A simplified and accurate model of a surge arrester used in the residual voltage test is proposed in this paper. With the help of a genetic algorithm, the measured impulse current and residual voltage waveforms are utilized to determine circuit param...
Model mismatch is inevitable in robot control due to the presence of unknown dynamics and unknown perturbations. Traditional model predictive control algorithms are usually based on constant value assumptions and are not able to overcome the degradat...
Residual stress is closely related to the evolution process of the component fatigue state, but it can be affected by various sources. Conventional fatigue evaluation either focuses on the physical process, which is limited by the complexity of the p...
In this paper, 316 L stainless steel deposited samples were fabricated by direct layer deposition (DED) using both continuous-wave (CW) and pulsed-wave (PW) laser modes. Effects of laser modes on residual stress of deposited samples were investigated...
In hyperspectral images, ghost image residuals exceeding a certain threshold not only reduce the recognition accuracy of the imaging detection system but also decrease the target identification rate. Ghost image residuals affect both the recognition...
Geometric model fitting is a fundamental issue in computer vision, and the fitting accuracy is affected by outliers. In order to eliminate the impact of the outliers, the inlier threshold or scale estimator is usually adopted. However, a single inlie...
In this paper, quantized residual preference is proposed to represent the hypotheses and the points for model selection and inlier segmentation in multi-structure geometric model fitting. First, a quantized residual preference is proposed to represen...
Aeronautical thin-walled frame workpieces are usually obtained by milling aluminum alloy plates. The residual stress within the workpiece has a significant influence on the deformation due to the relatively low rigidity of the workpiece. To accuratel...
Outliers significantly impact the accuracy of geometric model fitting. Previous approaches to handling outliers have involved threshold selection and scale estimation. However, many scale estimators assume that the inlier distribution follows a Gauss...
In order to describe the fatigue damage state of asphalt mixture more reasonably, direct tensile tests of the fatigue and the residual strength under stress levels of 1.00 MPa, 0.50 MPa and 0.25 MPa with five parallel tests were carried out. The trab...
In low-light optical imaging, the scarcity of incident photons and the inherent limitations of imaging sensors lead to challenges such as low signal-to-noise ratio, limited dynamic range, and degraded contrast, severely compromising image quality and...
Accurate prediction and reasonable warning for dam displacement are important contents of dam safety monitoring. However, it is difficult to identify abnormal displacement based on deterministic point prediction results. In response, this paper propo...
In automatic driving, accurate prediction of vehicle trajectory is the key to achieve automatic driving, and multi-vehicle joint trajectory prediction has become an important part of modern human-computer interaction systems such as automatic driving...
Metal corrosion in high-risk areas, such as high-altitude cables and chemical factories, is very complex and inaccessible to people, which can be a hazard and compromise people’s safety. Embedding deep learning models into edge computing device...
The water jet peening (WJP) technology can induce compressive residual stress (RS) in metal surfaces and, thus, improve the fatigue life of components. In this paper, a mathematical model is proposed for calculating the RS induced by WJP. To validate...
Internal state variable models are well suited to predict the effects of an evolving microstructure as a result of metal-based additive manufacturing (MBAM) processes in components with complex features. As advanced manufacturing techniques such as M...
During aerospace thin-walled component processing, the prediction and control of machining deformation have gained increasing attention. The initial residual stress in the blank is a major factor leading to the occurrence of machining deformation. Th...
This paper investigates the residual stresses induced by a longitudinal turning operation in 15-5PH martensitic stainless steel. An experimental investigation has quantified the sensitivity of residual stresses to cutting speed, feed, tool geometry a...
A better residual stress prediction model can lead to more accurate life assessments, better manufacturing process design and improved component reliability. Accurate modeling of transformation-induced plasticity (TRIP) is critical for improving resi...
Prestressed concrete (PSC) beams are widely used in critical infrastructure but are highly susceptible to corrosion in aggressive environments, which can significantly compromise their structural performance. Accurate prediction of residual flexural...
The method based on convolution neural networks (CNNs) has been widely developed and applied to residual life prediction, and many excellent results have been achieved. However, CNN models can only learn feature information relative to size, and it i...
Developing accurate, efficient, and robust closure models is essential in the construction of reduced order models (ROMs) for realistic nonlinear systems, which generally require drastic ROM mode truncations. We propose a deep residual neural network...
In this study, we introduce a novel model, the Combined Model, composed of a conditional denoising diffusion model (SR3) and an enhanced residual network (EResNet), for reconstructing high-resolution turbulent flow fields from low-resolution flow dat...
Shot peening is a surface treatment process commonly used to enhance the fatigue properties of metallic engineering components. In industry, various types of shots are used, and a common strategy is to regenerate a portion (approximately up to 35% of...
Despite the fact the Laplace transform has an appreciable efficiency in solving many equations, it cannot be employed to nonlinear equations of any type. This paper presents a modern technique for employing the Laplace transform LT in solving the non...
