Power systems have an increasing demand for operational condition monitoring and safety control aspects. Low-frequency oscillation mode identification is one of the keys to maintain the safe and stable operation of power systems. To address the probl...
The maneuvering target echo of high-resolution radar can be expressed as a multicomponent polynomial phase signal (mc-PPS). However, with improvements in radar resolution and increases in the synthetic period, classical time frequency analysis method...
System identification of offshore floating platforms is usually performed by testing small-scale models in wave tanks, where controlled conditions, such as still water for free decay tests, regular and irregular wave loading can be represented. Howev...
The purpose of denoising microseismic mine signals (MMS) is to extract relevant signals from background interference, enabling their utilization in wave classification, identification, time analysis, location calculations, and detailed mining feature...
This paper proposes a fully digital background calibration method for time-interleaved analog-to-digital converter (TIADC) mismatches. The method analyzes the frequency and phase of spurious signals caused by three types of mismatches in TIADCs in th...
Landslides are common geological hazards that often result in significant casualties and economic losses. Due to their occurrence in complex terrain areas, conventional geophysical techniques face challenges in early detection and warning of landslid...
Carbon-fiber-reinforced polymer (CFRP) composites have many advantages, and have been widely used in aerospace structures, buildings, bridges, etc. The analysis of dynamic response characteristics of CFRP composite structures is of great significance...
Numerical solutions of heterogeneous Helmholtz problems present various computational challenges, with descriptive theory remaining out of reach for many popular approaches. Robustness and scalability are key for practical and reliable solvers in lar...
Accurate identification of harmonic components is a prerequisite for addressing resonance risks in new energy power stations. Traditional Variational Modal decomposition (VMD) is susceptible to the influence of the modal decomposition order K and the...
Breathing Rate (BR), an important deterioration indicator, has been widely neglected in hospitals due to the requirement of invasive procedures and the need for skilled nurses to be measured. On the other hand, biomedical signals such as Seismocardio...
It is of great significance to detect drones in airspace due to the substantial increase and regrettable misuse in the consumer market. In this paper, we establish a micro-motion theoretical model of a drone and analyze the micro-Doppler signature of...
Wavelet decomposition is pivotal for underwater image processing, known for its ability to analyse multi-scale image features in the frequency and spatial domains. In this paper, we propose a new biorthogonal cubic special spline wavelet (BCS-SW), ba...
To address the high non-stationarity of COVID-19 pandemic time-series data and the severe error accumulation issue in long-horizon forecasting, a spatiotemporal two-branch multi-step forecasting model named CFC-FLCA is proposed. This model integrates...
Complex variational mode decomposition (CVMD) has been proposed to extend the original variational mode decomposition (VMD) algorithm to analyze complex-valued data. Conventionally, CVMD divides complex-valued data into positive and negative frequenc...
The rapid integration of renewable energy sources into modern power systems has exacerbated power quality challenges, particularly broadband oscillation phenomena that threaten grid symmetry and stability. The proposed symplectic geometric mode decom...
Diesel engines have a wide range of functions in the industrial and military fields. An urgent problem to be solved is how to diagnose and identify their faults effectively and timely. In this paper, a diesel engine acoustic fault diagnosis method ba...
The evaluation and fault diagnosis of a diesel engine’s health conditions without disassembly are very important for diesel engine safe operation. Currently, the research on fault diagnosis has focused on the time domain or frequency domain pro...
In this paper, a time-domain signal processing method is proposed to extract the real-time time-varying cable frequency. The proposed conjugate-pair decomposition (CPD) method uses empirical mode decomposition (EMD) to obtain intrinsic mode functions...
Since variational mode decomposition (VMD) was proposed, it has been widely used in condition monitoring and fault diagnosis of mechanical equipment. However, the parameters K and α in the VMD algorithm need to be set before decomposition, whic...
In this paper, a Wiener filtering algorithm in the wavelet domain is proposed to filter the laser self-mixing interference (SMI) signals, which is used to improve the accuracy of displacement reconstruction. The Wiener filter is theoretically constru...
The essential task of a Brain-Computer Interface (BCI) is to extract the motor imagery features from Electro-Encephalogram (EEG) signals for classifying the thought process. It is necessary to analyse these obtained signals in both the time domain an...
It is critical to detect hidden, periodically impulsive signatures caused by tooth defects in a gearbox. A hybrid demodulation method for detecting tooth defects has been developed in this work based on the variational mode decomposition algorithm co...
Traditional correlation analysis is analyzed separately in the time domain or the frequency domain, which cannot reflect the time-varying and frequency-varying characteristics of non-stationary signals. Therefore, a time–frequency (TF) correlat...
In seismic data processing, noise not only affects velocity analysis and seismic migration, but also causes potential risks in post-stack processing because of the artifacts. The singular value decomposition (SVD) method based on the time domain and...
The frequency-domain analysis using the fast Fourier transform (FFT) for diagnosis of eccentricity fault has been widely used in squirrel-cage induction motor (IM). However, with the restriction of sampling frequency and time acquisition, FFT analysi...
