Microwave nondestructive testing (NDT) techniques show promise for composite inspection due to microwave signals' ability penetrate and interact with internal structures. However, current imaging approaches have poor spatial resolution, struggling distinguish defects from defect-free regions. This limits reliable subsurface analysis widespread adoption. paper introduces a novel multi-frequency fusion method using an open-ended waveguide deep learning enhance defect detection accuracy in...

Abstract Structural health monitoring aims to detect damage progression in materials. This study focuses on categorizing crack stages, a critical aspect of structural integrity. By leveraging acoustic emission (AE) monitoring, cracks can be analyzed data-driven manner. However, applying AE analysis poses several challenges, including discrepancies between simulated data from models and experimental the field, as well class imbalance data, with scarcity late-stage data. To bridge gap theory...

An improved anti-noise morphology vision navigation algorithm is proposed for intelligent tractor tillage in a complex agricultural field environment. At first, the two key steps of guided filtering and line extraction were addressed detail. Then, experiments carried out order to verify effectiveness advancement presented algorithm. Finally, optimal template its application condition studied improving image-processing speed. The comparison experiment results show that YCbCr color space has...

Abstract Systems in service continue to degrade with the passage of time. Pipelines are among most common systems that wear away usage. For public safety, it is utmost importance monitor pipelines. Magnetic flux leakage (MFL) testing a widely used nondestructive evaluation (NDE) technique for defect detections within pipelines, particularly those composed ferromagnetic materials. Pipeline inspection gauge (PIG) procedure based on line scans can collect accurate MFL readings detection....

The following topics are dealt with: learning (artificial intelligence); condition monitoring; remaining life assessment; production engineering computing; maintenance engineering; fault diagnosis; mechanical neural nets; recurrent and regression analysis.

We develop a high-Q capacitive sensing based robust non-destructive evaluation (NDE) methodology that can be widely used in varied NDE applications. show the proposed method detect defects host of regimes where uncertainties such as lift-off, probe tilt, fluctuations sampling rates, and step sizes are inherent data collection process. explicitly characterize corruption due to various lift-off uncertainties. use Bayesian decision theoretic approach rigorously understand impact these...

Adhesive bonding have been increasingly employed in composite structures owing to several advantages over mechanically fastened or riveted joints. Adhesively bonded lap joints not only yield light-weighted but also provide a more uniform stress distribution than resulting higher fatigue life. However, modeling the physics behind crack initiation and propagation inside regions is challenging especially under loading. As result, NDE techniques such as guided wave sensing required monitor...

Composite materials/structures are rapidly advancing, offering improved product efficiency, cost-effectiveness, and superior specific properties. These materials find increasing applications in corrosion resistance load-carrying structures across industries such as aerospace, wind turbines, transportation, medical equipment. Therefore, ensuring reliable non-destructive evaluation of composites is crucial to address safety concerns minimise maintenance expenses. The microwave (NDE) method...

Pipeline infrastructure systems in service are aging and continue to deteriorate with the passage of time. For public safety, it is extremely important accurately detect harmful defects these pipelines replace corresponding pipe sectors before they lead leakages. However, due regular usages, inner surfaces can be rather non-smooth inundated several scratches tiny cavities. Their minor within pipeline do-not need immediate repair. As such, will very expensive if sections just containing...

We propose a model assisted method to identify damage types and severity based on mode converted wave strength. Machine learning techniques are employed develop classification models complemented by the finite element simulation models. Finite provide training data for various cases of involving common damages in composites. Damage conversion strength versus frequency curves participating four modes. For recognition classification, multi-layer Convoluted Neural Network (CNN) has been trained...

The structural integrity of safety-critical infrastructures diminishes over time, necessitating periodic inspections. gathering low-noise, precise nondestructive evaluation (NDE) readings for defect detection can be both time-consuming and costly. In practical applications, NDE data highly noisy due to factors like liftoff/stand-off distances, probe drift, scanning speed, variations in acquisition rates. Given the broad spectrum potential uncertainties that contribute noise accumulation,...

Magnetic flux leakage (MFL), one of the most popular electromagnetic-based Nondestructive Evaluation (NDE) methods, is an important inspection technique for pipeline safety to prevent long-term failures. In real-life field testing or scenario, there exist lots associated uncertainties that will affect damage condition-based decision-making, therefore, it vital address and quantify involved uncertainty ensuring reliability inspection. This paper investigates effect in dynamic magnetization...

This paper investigates the impact of uncertainties during dynamic magnetization due to relative motion between magnetic flux leakage (MFL) sensors and material under test. A 3D finite element method (FEM) based model for MFL inspection system is developed better understand relationships inline (ILI) data damage parameters in nonlinear ferromagnetic materials. In real-life field testing or scenario, there exist lots associated with nondestructive evaluation (NDE), which will further affect...

Delamination is the most common type of damage that can occur in a composite structure at very early stage its operation. Detection, localization and classification delamination parameters laminates assist determining operating condition structure. Such task, especially involving global on local along thickness laminate difficult using guided waves are inherently multimodal leading to complicated mixed mode response transducers. This paper proposes use embedded thin film sensors decouple due...

Abstract Systems in service continue to degrade with passage of time. Pipelines are among the most common systems that wear away usage. For public safety it is utmost importance monitor pipelines and detect new defects within pipelines. Magnetic flux leakage (MFL) testing a widely used nondestructive evaluation (NDE) technique for defect detections pipelines, particularly those composed ferromagnetic materials. Pipeline inspection gauge (PIG) procedure based on line-scans or 2D-scans can...

Pipeline systems in service continue to degrade with passage of time due usage. Magnetic flux leakage (MFL) and Eddy Current (EC) based Non destructive evaluation (NDE) methods are most common for inline inspection (ILI) the metallic pipelines. Many times, a single measurement technique fails reveal all characteristics damage resolution constraints. This paper presents novel pixel fusion both MFL EC that can detect real defects like cracks slits sub millimeter dimension. An automated data...

Knowledge of the electrical properties, such as complex permittivity, permeability and loss tangent measurements is rapidly becoming a necessity for Nondestructive Evaluation (NDE) based material characterization. In this paper, we aim to provide data-driven approach estimate wideband dielectric permittivity given substrate on frequency responses from microstrip transmission lines fabricated with material. We demonstrate registration-aided machine learning models that adaptively use...

The use of existing natural gas pipelines for hydrogen transportation is a cost-effective and environmentally friendly solution. However, permeation can cause small cracks in pipeline walls or degrade the piping materials through electrochemical reactions, requiring improved inspection more stringent criteria detecting cracks. To address this issue, we propose novel flexible differential capacitive sensor array probe inspecting hydrogen-induced (HICs). method suppresses common mode noise,...

Composite material usage is rapidly increasing within various industries due to their unique properties. Though having better damage tolerance and corrosion resistance than metals, the presence of defects in composites may significantly affect material’s integrity strength. This paper presents a multi-frequency nearfield microwave imaging system tailored evaluate multi-layered composite materials. The employs data fusion techniques utilizing signals while improving image quality. Results...

Automotive industries in the last decade are demanding for lightweight, corrosion resistance and improved fatigue performance materials. Composites having all such properties quickly gain popularity. Due to complex fabrication methods, composites known various process defects. Thus, monitoring characterizing composite component before assembly is necessary maintain overall structural integrity. Further a rapid reliable inspection much needed addition most automotive save time.
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