FFT Method Research Articles

Acoustic fault diagnosis of three-phase induction motors using smartphone and deep learning

Faults in induction motors can halt production lines in factories, leading to downtime and resulting in production and economic losses. Therefore, it is crucial to ensure that motors operate reliably. This paper describes an approach for the acoustic fault diagnosis of rotor bars in three-phase induction motors (IM). The authors analyzed the following conditions: a healthy IM, an IM with one broken rotor bar, an IM with two broken rotor bars, and an IM with three broken rotor bars. The FFT method was used to compute the FFT spectrum of the acoustic signals. An original feature extraction method DWV (Differences of Word Vectors) was proposed to compute the acoustic features. DenseNet-201, ResNet-18, ResNet-50, and EfficientNet-b0 were used to classify these acoustic features. The computed recognition efficiency is 100 %. The proposed method was also verified using a low-pass filter of 1–1225 Hz and word coding.

Analysis of EFT Transmission Characteristics in Armoured Shielded Cables

Abstract Electrical fast transient pulses (EFT) generated when a gas-isolated substation (GIS) is switched on and off. The EFT is transmitted to the control chamber through the secondary control cable, which will cause the failure of the control equipment. In this paper, the three-dimensional electromagnetic simulation software CST (Computer Simulation Technology) is used to study the transmission characteristics of EFT in armored shielded control cables. First, an EFT analog signal is generated using an interference generator. Analyze the difference between the EFT analog signal and the EFT model in the IEC standard. The conversion method of FFT is used to analyze the spectral characteristics of EFT analog signals. According to the structural parameters, a 20-meter-long model of an armored shielded control cable was built in the CST cable studio The effect of the grounding of the shield and armor layers on the attenuation and crosstalk of EFT signals in the cable is studied. Finally, the EFT experiment of 1m long armored shielded cable is carried out, and the reliability of the research method is verified by comparing with the simulation results.

Fault diagnosis of the traction main circuit based on product-based neural network

Abstract The traction main circuit serves not only to supply power to the EMUs train set but also plays a crucial role in the initiation, speed regulation, and braking of the train. Therefore, diagnosing the operational status of the traction main circuit is of paramount importance. This paper initiates the modeling of the traction main circuit for the CRH2 EMUs train set, followed by an analysis of the primary components’ faults within the traction main circuit. Voltage and current signals from the transformer’s primary side, traction winding, as well as the stator current and speed signals of the traction motor, are collected. Fault characteristics are then extracted using FFT and wavelet analysis methods. Subsequently, employing the Product-based Neural Network (PNN), the transformer, converter, and motor are subjected to fault diagnosis. Experimental results validate the high accuracy of the proposed fault diagnosis method presented in this paper.

Discrete modeling of the calendering process for positive electrodes of Li-ion batteries

The electronic properties of Li-ion batteries crucially depend on the microstructure of their electrodes. One step of the manufacturing process, called ‘calendering’, consists in compressing the electrodes between two counterrotating cylinders to increase their density. Through a new simulation model, we investigate the effect of calendering on microstructural and electronic properties of the electrodes. Our model takes into account the real geometry of the rotating cylinder and a new contact law involving the elastic behavior of the active material and the cohesive-plastic behavior of the binder layer. Our results align well with experimental data for porosity, final thickness, and elongation. We show that the bonding structure induced by calendering involves mostly vertical tensile contacts and horizontal compressive contacts. This unexpected observation highlights the importance of shear deformation induced by rolling and thickness reduction. Using the FFT method, we also investigate the ionic and electronic conductivities of the numerically calendered electrodes.

EEG-based brain-computer interface methods with the aim of rehabilitating advanced stage ALS patients

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease that leads to progressive muscle weakness and paralysis, ultimately resulting in the loss of ability to communicate and control the environment. EEG-based Brain-Computer Interface (BCI) methods have shown promise in providing communication and control with the aim of rehabilitating ALS patients. In particular, P300-based BCI has been widely studied and used for ALS rehabilitation. Other EEG-based BCI methods, such as Motor Imagery (MI) based BCI and Hybrid BCI, have also shown promise in ALS rehabilitation. Nonetheless, EEG-based BCI methods hold great potential for improvement. This review article introduces and reviews FFT, WPD, CSP, CSSP, CSP, and GC feature extraction methods. The Common Spatial Pattern (CSP) is an efficient and common technique for extracting data properties used in BCI systems. In addition, Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), Neural Networks (NN), and Deep Learning (DL) classification methods were introduced and reviewed. SVM is the most appropriate classifier due to its insensitivity to the curse of dimensionality. Also, DL is used in the design of BCI systems and is a good choice for BCI systems based on motor imagery with big datasets. Despite the progress made in the field, there are still challenges to overcome, such as improving the accuracy and reliability of EEG signal detection and developing more intuitive and user-friendly interfaces By using BCI, disabled patients can communicate with their caregivers and control their environment using various devices, including wheelchairs, and robotic arms.

