFEMs under both sinusoidal and modulated signals are studied and compared with those of the corresponding CMFEMs. Finally, the effect of the mesoscale heterogeneity of a concrete core and the randomness of circular coarse aggregate distribution on the responses of PZT sensors in the time domain of the CHFEMs with and without debond defects is further investigated. The results show that the mesoscale heterogeneity of a concrete core and randomness of circular coarse aggregate distribution only have a certain influence on the response of PZT sensors that are close to the PZT actuator. Instead, the interface debond defects dominantly affect the response of each PZT sensor regardless of the measurement distance. This finding supports the feasibility of stress wave-based debond detection for RCFSTs where the concrete core is a heterogeneous material.

Adaptive Robust RBF-NN Nonsingular Terminal Sliding Mode Control Scheme for Application to Snake Robot’s Head for Image Stabilization

Image stabilization is important for snake robots to be used as mobile robots. In this paper, we propose an adaptive robust RBF neural network nonsingular terminal sliding mode control to reduce swinging in the snake robot’s head while it is being driven. To avoid complex dynamic problems and reduce interference during driving, we propose a 2-DOF snake robot’s head system. We designed the control system based on the nonsingular terminal sliding mode control, which ensures a fast response and finite time convergence. To reduce chattering, we incorporated an RBF neural network that can compensate for disturbances. Additionally, we included an adaptive robust term to address the disadvantages of neural network-based control. The adaptive robust term generates control inputs based on the error and is used in conjunction with the reverse saturation function to eliminate chattering. The update law of the neural network and the adaptive robust term is designed based on Lyapunov’s theory. We proved the stability of the proposed controller by investigating finite time convergence before and after the reverse saturation function operation section. Finally, we verified the performance of the proposed controller through computer simulation. The simulation evaluates the controllers using a sinusoidal reference signal similar to snake robot movement and a mixed reference signal considering the controller’s waste case. The proposed controller has excellent tracking performance and improved chattering compared with the previous controller.

Application-Layer Time Synchronization and Data Alignment Method for Multichannel Biosignal Sensors Using BLE Protocol.

Wearable wireless biomedical sensors have emerged as a rapidly growing research field. For many biomedical signals, multiple sensors distributed about the body without local wired connections are required. However, designing multisite systems at low cost with low latency and high precision time synchronization of acquired data is an unsolved problem. Current solutions use custom wireless protocols or extra hardware for synchronization, forming custom systems with high power consumption that prohibit migration between commercial microcontrollers. We aimed to develop a better solution. We successfully developed a low-latency, Bluetooth low energy (BLE)-based data alignment method, implemented in the BLE application layer, making it transferable between manufacturer devices. The time synchronization method was tested on two commercial BLE platforms by inputting common sinusoidal input signals (over a range of frequencies) to evaluate time alignment performance between two independent peripheral nodes. Our best time synchronization and data alignment method achieved absolute time differences of 69 ± 71 μs for a Texas Instruments (TI) platform and 477 ± 490 μs for a Nordic platform. Their 95th percentile absolute errors were more comparable-under 1.8 ms for each. Our method is transferable between commercial microcontrollers and is sufficient for many biomedical applications.

Model for Choosing the Shape Parameter in the Multiquadratic Radial Basis Function Interpolation of an Arbitrary Sine Wave and Its Application

In multiquadratic radial basis function (MQ-RBF) interpolation, shape parameters have a direct effect on the interpolation accuracy. The paper presents an MQ-RBF interpolation technique with optimized shape parameters for estimating the parameters of sine wave signals. At first, we assessed the impact of basic sinusoidal parameters on the MQ-RBF interpolation outcomes through numerical experiments. The results indicated that the angular frequency of a sine wave is a crucial determinant of the corresponding MQ-RBF interpolation shape parameters. A linear regression method was then used to establish the optimal parameter selection formula for a single-frequency sine wave, based on a large volume of experimental data. For multi-frequency sinusoidal signals, appropriate interpolation shape parameters were selected using the random walk algorithm to create datasets. These datasets were subsequently used to train several regression models, which were then evaluated and compared. Based on its operational cost and prediction accuracy, the random forest algorithm was chosen to establish the shape parameter selection model for multi-frequency sinusoidal signals. The inclusion of the Bayesian optimizer resulted in a highly accurate model. The establishment of this model enabled the adaptive selection of the corresponding shape parameters for any sine wave signal, providing a convenient means of selecting MQ-RBF interpolation shape parameters. Furthermore, the paper proposes an MQ-RBF interpolation subdivision least squares method that significantly improves the estimation accuracy of sine wave parameters. The practicality of the method was validated by successfully applying it in the calibration of the clock delay mismatch of a time-interleaved analog-to-digital converter system.

