Low-frequency Problems Research Articles

Application of neural network algorithm in computer data information processing system

In order to solve the problem that the data processing frequency of the traditional centralized data processing system is low, which leads to the poor feedback effect of massive data, this paper proposes a computer data information processing system based on neural network algorithm. Based on the original system hardware, the system replaces the data processor and increases the total number of the processor, so as to realize the distributed synchronous processing of massive data. In the aspect of software design, the interaction between system units and modules is formed through the protocol to improve the data communication mode of the system; Calculate the Euclidean distance and set the distributed processing mode of the system; According to the definition of cloud computing, the classification function is used to determine the constraints, establish the processing frequency equation, and realize the rapid processing of massive data. The experimental results show that the processing frequency of the system designed in this paper is more than 50 % higher than that of the traditional system, which solves the problem of low processing frequency caused by weak analysis ability and slow response speed in the traditional system. Conclusioncompared with the traditional system, the system designed in this paper has faster processing frequency for massive data and better feedback effect to users.

Physics-Informed Neural Networks for High-Frequency and Multi-Scale Problems Using Transfer Learning

Physics-Informed Neural Network (PINN) is a data-driven solver for partial and ordinary differential equations (ODEs/PDEs). It provides a unified framework to address both forward and inverse problems. However, the complexity of the objective function often leads to training failures. This issue is particularly prominent when solving high-frequency and multi-scale problems. We proposed using transfer learning to boost the robustness and convergence of training PINN, starting training from low-frequency problems and gradually approaching high-frequency problems through fine-tuning. Through two case studies, we discovered that transfer learning can effectively train PINNs to approximate solutions from low-frequency problems to high-frequency problems without increasing network parameters. Furthermore, it requires fewer data points and less training time. We compare the PINN results using direct differences and L2 relative error showing the advantage of using transfer learning techniques. We describe our training strategy in detail, including optimizer selection, and suggest guidelines for using transfer learning to train neural networks to solve more complex problems.

Motion Characteristics of Self-Sensing Piezoelectric Actuator for Yarn Micro-Gripper

In order to solve the problem of low response frequency and poor consistency of conventional yarn grippers in weft accumulators, in this study, a piezoelectric yarn gripper is used instead of conventional yarn grippers and the motion characteristics of its actuator are studied. This gripper uses a bimorph piezoelectric bending actuator with a low-cost, well integrated self-sensing method based on charge measurement. The modeling of the piezoelectric micromanipulator is based on the piezoelectric and Euler–Bernoulli beam equations. The static and dynamic characteristics of the piezoelectric actuator as well as the self-sensing capability were experimentally tested. The experimental results show that the maximum output displacement at the end of the piezoelectric actuator is 834 μm, and the maximum output force is 388 μN at 150 V driving voltage. The stability and consistency of its response are also very good, with a response speed of 24 ms. The self-sensing test of the output force also proved the feasibility of the self-sensing method used, with an error of 0.74%. The piezoelectric yarn gripper studied in this paper is promising for practical clamping applications.

Uzun Dönemli Ortak Değişkenlik Çerçevesinde Fisher Hipotezi: İngiltere Örneği

This paper aims to present the long-run covariability between inflation and the interest rate of the United Kingdom by using a new method developed by Müller and Watson (2018) that eliminates the low-frequency problems. In this study, the validity of the Fisher hypothesis is investigated under structural break periods for the UK's economy. The analysis is carried out with monthly inflation and interest rate for six periods: Full sample (1920:1-2019:12), interwar years (1920:1-1939:8), fixed exchange rate (1952:1-1973:2), Post War II (1952:1-1992:9) and two different inflation targeting periods (1992:10-2008:8 and 1992:10-2019:12). The empirical finding suggests that the Fisher hypothesis holds for the United Kingdom in the long-run.

