Infrasound leakage signals, with low propagation energy loss, are ideal for long-distance and small leakage detection but suffer severe background noise interference. Existing wavelet denoising methods using traditional soft/hard threshold functions...
When the pulse current method is used for partial discharge (PD) monitoring of mining cables, the detected PD signals are seriously disturbed by the field noise, which are easily submerged in the noise and cannot be extracted. In order to realize the...
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...
Accurate measurement of broadband signals is fundamental to the broadband oscillation analysis of power grids. However, the measurement process of broadband signals generally suffers from noise interference and insufficient measurement accuracy. To a...
In this study, an algorithm for denoising ultrasound echo signals in industrial settings is proposed to address the problem of high noise and low signal-to-noise ratio. The algorithm combines complete ensemble empirical mode decomposition with adapti...
Acoustic emission (AE) as a non-destructive monitoring method is used to identify small damage in various materials effectively. However, AE signals acquired during the monitoring of oil and gas steel pipelines are always contaminated with noise. A n...
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...
To address the noise issue in the measured vibration signals of spillway radial gate discharge, this paper utilizes the Multiverse Optimization Algorithm (MVO) to optimize the number of decomposition modes (K) and the penalty factor (α) in Vari...
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...
In order to solve the problem of noise interference in the collected magneto mechanical signals, a new wavelet shrinkage threshold based on adaptive estimation is proposed. Based on the shortcomings of the traditional threshold function, an improved...
Guided wave ultrasonic testing (GWUT) within the realm of pipeline inspection is an efficacious approach; however, current GWUT systems are characterized by high costs and power consumption, and their detection results are significantly susceptible t...
Non-stationary, multi-component vibration signals in rotating machinery are easily contaminated by strong background noise, which masks weak fault features and degrades diagnostic reliability. This paper proposes a joint denoising method that combine...
To enhance fault detection in slewing bearing vibration signals, an advanced noise-reduction model, HRCSA-VMD-WT, is designed for effective signal noise elimination. This model innovates by refining the Chameleon Swarm Algorithm (CSA) into a more pot...
Depending on its operating conditions, traditional soot blowing is activated for a fixed time. However, low-frequency soot blowing can cause heat transfer efficiency to decrease. High-frequency soot blowing not only wastes high-pressure steam, but al...
Partial discharge (PD) is the primary factor causing insulation degradation in transformers. However, the collected signals of partial discharge are often contaminated with significant noise. This makes it difficult to extract the PD signal and hinde...
Early fault vibration signals of rolling bearings are non-stationary and nonlinear, with weak fault signatures easily masked by noise. Traditional denoising methods (e.g., wavelet thresholding, empirical mode decomposition (EMD)) struggle to accurate...
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...
In order to investigate the analysis and processing methods for nonstationary signals generated in bridge health monitoring systems, this study combines the advantages of complete ensemble empirical mode decomposition (CEEMD) and wavelet threshold de...
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...
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...
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...
Denoising is the basis and premise of image processing and an important part of image preprocessing. Denoising can effectively improve image quality, which contributes to subsequent image processing such as image segmentation, feature extraction, and...
Underwater acoustic technology as an important means of exploring the oceans is receiving more attention. Denoising for underwater acoustic information in complex marine environments has become a hot research topic. In order to realize the hydrophone...
Owing to the problems that imperfect decomposition process of empirical mode decomposition (EMD) denoising algorithm and poor self-adaptability, it will be extremely difficult to reduce the noise of signal. In this paper, a noise reduction method of...
In this paper, we propose the local complexity estimation based filtering method in wavelet domain for MRI (magnetic resonance imaging) denoising. A threshold selection methodology is proposed in which the edge and detail preservation properties for...
To achieve high-precision geomagnetic matching navigation, a reliable geomagnetic anomaly basemap is essential. However, the accuracy of the geomagnetic anomaly basemap is often compromised by noise data that are inherent in the process of data acqui...