Fast Fourier transform method in peridynamic micromechanics of composites

We consider a static linear bond–based peridynamic (proposed by Silling, see J. Mech. Phys. Solids 2000; 48:175–209) composite materials (CMs) of a periodic structure. In the framework of the second background of micromechanics (also called computational analytical micromechanics), one proved that local micromechanics (LM) and peridynamic micromechanics (PM) are formally analogous to each other for CM of both random and periodic structures. It allows a straightforward generalization of LM methods (including fast Fourier transform, FFT) to their PM counterparts. So, in the PM counterpart of the implicit periodic Lippmann–Schwinger (L-S) equation in LM, we have three convolution kernels corresponding to the properties of the matrix, inclusions, and interactive interface. Eshelby tensor in LM, depending on the inclusion shape, is replaced by PM counterparts depending on the shapes of inclusions, and the interaction interface (although the Eshelby concept of homogeneous eigenfields does not work in PM). The mentioned tensors are estimated once (as in LM) in a frequency domain (also by the FFT method). The possible incorrectness of FFT applications to PM is analyzed and corrected. The polarization schemes of the solution of the L-S equation in the Fourier space have one primary unknown variable (polarization), whereas the PM counterpart contains three primary ones estimated at each step, which are formally similar to the LM case. A description of the generalized basic scheme and the Krylov approach is presented. Computational complexities O(N log2 N) of the FFT methods are the same in both LM and PM.

Bayesian uncertainty quantification of modal parameters and RRF identification of transmission towers with limited measured vibration data

The resonant response factor (RRF) sensitive to modal parameters, including the damping ratio and frequency, is a critical parameter for wind-resistant design of extra high voltage (EHV) transmission towers, because it directly affects the calculation of the wind vibration coefficient. However, the research on operational modal analysis (OMA) of in-service EHV transmission towers is limited due to the high risk of field monitoring. Therefore, it is critical to determine the size of sufficient data samples or minimum monitoring duration for the OMA of a transmission tower. In this study, an investigation of uncertainty quantification in Bayesian OMA of EHV transmission towers with small data samples from the ambient dynamic test is carried out. The uncertainty of the resonant component factor for wind-resistance design is proposed and quantified, which could provide engineering designers with a reference for confidence levels. Firstly, a field test system is installed on a multipurpose EHV transmission tower with a closed-loop cat head and a pair of cross-arms, to gather the acceleration responses. Then, the OMA for the transmission tower is carried out by the fast Bayesian FFT (FBFFT) method to determine the modal parameters as well as the associated posterior uncertainty. The small sample analysis of OMA for the transmission tower is further performed to obtain sufficient data samples and minimum monitoring duration. Finally, the distribution of the RRF is presented with the different confidential levels. It is found that a sampling length of 600 s could fulfill the basic needs of accuracy in Bayesian OMA and the determination of RRF. The outcomes of this study may provide a reference for the wind-resistance design parameter selection of the similar type of transmission towers.

Methods and metrics to assess the accuracy of heat flux data from a spark ignition IC engine

The measurement of in-cylinder heat transfer can be a valuable diagnostic tool for quantifying and improving IC engine performance. Increased heat transfer out of the combustion chamber negatively impacts overall efficiency, while heat transfer from the metal to the charge can increase knock propensity. The heat flux at various locations in an engine cylinder can be measured using heat flux probes consisting of two thermocouples – a surface thermocouple exposed to the changing in-cylinder temperatures, and a far field thermocouple which has a constant temperature at steady state operating conditions. The buildup of carbon deposits on the surface thermocouple can affect the heat flux measurements and lead to errors in the data. Heat flux measurements were performed on a proprietary single-cylinder research engine with instrumented heat flux probes in the cylinder head and cylinder liner. The engine was run rich with a high PMI fuel to expedite the buildup of carbon deposits. A metric was developed based on the output of the surface thermocouple to determine the cleanliness of the heat flux probes non-intrusively. Heat flux calculations were done using the FFT method and validated using the Cook-Felderman method. An uncertainty analysis was conducted on the heat flux data to verify that the negative heat flux observed was not due to errors in the distance between the two thermocouples or the measurement of temperature. Finally, to bolster confidence in the results, heat flux measurements were made for motoring conditions with varying coolant and intake air temperatures to gauge whether the trends in the output were in the expected direction.