Cylinder position control driven by pneumatic digital bridge circuit using a fuzzy algorithm under large stroke and varying load conditions

A digital bridge circuit based on the concept of independent metering control can enable the precise position control of a pneumatic cylinder, but large strokes and variable loads still cause challenges. To solve this problem, a piecewise on/off valve flow compensator and a composite friction observer were innovatively designed in this study, and they were combined with a multiple fuzzy intelligent algorithm to ensure the accuracy and robustness of pneumatic position control. Considering the starting and stopping delays and the response processes of on/off valves, a six-stage flow–duty ratio linearization relationship was proposed. Employing a parameter identification method, a static and dynamic composite friction model was presented. Then, a fuzzy PID controller was proposed, and a genetic algorithm was used to optimize the control parameters. Experiment results showed that, when focusing on a large stroke (250 mm) and varying loads (8.5–18.5 kg), for sinusoidal signal with amplitude of 150 mm and frequency of 0.125 Hz and the air supply pressure is 0.5 Mpa, the algorithm in this study could ensure that the steady-state step response error was less than 1% and the root mean squared error of the sinusoidal trajectory tracking was less than 3%.

Perceptual Substitution Based Haptic Texture Rendering for Narrow-Band Reproduction.

Recorded high-resolution texture vibration contains perceptually redundant spectral information due to tactile limitations of human skin. Also, accurate reproduction of recorded texture vibration is often infeasible for widely available haptic reproduction systems at mobile devices. Usually, haptic actuators can only reproduce narrow-bandwidth vibration. With the exception of research setups, rendering strategies need to be developed, that utilize the limited capabilities of various actuator systems and tactile receptors while minimizing a negative impact on perceived quality of reproduction. Therefore, the aim of this study is to substitute recorded texture vibrations with perceptually sufficient simple vibrations. Accordingly, similarity of band-limited noise, single sinusoid and amplitude-modulated signals on display are rated compared to real textures. Considering that low and high frequency bands of noise signals might be implausible and redundant, different combinations of cut-off frequencies are applied to noise vibrations. Moreover, suitability of amplitude-modulation signals are tested for coarse textures in addition to single sinusoids because of their capability of creating pulse-like roughness sensation without too low frequencies. With the set of experiments, narrowest band noise vibration with frequencies between 90 Hz to 400 Hz is determined according to the fine textures. Furthermore, AM vibrations are found to be more congruent than single sinusoids to reproduce too coarse textures.

An Endless Optical Phase Delay for Harmonic-Free Phase/Frequency Shifting in Coherent-Lite DCIs and Microwave Photonics

An optical IQ modulator (IQM), when driven by quadrature-phase sinusoidal electrical signals, adds a phase/frequency offset to the optical input. However, harmonics of the applied electrical signals are also generated in the optical domain. In this work, we analytically derive the waveform shapes that achieve a harmonic-free phase/frequency shift with high spectral purity using the IQM. Using these waveforms, an endless optical phase delay (EOPD), wherein the phase delay can be increased or decreased continuously and arbitrarily in a reset-free manner, has been presented. The EOPD can be used in coherent-lite or analog coherent receiver based DCIs, phased array LiDAR, and many other applications. In order to adjust for the bias voltages and control signal gains in the EOPD, some of which may be time varying, a multivariate gradient descent algorithm is presented. Use of the EOPD for phase synchronization in a self-homodyne coherent-lite optical link has been demonstrated, making it a promising solution for low-power high-capacity coherent data center interconnects (DCIs).

A Background Test and Calibration Technique of Nonlinear Mismatches in MEMS Oscillating Accelerometers

MEMS accelerometers have benefits of low cost and small volume, however their long-term stability is limited by the fabrication mismatches. This paper proposes a self-test and calibration technique for differential MEMS accelerometers, to reduce the effect of flicker noise in reference voltages due to nonlinear stiffness mismatch in two channels. Through detecting the frequency response induced by the sinusoidal test signal, the oscillating amplitude of the two channels is properly adjusted to meet a theoretically derived noise cancellation condition. A numerical model is established based on practical mechanical parameters of the MEMS structures to simulate the proposed system, and optimize the key design parameters. Finally, a prototype including a MEMS accelerometer chip and an FPGA-based control circuit is implemented to verify the suggested approaches. Compared to that without the proposed technique, the 1-h bias-instability of the SOA is reduced from 6.31 μg to 3.44 μg. At different reference voltages from 1.09 V to 1.33 V, the decrease in instability is between 21.7 % and 45.5 %.