Enhanced energy transfer and multimodal vibration mitigation in an electromechanical acoustic black hole beam

Owing to their unique energy focusing capability and high-frequency damping effects, Acoustic Black Hole (ABH) structures show promise for numerous engineering applications. However, conventional ABH structures are mostly effective only above the so-called cut-on frequency, a bottlenecking deficiency that needs to be addressed if low-frequency problems are of concern. Meanwhile, achieving simultaneous high frequency ABH effects and low-frequency vibration reduction is also a challenge. In this paper, electrical linear and nonlinear shunts are intentionally added to an ABH beam via PZT patches to tactically influence its dynamics through electromechanical coupling. Both numerical and experimental results confirm that the effective frequency range of the ABH can be broadened as a result of the electrical nonlinearity induced energy transfer (ET) from low to high frequencies inside the beam. However, increased nonlinearity strength, albeit beneficial to energy transfer, jeopardizes the linear dynamic absorber (DA) effects acting on the lower-order resonances. Solutions are exploited to tackle this problem, exemplified by the use of negative capacitance in the nonlinear shunts with the embodiment of parallel linear electrical branches. On top of the nonlinear ET effects, simultaneous DA effect is also achieved for the low-frequency resonant vibration mitigation. Studies finally end up with a design methodology which embraces the principle of ET and DA to tactically cope with different frequency bands. The final outcome is the broadband multi-modal vibration reduction and the breaking down of the frequency barrier existing in conventional linear ABH structures.

WTASR: Wavelet Transformer for Automatic Speech Recognition of Indian Languages

Automatic speech recognition systems are developed for translating the speech signals into the corresponding text representation. This translation is used in a variety of applications like voice enabled commands, assistive devices and bots, etc. There is a significant lack of efficient technology for Indian languages. In this paper, an wavelet transformer for automatic speech recognition (WTASR) of Indian language is proposed. The speech signals suffer from the problem of high and low frequency over different times due to variation in speech of the speaker. Thus, wavelets enable the network to analyze the signal in multiscale. The wavelet decomposition of the signal is fed in the network for generating the text. The transformer network comprises an encoder decoder system for speech translation. The model is trained on Indian language dataset for translation of speech into corresponding text. The proposed method is compared with other state of the art methods. The results show that the proposed WTASR has a low word error rate and can be used for effective speech recognition for Indian language.

Kutta–Joukowski Theorem for Unsteady Linear Aerodynamics

This paper presents the extension of the Kutta–Joukowski theorem to unsteady linear aerodynamics. Starting from the formulation developed by Theodorsen for the solution of the velocity potential for circulatory flows around thin, rectilinear airfoils, the frequency response function between bound circulation and circulatory lift is derived. To provide a formulation suitable for time-domain applications, two finite-state approximations of the Kutta–Joukowski frequency response function, with different degrees of complexity and accuracy, are also proposed. The validity of the derived unsteady Kutta–Joukowski theorem is verified by correlation with numerical predictions of the circulatory lift given by a validated boundary-element-method solver for potential flows. Furthermore, the proposed finite-state approximations of the unsteady Kutta–Joukowski theorem are applied to problems concerning the circulatory lift response to damped oscillatory airfoil motion and gust perturbation. The higher-accuracy finite-state model provides predictions that correspond perfectly to those obtained by the convolution integrals of the step responses given by the theories of Wagner and Küssner. The results given by the simpler finite-state model derived from the linear approximation of the frequency response function are satisfactory for low-frequency problems, and are compared with those provided by a widely used approximate unsteady version of the Kutta–Joukowski theorem available in the literature.

Nonlinear features and energy transfer in an Acoustic Black Hole beam through intentional electromechanical coupling

Acoustic Black Hole (ABH) phenomenon features unique wave retarding and energy focusing of flexural waves inside thin-walled structures whose thickness follows a power-law variation. Existing studies, mostly focusing on linear aspects, show the deficiency of the linear ABH structures in coping with low-frequency problems, typically below the so-called cut-on frequency. In this paper, electrical nonlinearities are intentionally imposed via PZT patches over an ABH beam to tactically influence its dynamics through electromechanical coupling. Using a fully coupled electromechanical beam model, typical electromechanical coupling phenomena between the beam and the external nonlinear circuits, as well as the resultant salient nonlinear features of the system, are numerically investigated. Results show the beneficial effects arising from the intentional electrical nonlinearity in terms of generating energy transfer from low to high frequencies inside the beam, before being dissipated by the ABH covered by a small amount of damping materials. As such, the effective frequency range of the ABH is broadened, conducive to low-frequency vibration control problems. Meanwhile, different from existing mechanical means, the introduced intentional electrical nonlinearity allows for flexible tuning to accommodate specific frequency ranges arising from different applications.