Pressure pulsation of pump turbine at runaway condition based on Hilbert Huang transform

Pumped storage is an important component of electrified wire netting. The safe and stable operation of pump turbines is extremely important. Among them, pressure pulsation is one of the main causes of pump turbine vibration. The characteristics of pressure pulsation are relatively complex, and it is difficult to directly observe their temporal changes using commonly used FFT methods. The division of frequency characteristics is often vague. Meanwhile, it is difficult to explain some phenomena such as frequency doubling. This article focuses on a certain model of pump turbine and uses SST model to numerically simulate the runaway condition of the pump turbine. And the Hilbert Huang transform method is used to analyze the pressure pulsation in the vaneless region and draft tube. The results show that the main characteristic frequencies of the vaneless region are blade passing frequency 112.5 Hz and rotational frequency 12.5 Hz. The main characteristic frequencies of the draft tube are vortex rope frequency near 3 Hz which energy ratio is up to 50%, rotational frequency, and blade passing frequency. The pressure pulsation characteristics in the vaneless region have changed from a complex composition of double blade passing frequency and rotational frequency to a distribution dominated by blade passing frequency. In the passage of the guide vane, the pressure pulsation is almost only characterized by blade passing frequency. The frequency characteristics of the vaneless region between the runner and the guide vane become complex again. Meanwhile, the results show that the characteristic frequencies of the vaneless region and the draft tube propagate upstream and downstream.

Through the wall human heart beat detection using single channel CW radar.

Single-channel continuous wave (CW) radar is widely used and has gained popularity due to its simple architecture despite its inability to measure the range and angular location of the target. Its popularity arises in the industry due to the simplicity of the required components, the low demands on the sampling rate, and their low costs. Through-the-wall life signs detection using microwave Doppler Radar is an active area of research and investigation. Most of the work in the literature focused on utilizing multi-channel frequency modulated continuous wave (FMCW), CW, and ultra-wideband (UWB) radar for their capability of range and direction of arrival (DOA) estimation. In this paper, through-the-wall single-subject and two-subject concurrent heart rate detection using single-channel 24-GHz CW radar leveraged with maximal overlap discrete wavelet transform (MODWT) is proposed. Experimental results demonstrated that the repetitive measurement of seven different subjects at a distance of 20cm up to 100cm through two different barriers (wood and brick wall) showed an average accuracy of heart rate extraction of 95.27% for varied distances (20-100cm) in comparison with the Biopac ECG acquisition signal. Additionally, the MODWT method can also isolate the independent heartbeat waveforms from the two subjects' concurrent measurements through the wall. This involved four trials with eight different subjects, achieving an accuracy of 97.04% for a fixed distance of 40cm from the Radar without estimating the angular location of the subjects. Notably, it also superseded the performance of the direct FFT method for the single subject after 40cm distance measurements. The proposed simpler architecture of single-channel CW radar leveraged with MODWT has several potential applications, including post-disaster search and rescue scenarios for finding the trapped, injured people under the debris, emergency evacuation, security, surveillance, and patient vital signs monitoring.

A High-Throughput and Flexible CNN Accelerator Based on Mixed-Radix FFT Method

A High-Throughput and Flexible CNN Accelerator Based on Mixed-Radix FFT Method

FFT based iterative schemes for composite conductors with uniform boundary conditions

In the present paper, we extend the FFT method to deal with the homogenization problem of composite conductors with uniform boundary conditions. The principle of the approach consists of applying a transformation to build a periodic problem from the solution with uniform boundary conditions. It is shown that the related periodic problem must be applied to an extended domain obtained by mirror symmetry of the unit cell. The conductivity equation must then be solved on this extended domain under an applied periodic polarization field as a loading parameter. Illustrations are provided and the effective conductivity obtained with FFT is compared to finite element solutions to validate the approach. The proposed method can be applied to microstructure geometries of all kinds, including cells obtained through imaging devices.