We present a mathematical model for agri-food industry residual streams flow management, which serves as a decision support tool for optimizing their valorization. The aim is to determine, under a cost-benefit analysis approach, the best strategy at...
As the progress of electronics and information processing technology continues, indoor localization has become a research hotspot in wireless sensor networks (WSN). The adverse non-line of sight (NLOS) propagation usually causes large measurement err...
The scale of digital elevation models (DEMs) is vital for terrain analysis, surface simulation, and other geographic applications. Compared to traditional super-resolution (SR) methods, deep convolutional neural networks (CNNs) have shown great succe...
Structures composed of aviation aluminium alloys, characterized by their limited rigidity and thin-walled configurations, frequently exhibit deformation after processing. This paper presents an investigation into T-shaped components fabricated from p...
With the persistent rise in global energy demand, the efficient extraction of petroleum resources has become an urgent and critical issue. Polymer flooding technology, widely employed for enhancing crude oil recovery, still lacks an in-depth understa...
Traditional machine learning-based methods for the detection of rice degree of milling (DOM) that are not comprehensive in feature extraction and have low recognition rates fail to meet the demand for fast, non-destructive, and accurate detection. Th...
There is currently a growing need for energy, which, combined with climate change, has increased the focus on renewable energies. Among them, biomass energy takes the lion’s share, and this can create forestry pressures or lead to the excessive...
To enhance the accuracy of dam displacement prediction, this paper proposes a hybrid model combining Random Forest (RF), a Convolutional Neural Network (CNN), and a Residual Attention Informer (RA-Informer). Firstly, RF is utilized to assess the impo...
This work presents a multi-scale one-way-coupled thermo-mechanical method to determine the residual stress in an Atmospheric Plasma Spray (APS) process. The model uses three submodelling scale levels that range from the entire component (macroscopic)...
Numerical models are associated with uncertainties that can be reduced through data assimilation (DA). Lower costs have driven a recent tendency to use Lagrangian instruments such as drifters and floats to obtain information about water bodies. Howev...
Potato (Solanum tuberosum L.) is a chlorine-sensitive crop. When soil Cl− concentrations exceed optimal thresholds, the yield and quality of potatoes are limited. Consequently, chloride-containing fertilizers are rarely used in actual agricultu...
The projection objective lens holds a pivotal role in lithography, directly influencing imaging system quality and, consequently, the lithography machine’s feature dimensions. Optical inspection methods for this lens require advancements in cal...
Rural fires have been a constant concern, with most being associated with land abandonment. However, some fires occur due to negligent attitudes towards fire, which is often used to remove agroforestry leftovers. In addition to the fire risk, this bu...
In this paper, we introduce an analytical approximate solution of nonlinear fractional Volterra population growth model based on the Caputo fractional derivative and the Riemann fractional integral of the symmetry order. The residual power series met...
Surface defect inspection is vital for the quality control of products and the fault diagnosis of equipment. Defect inspection remains challenging due to the low level of automation in some manufacturing plants and the difficulty in identifying defec...
Objective: This study aimed to identify reliable risk factors for residual/recurrent cervical intraepithelial lesions in patients with negative margins after cold-knife conization. Methods: A total of 2352 women with HSILs (high-grade squamous intrae...
Experimental research of bone strength remains costly and limited for ethical and technical reasons. Therefore, to predict the mechanical state of bone tissue, as well as similar materials, it is desirable to use computer technology and mathematical...
Knowledge graph completion (KGC) utilizes known knowledge graph triples to infer and predict missing knowledge, making it one of the research hotspots in the field of knowledge graphs. There are still limitations in generating high-quality entity emb...
Accurate forecasting of annual runoff time series is of great significance for water resources planning and management. However, considering that the number of forecasting factors is numerous, a single forecasting model has certain limitations and a...
Tree species classification is an important and challenging task in image recognition and the management of forest resources. Moreover, the task of tree species classification based on remote sensing images can significantly improve the efficiency of...
Control charts with conditional expected value (CEV) can be used with novel statistical techniques to monitor the means of moderately and lowly censored data. In recent years, machine learning and deep learning have been successfully combined with qu...
Aiming at the problem of accurate AC series arc fault detection, this paper proposes a low voltage AC series arc fault intelligent detection model based on deep learning. According to the GB/T 31143—2014 standard, an experimental platform was e...
The use of hydrocracked and straight-run vacuum residues in the production of road pavement bitumen requires a good understanding of how the viscosity and softening point can be modeled and controlled. Scientific reports on modeling of these rheologi...
Influence analysis is a critical diagnostic tool in regression modeling to ensure reliable parameter estimates. This study evaluates the effectiveness of diagnostic methods for detecting influential observations in the lognormal regression model usin...
Residuals are essential in regression analysis for evaluating model adequacy, validating assumptions, and detecting outliers or influential data. While traditional residuals perform well in linear regression, they face limitations in exponential fami...
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