Multi-failure detection using device hierarchical attention network

With rapid developments in the information industry, data centers have become increasingly important for collecting and storing data. The devices in data centers are not only connected to external machines to provide a variety of services, but they also store vast amounts of data, as device failures in data centers can result in fatal and heavy economic damage. Various methods have been studied in recent years to effectively predict failures in connected devices. However, in data center-scale systems, there is a problem of low frequency of failure when predicting the failure for each device. In addition, there are complex failures that may occur within the data center owing to a mix of devices and systems, and it is difficult to determine the cause of failure in such cases. In this study, we present a device hierarchical attention network (DHAN) methodology that can predict all device failures by simultaneously using existing device information regarding the devices in the data center. Because the devices in the data center could potentially affect each other, this information regarding the device is used in a composite manner. When using information from a single device, it was observed that failure could be predicted more effectively compared to the results obtained from failure prediction. In addition, by extracting attention information from the DHAN model, we identified a device that plays an important role in predicting the failure of a particular device. Thereafter, we utilized it to cluster and reconstruct the DHAN model and identify the results of predicting failures more effectively. Based on the results presented herein, it is expected that the proposed system can be stably maintained and repaired by identifying the potential impact of the devices.

Optimized Voltage-Led Customer Load Active Service Using Genetic Algorithm in Distribution Networks

To mitigate the low frequency problem in a transmission system in an event of a power station failure or during low renewable generation production, UK National Grid (NG) Electricity System Operator has balancing mechanism in place with generators to provide temporary extra power, or with large energy users to reduce load demand or so call fast reserve services. This paper presents an alternative method to aggregately control the existing distribution network primary on load transformer tap changers as a voltage-led customer load active service. The main benefits of the proposed method are (i) to unlock the distribution network load demand flexibility without causing any negative impact on customers, and (ii) to provide the lowest cost of fast reserve service from a distribution network to transmission network. In this paper an optimal control strategy based on genetic algorithm is proposed and developed to achieve an optimized voltage-led customer load active service with the aim of finding the optimal dispatch of on load transformer tap changers by minimizing each transformer tap switching operation as well as network losses. Two practical 102 buses and 222 buses UK distribution networks have been modelled and used to demonstrate and compare the effectiveness of the proposed control methods under different operating conditions. The performances of the proposed method are also compared with both the rule-based and the branch-and-bound methods. The results show that the proposed optimal control strategy based on the genetic algorithm is more effective by achieving more accuracy and a faster solution for a large distribution network than other two methods. These are important findings as the fast reserve service by transmission network requires the accuracy of the load demand reduction delivery within 2 minutes.

A bidirectional and low-frequency energy harvester for collecting human crowd energy in shopping malls

Human crowd kinetic energy is a promising electricity source in shopping malls. Harvesting human crowd energy can supply considerable power for lighting and door control. In this study, a bidirectional low-frequency energy harvester was proposed, analysed, fabricated, and tested. The harvester was mainly composed of a hinge, four one-way bearings, one sun gear, one internal gear, one planetary gearbox and one direct current motor. The hinge was used to connect the door. The combination of these one-way bearings, hollow shaft, solid shaft and gears transformed the bidirectional movement into unidirectional movement. The utilization of the planetary gearbox boosted the velocity of the door movement to overcome the low-frequency problems. The motor generated a varied direct current voltage. A theoretical analysis was performed to ascertain the factors that would determine the energy harvester’s performance. A full-size prototype was fabricated, a simulated shopping door environment was created, and experiments were investigated. The simulation results correlated well with the experimental results. At an ultralow door movement (45°/s), the harvester can output an open-circuit voltage of 7.4 V (steady voltage) and a power of 3046 mW. The harvester had a high efficiency up to 56.79%. The harvested voltage can power electronic locks, LED billboards and wireless doorbells, all of which are necessary apparatuses in shopping malls. The proposed harvester can potentially be used in shopping malls to harvest plentiful human crowd kinetic energy.