An explicit dynamic FFT method for homogenizing heterogeneous solids under large deformations

We propose an explicit displacement-based FFT method for computational homogenization and multi-scale modeling of heterogeneous solids. Unlike existing FFT methods that solve the static equilibrium equation using implicit iterative techniques, our proposed explicit method solves dynamic equations with the Central Difference method. The voxel-like discretizations of the periodic domain and the direct calculation of gradient and divergence operations using Discrete Fourier Transform and its inverse result in a straightforward algorithm that avoids convergence issues and does not require material consistent tangents. The stability condition of this explicit method is also addressed. Four numerical examples (2D particle-reinforced composites of hyperelasticity and viscoelasticity, a 3D fiber-reinforced composite, and a 3D polycrystalline metal) illustrate that the proposed method calculates as accurately and efficiently as implicit FFT methods for quasi-static problems. Furthermore, the proposed explicit displacement-based FFT method outperforms implicit FFT methods when dealing with microstructures comprising phases with very high contrast. Moreover, since the method does not require material consistent tangents, it extends the applicability of FFT methods to the homogenization of materials with complex or black-boxed constitutive models, where consistent tangents are challenging to compute.

Time-domain fit for improved contrast in quantitative coherent anti-Stokes Raman spectroscopy.

Among the multiple coherent anti-Stokes Raman scattering (CARS) techniques that provide important quantitative molecular microscopic contrast, Fourier-transform CARS (FT-CARS) stands out with the immunity to nonresonant background and high-speed detection capacity. However, by using FFT for the exponentially decaying signal, FT-CARS faces the dilemma of choosing the delay range of the signal for high SNR or high resolution, the lack of either of which is detrimental to the quantitative contrast of imaging. Here, time-domain fit (TDF) is proposed to fully utilize the time-domain information of FT-CARS, providing optimized SNR and vibrational feature distinguishment. The capacity of noise restriction and feature distinguishment of the traditional FFT and the proposed TDF is analysed with theoretical examination and simulation. Exploiting the matrix pencil extraction of vibrational parameters, TDF is performed for quantitative analysis for simulated FT-CARS signal, and shows more accurate and consistent performance than the FFT method. FT-CARS coupled with TDF intensity evaluation holds the promise to provide micro-spectroscopic contrast with higher SNR and free of spectral overlapping, contributing to a more powerful diagnostic tool.

Decametric Solar Radio Spectrometer Based on 4-element Beamforming Array and Initial Observational Results

The dynamic spectral observation at decametric wavelength is important to study solar radio physics and space weather. However, the observing system is difficult to observe with high sensitivity at this band due to the fact that the system temperature is dominated by the sky background noise and the antenna is difficult to design with high gain. An effective solution to improve the sensitivity is constructing an antenna array based on the beamforming method. Accordingly, we develop a decametric solar radio spectrometer system based on a 4-element beamforming array. The system consists of four antennas, an 8-channel analog receiver and a digital receiver. We use the true time delay to implement the beamformer and the classical FFT method to perform spectrum analysis in the digital receiver. Operating at a frequency range of 25–65 MHz with dual-circular polarizations, the system provides high resolution dynamic spectrum with spectral resolution of ∼12 kHz and temporal resolution of ∼5.3 ms (typical). Tens of solar radio bursts have been observed successfully during the period of the trial observation, demonstrating the system’s ability to detect fine structures with high spectral and temporal resolution. In this article, we present the design, implementation, and initial observational results of the decametric solar radio spectrometer system in detail.

Dynamic mode structure analysis of the near-wake region of a Savonius-type hydrokinetic turbine

Hydrokinetic turbine is a clean technology that can effectively use tidal energy, the Savonius-type runner is very suitable for natural flows, and has been widely used in tidal energy power stations. The dynamic structure of the flow field in the near-wake region downstream has strong impact on the dense layout of the turbine, but there has been no in-depth exploration till now. To explore the potential for beneficial interactions between turbines, this study conducted numerical simulations of Savonius-type turbine, combining fast Fourier transformation and Dynamic mode decomposition to conduct in-depth analysis of the velocity fluctuation frequency distribution and dynamic mode in near-wake region, and compared the advantages and disadvantages of the two methods. This research obtained the distribution of two main frequencies in the near-wake region and clarified their excitation sources. The frequencies of turbines are mixed in the far field, greatly affects the far-field flow state in the near-wake region. The DMD method has great advantages in flow field analysis, as it does not require prior knowledge of flow field compared to FFT method. The conclusions of this study provide new considerations for large-scale arrangement of turbine units, and provide a new method for the flow state analysis.

