Despite the increased attention that has been given to the unmanned aerial vehicle (UAV)-based magnetic survey systems in the past decade, the processing of UAV magnetic data is still a tough task. In this paper, we propose a novel noise reduction me...
Tunnels generally operate underground or underwater in a complex environment. As a result, the health monitoring system is inevitably affected by various environmental factors, which introduces noise to the system. However, the noise contained in the...
In this paper, a method for extracting the on-the-fly (OTF) GNSS tide level was designed by combining variational modal decomposition (VMD) and a wavelet thresholding (WT) method to improve the extraction accuracy of the OTF GNSS tide level. First, t...
The underground pressure disaster caused by the exploitation of deep mineral resources has become a major hidden danger restricting the safe production of mines. Microseismic monitoring technology is a universally recognized means of underground pres...
Generally, the sound signal produced by transmission unit or cutting unit contains abundant information about the working state of a machine. The acoustic-based diagnosis system presents some distinct advantages in some severe conditions particularly...
The incorporation of effective denoising techniques is a crucial requirement for seismic data processing during the acquisition phase due to the inherent susceptibility of the seismic data acquisition process to various forms of interference, such as...
Partial discharge (PD) source localization is an essential technology to identify the location of defects in power cables. This paper presents a complete cable PD localization system. To improve localization accuracy and reduce computational cost, th...
Hard thresholding is a common method for denoising wavelet coefficients. However, determining an optimal threshold remains challenging. Therefore, we propose an adaptive hard threshold that accounts for the size of the noisy image based on the statis...
This paper addresses how to use high-order diffusion to restore the wavelet coefficients in the wavelet domain. To avoid image distortion, wavelets with symmetry are used for image decomposition to obtain the wavelet coefficients of each sub-band. Du...
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...
Electrocardiographic (ECG) signal is essential to diagnose and analyse cardiac disease. However, ECG signals are susceptible to be contaminated with various noises, which affect the application value of ECG signals. In this paper, we propose an ECG s...
From the viewpoint of BDS bridge displacement monitoring, which is easily affected by background noise and the calculation of a fixed threshold value in the wavelet filtering algorithm, which is often related to the data length. In this paper, a data...
To enhance the denoising performance of satellite signals at a low signal-to-noise ratio (SNR), we propose an improved wavelet threshold denoising correlation (IWTDC) method that utilizes wavelet decomposition to analyze the received satellite signal...
Partial discharge (PD) signals are used to evaluate the insulation condition of stators in electrical machines. Their measurements are often heavily corrupted by ambient noise, making denoising essential for effective detection and analysis of PD sig...
To address complex noise in nitrogen-vacancy center fluorescence signal acquisition, a hybrid denoising framework combining marine predators algorithm-optimized variational mode decomposition (VMD) and wavelet thresholding is proposed. MPA adaptively...
Conventional sparse spike deconvolution algorithms that are based on the iterative shrinkage-thresholding algorithm (ISTA) are widely used. The aim of this type of algorithm is to obtain accurate seismic wavelets. When this is not fulfilled, the proc...
In ultrasonic Lamb wave non-destructive testing of aluminum plates, Lamb wave signals are susceptible to industrial interference, which may obscure useful information. To address this issue, this paper developed a signal denoising method combining Im...
Stable operation of fuel cell air compressions is constrained by rotating surge in low flowrate conditions. In this paper, a diagnosis criterion based on wavelet transform to solve the surge fault is proposed. First of all, the Fourier transform was...
The large size and metal-enclosed casings of oil-immersed power transformers present significant challenges for patrol robots attempting to accurately locate their position within the transformer. Therefore, this paper proposes a three-dimensional sp...
Fusarium head blight in winter wheat ears produces the highly toxic mycotoxin deoxynivalenol (DON), which is a serious problem affecting human and animal health. Disease identification directly on ears is important for selective harvesting. This stud...
Because the existing methods extract the signal characteristics of electronic communication networks, there is a problem of poor extraction. In this paper, a feature extraction method based on symmetric algorithm for transmission signals in electroni...
This paper develops a method to improve the estimation of jump variation using high frequency data with the existence of market microstructure noises. Accurate estimation of jump variation is in high demand, as it is an important component of volatil...
Although there are many methods in the literature to eliminate noise from images, finding new methods remains a challenge in the field and, despite the complexity of existing methods, many of the methods do not reach a sufficient level of applicabili...
Denoising one-dimensional signals by wavelet shrinkage critically depends on the choice of wavelet basis, yet basis selection is often guided by heuristics rather than explicit statistical criteria. This paper investigates the relationship between wa...
Noise significantly reduces the detection accuracy of transient power quality disturbances. It is critical to denoise the disturbance. The purpose of this research is to present an improved wavelet threshold denoising method and an adaptive parameter...
This paper presents a robust method for defect detection in textures, entropy-based automatic selection of the wavelet decomposition level (EADL), based on a wavelet reconstruction scheme, for detecting defects in a wide variety of structural and sta...