In recent years, image filtering has been a hot research direction in the field of image processing. Experts and scholars have proposed many methods for noise removal in images, and these methods have achieved quite good denoising results. However, m...
Maintenance scheduling is a fundamental element in industry, where excessive downtime can lead to considerable economic losses. Active monitoring systems of various components are ever more used, and rolling bearings can be identified as one of the p...
We propose a novel fast iterative thresholding algorithm for image compressive sampling (CS) recovery using three existing denoisers—i.e., TV (total variation), wavelet, and BM3D (block-matching and 3D filtering) denoisers. Through the use of the rec...
Due to the susceptibility of LiDAR echo signals to various noise interferences, which severely affect their detection quality and accuracy, this paper proposes a joint denoising method combining Variational Mode Decomposition (VMD), Crested Porcupine...
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...
In the imaging process of bistatic inverse synthetic aperture radar (Bi–ISAR), the echo is easily affected by the internal interference and external environment of the radar system, resulting in the problems of sparse aperture and low echo sign...
The performance of steam traps plays an important role in the normal operation of steam systems. It also contributes to the improvement of thermal efficiency of steam-using equipment and the rational use of energy. As an important component of the st...
Owing to the complexity of the ocean background noise, underwater acoustic signal denoising is one of the hotspot problems in the field of underwater acoustic signal processing. In this paper, we propose a new technique for underwater acoustic signal...
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...
In order to accurately identify the pipeline leak fault of a mine air compressor, a novel intelligent diagnosis method is presented based on the integration of an adaptive wavelet threshold denoising (WTD) algorithm, improved firefly algorithm (IFA),...
Doppler radar for monitoring vital signals is an emerging tool, and how to remove the noise during the detection process and reconstruct the accurate respiration and heartbeat signals are hot issues in current research. In this paper, a novel radar v...
Monitoring tree growth helps operators better understand the growth mechanism of trees and the health status of trees and to formulate more effective management measures. Computer vision technology can quickly restore the three-dimensional geometric...
The wavelet threshold functions are widely used in oil chromatography denoising because high-quality signals are the basis for Dissolved Gas Analysis (DGA), which determines the accuracy of transformer fault monitoring. However, there are certain lim...
Damage detection using an FBG sensor is a critical process for an assessment of any inspection technology classified as structural health monitoring (SHM). FBG signals containing noise in experiments are developed to detect flaws. In this paper, we p...
The widely used wavelet-thresholding techniques (DWT-H and DWT-S) have a near-optimal behavior that cannot be enhanced by any local denoising filter, but they cannot utilize the similarity of small-size image patches to enhance the denoising performa...
Traditional user authentication mechanisms in information systems, such as passwords and biometrics, remain vulnerable to forgery, theft, and privacy breaches. To address these limitations, this study proposes a two-factor authentication framework th...
A point machine’s gap is an important indication of its healthy status. An edge detection algorithm is proposed to measure and calculate a point machine’s gap from the gap image captured by CCD plane arrays. This algorithm integrates adaptive wavelet...
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...
Electrophysiological signals are one of the key ways that fish convey information and govern movement. Changes in physiological electrical signals may indirectly reflect changes in fish sensory thresholds and locomotor behavior. The acquisition of ph...
Wavelength modulation-tunable diode laser absorption spectroscopy (WM-TDLAS) is a critical tool for gas detection. However, noise in second harmonic signals degrades detection performance. This study presents a hybrid denoising algorithm combining Em...
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...
The continuous casting process is a continuous, complex phase transition process. The noise components of the continuous casting process are complex, the model is difficult to establish, and it is difficult to separate the noise and clear signals eff...
Traditional ultrasonic bolt stress measurement is hindered by high power consumption. Lowering excitation voltage reduces power but degrades signal-to-noise ratio (SNR), compromising accuracy. This paper proposes a synergistic algorithm combining Emp...
Wearable laser Doppler devices are susceptible to complex noise interferences, such as Gaussian white noise, baseline drift, and motion artifacts, with motion artifacts significantly impacting clinical diagnostic accuracy. Addressing the limitations...
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