Built defects of homogeneous junction to enhance the lithium storage capacity of niobium pentoxide materials

Niobium pentoxide(Nb_(2)O_(5))is deemed one of the promising anode materials for lithium-ion batteries(LIBs)for its outstanding intrinsic fast Li-(de)intercalation kinetics.The specific capacity,however,is still limited,because the(de)intercalation of excessive Li-ions brings the undesired stress to damage Nb_(2)O_(5) crystals.To increase the capacity of Nb_(2)O_(5) and alleviate the lattice distortion caused by stress,numerous homogeneous H-and M-phases junction interfaces were proposed to produce coercive stress within theNb_(2)O_(5)crystals.Such interfaces bring about rich oxygen vacancies with structural shrinkage tendency,which pre-generate coercive stress to resist the expansion stress caused by excessive Li-ions intercalation.Therefore,the synthesized Nb_(2)O_(5) achieves the highest lithium storage capacity of 315 mA h g−1 to date,and exhibits high-rate performance(118 mA h g^(-1) at 20 C)as well as excellent cycling stability(138 mA h g^(-1) at 10 C after 600 cycles).

Theoretical Design of Defects as a Driving Force for Ion Transport in Li_(3)OBr Solid Electrolyte

Due to ever-increasing concerns about safety issues in using Li ionic batteries,solid electrolytes have extensively explored.The Li-rich antiperovskite Li_(3)OBr has been considered as a promising solid electrolyte candidate,but it still suffers challenges to achieve a high ionic conductivity owing to the high intrinsic symmetry of the crystal lattice.Herein,we presented a design strategy that introduces various point defects and grain boundaries to break the high lattice symmetry of Li_(3)OBr crystal,and their effect and microscopic mechanism of promoting the migration of Li-ion were explored theoretically.It has been found that Li_(i)are the dominant defects responsible for the fast Li-ion diffusion in bulk Li_(3)OBr and its surface,but they are easily trapped by the grain boundaries,leading to the annihilating of the Frenkel defect pair V'_(Li)+Li_(i),and thus limits the V'_(Li)diffusion at the grain boundaries.The V_(Br)defect near the grain boundaries can effectively drive V'_(Li)across the grain boundary,thereby converting the carrier of Li^(+)migration from Li,in the bulk and surface to V'_(Li)at the grain boundary,and thus improving the ionic conductivity in the whole Li_(3)OBr crystal.This work provides a comprehensive insight into the Li^(+)transport and conduction mechanism in the Li_(3)OBr electrolyte.It opens a new way of improving the conductivity for all-solid-state Li electrolyte material through the defect design.

Heterointerface Engineering-Induced Oxygen Defects for the Manganese Dissolution Inhibition in Aqueous Zinc Ion Batteries

Manganese-based material is a prospective cathode material for aqueous zinc ion batteries(ZIBs)by virtue of its high theoretical capacity,high operating voltage,and low price.However,the manganese dissolution during the electrochemical reaction causes its electrochemical cycling stability to be undesirable.In this work,heterointerface engineering-induced oxygen defects are introduced into heterostructure MnO_(2)(δa-MnO_(2))by in situ electrochemical activation to inhibit manganese dissolution for aqueous zinc ion batteries.Meanwhile,the heterointerface between the disordered amorphous and the crystalline MnO_(2)ofδa-MnO_(2)is decisive for the formation of oxygen defects.And the experimental results indicate that the manganese dissolution ofδa-MnO_(2)is considerably inhibited during the charge/discharge cycle.Theoretical analysis indicates that the oxygen defect regulates the electronic and band structure and the Mn-O bonding state of the electrode material,thereby promoting electron transport kinetics as well as inhibiting Mn dissolution.Consequently,the capacity ofδa-MnO_(2)does not degrade after 100 cycles at a current density of 0.5 Ag^(-1)and also 91%capacity retention after 500cycles at 1 Ag^(-1).This study provides a promising insight into the development of high-performance manganese-based cathode materials through a facile and low-cost strategy.