The Hybrid FEM-DBCI for the Solution of Open-Boundary Low-Frequency Problems

This paper describes a particular use of the hybrid FEM-DBCI, for the computation of low-frequency electromagnetic fields in open-boundary domains. Once the unbounded free space enclosing the system has been truncated, the FEM is applied to the bounded domain thus obtained, assuming an unknown Dirichlet condition on the truncation boundary. An integral equation is used to express this boundary condition in which the integration surface is selected in the middle of the most external layer of finite elements, very close to the truncation boundary, so that the integral equation becomes quasi-singular. The method is described for the computation of electrostatic fields in 3D and of eddy currents in 2D, but it is also applicable to the solution of other kinds of electromagnetic problems. Comparisons are made with other methods, concluding that FEM-DBCI is competitive with the well-known FEM-BEM and coordinate transformations for what concerns accuracy and computing time.

Kernel Degeneration Based Integral Equation Solver for Low Frequency Problems

In this paper, the kernel degeneration-based boundary element method (BEM) is applied to accelerate solving the low frequency eddy current problems. With ${\mathcal{H}}$ -matrix method as the mathematical framework, the admissible blocks are compressed by the kernel degeneration-based method, while the inadmissible ones are computed and stored as full matrices. The robustness and efficiency of the proposed method are validated by solving the low frequency eddy current problems.

Association between single session service attendance and clinical characteristics in administrative data.

A large proportion of young people accessing specialist mental health services do so for a single session. The aim of the present study was to examine the characteristics of young people attending specialist mental health services for a single session and to examine associations between single session attendance and clinical characteristics. Secondary analysis of administrative data on N = 23,300 young people (mean age = 12.73 years, 57% female, 64% White British) was conducted. The mean number of sessions attended was 4.33 and 46% (10,669) attended for a single session. Multilevel logistic regression analysis showed that younger children, Black young people (OR = 1.20, 95% CI = 1.01-1.43) or those whose ethnicity was not stated (OR = 1.25, 95% CI = 1.15-1.35), young people with peer relationship difficulties (OR = 1.11, 95% CI = 1.04-1.19) or low frequency problems (OR = 1.06, 95% CI = 0.99-1.14), and those with more complexity factors (OR = 1.07, 95% CI = 1.04-1.10) were more likely to attend services for a single session. The present study sets out research questions to prompt future research: (1) the experience of attending services for a single session, (2) identifying groups of single session attenders who do not require further support compared to those who are not able to sustain engagement with more sessions, and (3) whether new care pathways are needed for these groups who currently access specialist mental health services for a single session.

An Real-Time Emergency Control Method Based On Unbalanced Transient Energy Function

In this paper, an emergency control strategy by combining generator tripping and load shedding is presented. Firstly, the unbalanced transient energy function of power system is defined, and its key features are analysed. Then, by combining the unbalanced power characteristics for power system in steady state operation condition, the method for calculating the control quantities of generator tripping and load shedding is proposed. Furthermore, a realtime closed-loop emergency control strategy is proposed. Since the proposed method by only using measurement data is based on the essential of transient instability, the accurate control quantities can be obtained. Compared with single generator tripping control, the low frequency and low voltage problem of system can be improved effectively with the combined emergency control strategy. Simulation results of New England 39-bus system validate the effectiveness of the proposed control strategy.

Метод оптимизации демпфирования на основе анализа рабочих режимов для подавления низкочастотных шумов оборудования

Aiming at the reduction of low-frequency noise problem for large equipment, a damping optimization method based on the OMA (Operational Mode Analysis) is proposed. Due to the stability of the mode frequencies and shapes, damping application could make efficient noise reduction without bringing new problems compared with structural optimizations, which makes it one of the most important means for finalized products. Taking the engine compartment of an excavator as the study object, a damping optimization method based on the OMA test is proposed in this article, which makes a more efficient optimization for large equipment by its feasible modal test. Through simulation and experimental verification, the method is effective. The test results show that based on the OMA damping application method, the low-frequency sound power level has been significantly reduced, and after the damping application, the sound radiation power level defined by the national standard has also been reduced.