This paper presents a comprehensive review of automated modal identification techniques, focusing on various established and emerging methods, particularly Stochastic Subspace Identification (SSI). Automated modal identification plays a crucial role...
The snapshot proper orthogonal decomposition (POD) method relies on synchronously sampled datasets, significantly limiting its utility for analyzing asynchronous measurements in unsteady flow studies. This paper proposes a frequency-domain proper ort...
Order tracking has been widely used to diagnose failures of variable speed rotating machines. The performance of the TOT (Time-Frequency Domain Tacholess Order Tracking) methods is based on the correct separation of the target component strictly rela...
The response to earthquake ground motion is composed of three basic elements, namely, amplitude, frequency, and duration. The seismic response of a structure is controlled by the particular combination of these three elements. The seismic response sp...
To enhance the spectral efficiency of hybrid beamforming in millimeter-wave massive MIMO systems, the problem is formulated as a high-dimensional non-convex optimization under constant modulus constraints. A novel algorithm based on fourth-order tens...
Simulating the acoustic field excited by pulse sound sources holds significant practical value in computational ocean acoustics. Two primary methods exist for modeling underwater acoustic propagation in the time domain: the Fourier synthesis techniqu...
The identification of ground intrusion is a key and important technology in the national public security field. In this paper, a novel variational mode decomposition (VMD) and Hilbert transform (HT) is proposed for the classification of seismic signa...
Magnetotelluric (MT) sounding is a crucial technique in mineral exploration. However, MT data are highly susceptible to various types of noise. Traditional data processing methods, which rely on the assumption of signal stationarity, often result in...
This paper proposes an intelligent diagnosis method for rotating machinery faults based on improved variational mode decomposition (IVMD) and CNN to process the rotating machinery non-stationary signal. Firstly, to solve the problem of time-domain fe...
In this paper, time/frequency domain data processing was proposed to analyse the EN signal recorded during stress corrosion cracking on precipitation-hardening martensitic stainless steel in a chloride environment. Continuous Wavelet Transform, albei...
Ensuring operational reliability in machinery requires accurate fault detection. While time-domain vibration pulsation signals are intuitive for pattern recognition and feature extraction, downsampling can reduce analytical complexity, but may result...
High-frequency optical dynamic measurement can realize multiple measurement points covering the whole surface of the thin-walled structure, which is very useful for obtaining high-resolution spatial information for damage localization. However, the n...
We describe a method for reducing the cost of optical frequency domain reflectometer (OFDR) hardware by replacing two reference channels, including an auxiliary interferometer and a gas cell, with a single channel. To extract useful information, digi...
The complex remote sensing image acquisition conditions and the differences in crop growth create many crop classification challenges. Frequency decomposition enables the capture of the feature information in an image that is difficult to discern. Fr...
Long-term multivariate time series forecasting serves as a fundamental analytical tool across diverse domains, such as energy management, transportation analysis, and meteorology. However, conventional modeling paradigms often yield suboptimal result...
A precise short-term load-forecasting model is vital for energy companies to create accurate supply plans to reduce carbon dioxide production, causing our lives to be more environmentally friendly. A variety of high-voltage-level load-forecasting app...
Bearings are core components in many types of industrial equipment, and their operating environment is often accompanied by strong background noise. This results in a low Signal-to-Noise Ratio (SNR) in the collected vibration signals, making it diffi...
Aiming at the problem that it is difficult to effectively characterize the operation status of hydropower units with a single vibration signal feature under the influence of multiple factors such as water–machine–electricity coupling, a m...
Diesel engines, as power equipment, are widely used in the fields of the automobile industry, ship industry, and power equipment. Due to wear or faulty adjustment, the valve train clearance abnormal fault is a typical failure of diesel engines, which...
Improving the simulation efficiency of the spectral representation method (SRM) for nonstationary fluctuating wind fields has attracted considerable attention. To this end, this study proposes a method based on proper orthogonal decomposition (POD) d...
In order to improve the fusion quality of multispectral (MS) and panchromatic (PAN) images, a pansharpening method with a gradient domain guided image filter (GIF) that is based on non-subsampled shearlet transform (NSST) is proposed. First, multi-sc...
In recent years, unmanned aerial vehicle (UAV) technology has advanced rapidly, leading to its widespread deployment. However, this proliferation has been accompanied by a rise in unauthorized “black flight”, which poses a series of secur...
An ultrasonic reverse time migration imaging method, based on high-order singular value decomposition, is proposed in the study to solve the problems of low signal-to-noise ratio (SNR) and excessive artifacts in defect ultrasonic detection imaging re...
The capacity configuration of the energy storage system plays a crucial role in enhancing the reliability of the power supply, power quality, and renewable energy utilization in microgrids. Based on variational mode decomposition (VMD), a capacity op...
Atmospheric light detection and ranging (lidar) measurements of the attenuated backscatter coefficient (ABSC) form high-dimensional vertical profiles that vary across multiple temporal scales. Directly processing the original time-domain sequence wit...
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