An Improved Method for Estimating Ballistic Target Micromotion and Structural Parameters Based on ISAR Image Sequences

Micro-motion and structural parameters extraction is a critical technique for recognizing ballistic missiles. It is generally known that parameter estimation methods based on inverse synthetic aperture radar(ISAR) image sequences can effectively extract target information. However, when the signal-to-noise ratio(SNR) is low, the traditional methods are prone to cross-association problems in the nearest-neighbor association procedure, and the structural parameters obtained may only be the local optimal solution. To solve the above two problems, an improved method for estimating ballistic target micro-motion and structural parameters based on ISAR image sequences is proposed in this paper. A distance association probability revision matrix is used to address the cross-association problem, reducing the risk of association with the incorrect nearest neighbor; at the same time, the impact of noise on the frequency estimation is decreased by utilizing refinement domain search-match algorithm, which can discover a narrower estimation interval with less noise to improve SNR. The global optimization capacity for structural parameters estimation of the traditional particle swarm optimization(PSO) algorithm is enhanced by step-by-step optimization algorithm, which reduces the dimension of the high-dimensional micro-motion projection cost function to ensure optimization direction variety. Simulation results show that when SNR is -5dB, the accuracy of the precession frequency estimation is improved by 0.2Hz compared with the traditional FFT method, and the RMSE values for cone height, precession angle, and nutation angle are 0.02m, 0.2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$°$</tex-math></inline-formula> , and 0.3 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$°$</tex-math></inline-formula> , respectively, which are better than the traditional PSO algorithm.

An FFT-based crystal plasticity phase-field model for micromechanical fatigue cracking based on the stored energy density

A novel FFT-based phase-field fracture framework for modelling fatigue crack initiation and propagation at the microscale is presented. A damage driving force is defined based on the stored energy and dislocation density, relating phase-field fracture with microstructural fatigue damage. The formulation is numerically implemented using FFT methods to enable modelling of sufficiently large, representative 3D microstructural regions. The early stages of fatigue cracking are simulated, predicting crack paths, growth rates and sensitivity to relevant microstructural features. Crack propagation through crystallographic planes is shown in single crystals, while the analysis of polycrystalline solids reveals transgranular crack initiation and crystallographic crack growth.

A new aerodynamic identification technology for short-time hypersonic wind tunnels while considering inertial force interference

When aerodynamic force tests are performed in hypersonic wind tunnels, the test model in the force measurement system (FMS) will be subjected to transient impact and induced transient vibration due to the high-speed airflow generated during start-up. The output signal of the FMS will contain the real aerodynamic signal and the inertial force signal caused by model vibration. The inertial force signal completely overcomes the aerodynamic signal, strongly influencing the test accuracy of the aerodynamic force and even making the aerodynamic force signal completely unusable. Therefore, this study develops a novel intelligent aerodynamic identification method based on deep residual shrinkage network (DRSN) deep learning technology and applies this method to aerodynamic force tests in hypersonic wind tunnels. This method can achieve intelligent identification and filtering of inertial force interference signals and instrument noise signals, and improve the test accuracy of aerodynamic forces. Also, this study performed a numerical simulation experiment and a test-bed experiment; verified the results through hypersonic wind tunnel test signals; and compared the identification results of the DRSN network method with the identification results of the traditional CNN network method, the mean method and the FFT method. From comparison results, the aerodynamic force identification accuracy of the DRSN network method proposed in this paper is shown to be nearly ideal and always remains above 95%. Thus, the proposed method effectively reduces the interference of instrument noise and inertial force, markedly improving the accuracy and reliability of the hypersonic wind tunnel aerodynamic force test.

Study on sinusoidal estimation deviation of electrostatic actuated MEMS mirror torsion angle

Electrostatic MEMS micromirrors usually work in resonant state to obtain large amplitude of torsion angle. The real-time prediction of MEMS micromirror torsion angle is calculated according to the measured resonant amplitude and phase under the assumption that the relationship between the torsion angle and time is sinusoidal. However, there are few reports on the deviation of this torsion angle predication based on sinusoidal assumption. In this paper, the real resonant torsion trajectory of C1100 MEMS micromirror under different driving frequencies and voltages is measured by using microscopic laser Doppler method, and the deviation between the real trajectory and the trajectory fitted by sinusoidal curve is compared. The results show that the real trajectory of the MEMS micromirror driven by square wave is not completely consistent with the sinusoidal estimation, and the deviation increases with the increase of the torsional angle amplitude. By obtaining the frequency domain components of the torsion angle signal using FFT method, the main reason of this prediction deviation is due to composition of harmonic signals on base frequency signal. The research results reveal that the sinusoidal assumption method is only suitable for situations when the optical angle accuracy is less than 0.1°.