Research on improving low frequency oscillation characteristics of wind power system with DFIG-PSS-VI

The new energy represented by strong random wind power connecting to the power system may make the problem of inter-area low-frequency oscillation more serious. In this paper, a DFIG-PSS controller based on virtual impedance is constructed to solve the low-frequency oscillation problem in the wind power system. The step response of PSS-VI was carried out to test the effect of the controller to verify the advantages of PSS-VI than traditional PSS. The input signal of PSS-VI which is a controller based on PSS installed virtual impedance is the active power of DFIG. The output signal of PSS-VI is added to the reactive power control loop of rotor side controller of DFIG. DFIG-PSS-VI was built in Digsilent/Powerfactory software, and the simulation was carried out on the system of 4 machines and 2 regions. It is verified that PSS-VI can improve the low-frequency oscillation of wind power system.

Unstructured PEEC method with the use of surface impedance boundary condition

PurposeThis paper aims to study unstructured-partial element equivalent circuit (PEEC) method for modelling electromagnetic regions with surface impedance condition (SIBC) is proposed. Two coupled circuits representations are used for solving both electric and/or magnetic effects in thin regions discretized by a finite element surface mesh. The formulation is applied in the context of low frequency problems with volumic magnetic media and coils. Non simply connected regions are treated with fundamental branch independent loop matrices coming from the circuit representation.Design/methodology/approachBecause of the use of Whitney face elements, two coupled circuits representations are used for solving both electric and/or magnetic effects in thin regions discretized by a finite element surface mesh. The air is not meshed.FindingsThe new surface impedance formulation enables the modeling of volume conductive regions to efficiently simulate various devices with only a surface mesh.Research limitations/implicationsThe propagation effects are not taken into account in the proposed formulation.Originality/valueThe formulation is original and is efficient for modeling non simply connected conductive regions with the use of SIBC. The unstructured PEEC SIBC formulation has been validated in presence of volume magnetic nonconductive region and compared with a SIBC FEM approach. The computational effort is considerably reduced in comparison with volume approaches.

Gathering energy from ultra-low-frequency human walking using a double-frequency up-conversion harvester in public squares

Conventional human walking energy harvesters suffer from low-frequency problems. A double-frequency up-conversion magnetostrictive energy harvester was proposed, analyzed, fabricated, and tested. The harvester is mainly composed of a gear rack and a multi-leaf cam. The rack acts as the first frequency up-conversion mechanism for low-frequency walking. The multi-leaf cam carries out the second frequency up-conversion operation. After the two steps, the low walking frequency is increased. A theoretical analysis of the energy harvester was conducted to find factors that influence its performance. A standard concrete block was proposed, which made the application of the energy harvester easy and fast. The energy harvester was fabricated and experiments were carried out. The ratio of the frequency up-conversion mechanism was 8.13. The maximum output voltage and output power of the harvester were 10.06 V (peak-to-peak) and 31.3 mW, respectively. The harvested energy could light up 100 light-emitting diodes (LEDs) at the same time. It could also power an electronic clock normally for more than 90 min. The proposed energy harvester can be applied for gathering low-frequency human walking energy in public squares.

An Improved Nodal Finite-Element Method for Magnetotelluric Modeling

Numerical modeling is an efficient tool for theoretical study and interpretation of electromagnetic geophysical phenomena. The magnetotelluric method (MT) is a frequency-domain electromagnetic tool that utilizes natural variation in the Earth's magnetic field as a source. Numerical modeling of MT requires solving low-frequency time-harmonic plane-wave electromagnetic induction problem and computing electromagnetic responses of inhomogeneous medium in which electrical conductivity generally varies drastically. Conventional node-based finite-element method (FEM) is not suitable for computing electromagnetic field in inhomogeneous conductivity structure. In this article, an improved nodal FEM is proposed. The method contains the current continuity condition in the governing equations, where the electrical field is decomposed into two parts: one is divergence-free and another is curl-free, and a penalty stabilizing term is introduced into the double-curl equation. Furthermore, the right-hand side of the linear system is replaced by an equivalent source vector, which can be analytically calculated with a background model, to improve the accuracy of the solution. Numerical examples show that the proposed method is accurate and stable for the quasi-static magnetotelluric modeling of structures with highly discontinuous conductivity.