In the process of the intelligent inspection of belt conveyor systems, due to problems such as its long duration, the large number of rollers, and the complex working environment, fault diagnosis by acoustic signals is easily affected by signal coupl...
We introduce a smoothed variant of the Smoothly Clipped Absolute Deviation (SCAD) thresholding rule for wavelet denoising by replacing its piecewise linear transition with a raised cosine. The resulting shrinkage function is odd, continuous on
This study presents the application of a set pair analysis-based similarity forecast (SPA-SF) model and wavelet denoising to forecast annual runoff. The SPA-SF model was built from identical, discrepant and contrary viewpoints. The similarity between...
Partial discharge (PD) signals acquired from gas-insulated switchgear (GIS) are often severely contaminated by discrete-spectrum interference and periodic narrowband noise, which impairs the accuracy of subsequent fault diagnosis. This paper proposes...
Microseismic monitoring has become a well-known technique for predicting the mechanisms of rock failure in deeply buried energy exploration, in which noise has a great influence on microseismic monitoring results. We proposed an improved microseismic...
Fault diagnosis of rolling bearings can be a serious challenge, as rolling bearings often work under complex conditions and their vibration signals are typically nonlinear and nonstationary. This paper proposes a novel approach to diagnosing faults o...
Hyper-wavelet transforms, such as a non-subsampled shearlet transform (NSST), are one of the mainstream algorithms for removing random noise from ground-penetrating radar (GPR) images. Because GPR image noise is non-uniform, the use of a single fixed...
Partial Discharge (PD) measurements of large generators are extremely affected and hampered by noise, making the denoising of PD signal an inevitable issue. Wavelet shrinkage is the most commonly employed method for PD signal denoising. The appropria...
Driver behavior and intention recognition affects traffic safety. Many scholars use the steering wheel angle, distance of the brake pedal, distance of the accelerator pedal, and turn signal as input data to identify driver behaviors and intentions. H...
A tunnel health monitoring (THM) system ensures safe operations and effective maintenance. However, how to effectively process and denoise several data collected by THM remains to be addressed, as well as safety early warning problems. Thus, an integ...
Acoustic emission (AE) technology has been widely utilized to monitor the SiC wafer lapping process. The root-mean-square (RMS) of the time–domain eigenvalues of the AE signal has a linear relationship with the material removal rate (MRR). Howe...
Wavelet transformation has been widely used in geophysical and geochemical exploration, and the fractal feature of wavelet coefficients has recently stood out from many wavelet threshold methods. We introduced the wavelet–fractal method to anal...
Partial discharge (PD) in insulators will not only lead to the gradual degradation of insulation performance but even cause power system failure in serious cases. Because there is strong noise interference in the field, it is difficult to accurately...
As the sound signal of a machine contains abundant information and is easy to measure, acoustic-based monitoring or diagnosis systems exhibit obvious superiority, especially in some extreme conditions. However, the sound directly collected from indus...
Wavelet transform modulus (WTM) has been used to detect or localize transient signal discontinuities. A numerical analysis indicated that these power quality disturbance (PQD) events are extremely sensitive to the random phase offset due to shift-var...
This article investigates the problem of univariate and bivariate density estimation using wavelet decomposition techniques. Special attention is given to the estimation of copula functions, which capture the dependence structure between random varia...
In this paper, the complexities of various noises, which are quantified by wavelet energy entropy (WEE) and differential coefficient of WEE (D(WEE)), were first analyzed and their uncertainties then estimated and described using confidence intervals....
Leak detection and location of water supply pipelines is an important area of research, and it is especially important to find the leakage location in time and repair them. In view of the problem, that a large amount of noise is mixed in the detectio...
Accurate detection and effective control strategy of commutation failure (CF) of high voltage direct current (HVDC) are of great significance for keeping the safe and stable operations of the hybrid power grid. At first, a novel detection method for...
The influence of some seemingly anomalous samples on modeling is often ignored in the quantitative prediction of soil composition modeling with hyperspectral data. Soil spectral transformation based on wavelet packet technology only performs pruning...
Aiming at the problems of microseismic signals from rock mass fracture in deep-buried tunnels with low signal-to-noise ratio (SNR) suffering from coupled interference of multi-source noise, and traditional filtering methods having fixed parameters an...
Signal de-noising methods based on threshold processing of wavelet decomposition coefficients have become popular due to their simplicity, speed, and ability to adapt to signal functions with spatially inhomogeneous smoothness. The analysis of the er...
The arc sound signal is one of the most important aspects of information related to pattern identification regarding the penetration state of ship robotic GMAW; however, arc sound is inevitably affected by noise interference during the signal acquisi...
Accurate and reliable dam inflow prediction models are essential for effective reservoir operation and management. This study presents a data-driven model that couples a long short-term memory (LSTM) network with robust input predictor selection, inp...
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