Micro defects formation and dynamic response analysis of steel plate of quasi-cracking area subjected to explosive load

As the protective component,steel plate had attracted extensive attention because of frequently threats of explosive loads.In this paper,the evolution of microstructure and the mechanism of damage in the quasi-cracking area of steel plate subjected to explosive load were discussed and the relationships between micro defects and dynamic mechanical response were revealed.After the explosion experiment,five observation points were selected equidistant from the quasi-cracking area of the section of the steel plate along the thickness direction,and the characteristics of micro defects at the observation points were analyzed by optical microscope(OM),scanning electron microscope(SEM) and electron backscattered diffraction(EBSD).The observation result shows that many slip bands(SBs) appeared,and the grain orientation changed obviously in the steel plate,the two were the main damage types of micro defects.In addition,cracks,peeling pits,grooves and other lager micro defects were appeared in the lower area of the plate.The stress parameters of the observation points were obtained through an effective numerical model.The mechanism of damage generation and crack propagation in the quasicracking area were clarified by comparing the specific impulse of each observation point with the corresponding micro defects.The result shows that the generation and expansion of micro defects are related to the stress area(i.e.the upper compression area,the neutral plane area,and the lower tension area).The micro defects gather and expand at the grain boundary,and will become macroscopic damage under the continuous action of tensile stress.Besides,the micro defects at the midpoint of the section of the steel plate in the direction away from the explosion center(i.e.the horizontal direction) were also studied.It was found that the specific impulse at these positions were much smaller than that in the thickness direction,the micro defects were only SBs and a few micro cracks,and the those decreased with the increase of the distance from the explosion center.

Properties of radiation defects and threshold energy of displacement in zirconium hydride obtained by new deep-learning potential

Zirconium hydride(ZrH_(2)) is an ideal neutron moderator material. However, radiation effect significantly changes its properties, which affect its behavior and the lifespan of the reactor. The threshold energy of displacement is an important quantity of the number of radiation defects produced, which helps us to predict the evolution of radiation defects in ZrH_(2).Molecular dynamics(MD) and ab initio molecular dynamics(AIMD) are two main methods of calculating the threshold energy of displacement. The MD simulations with empirical potentials often cannot accurately depict the transitional states that lattice atoms must surpass to reach an interstitial state. Additionally, the AIMD method is unable to perform largescale calculation, which poses a computational challenge beyond the simulation range of density functional theory. Machine learning potentials are renowned for their high accuracy and efficiency, making them an increasingly preferred choice for molecular dynamics simulations. In this work, we develop an accurate potential energy model for the ZrH_(2) system by using the deep-potential(DP) method. The DP model has a high degree of agreement with first-principles calculations for the typical defect energy and mechanical properties of the ZrH_(2) system, including the basic bulk properties, formation energy of point defects, as well as diffusion behavior of hydrogen and zirconium. By integrating the DP model with Ziegler–Biersack–Littmark(ZBL) potential, we can predict the threshold energy of displacement of zirconium and hydrogen in ε-ZrH_(2).

Defects evolution in n-type 4H-SiC induced by electron irradiation and annealing

Radiation damage produced in 4H-SiC by electrons of different doses is presented by using multiple characterization techniques. Raman spectra results indicate that SiC crystal structures are essentially impervious to 10 Me V electron irradiation with doses up to 3000 kGy. However, irradiation indeed leads to the generation of various defects, which are evaluated through photoluminescence(PL) and deep level transient spectroscopy(DLTS). The PL spectra feature a prominent broad band centered at 500 nm, accompanied by several smaller peaks ranging from 660 to 808 nm. The intensity of each PL peak demonstrates a linear correlation with the irradiation dose, indicating a proportional increase in defect concentration during irradiation. The DLTS spectra reveal several thermally unstable and stable defects that exhibit similarities at low irradiation doses.Notably, after irradiating at the higher dose of 1000 kGy, a new stable defect labeled as R_(2)(Ec-0.51 eV) appeared after annealing at 800 K. Furthermore, the impact of irradiation-induced defects on SiC junction barrier Schottky diodes is discussed. It is observed that high-dose electron irradiation converts SiC n-epilayers to semi-insulating layers. However, subjecting the samples to a temperature of only 800 K results in a significant reduction in resistance due to the annealing out of unstable defects.

An Analysis of Specific Categories of Birth Defects and Developmental Disabilities for Children of Participants of the Air Force Health Study

Background: The Air Force Health Study collected reproductive outcomes for live-born children of male Air Force veterans of the Vietnam War. Methods: Dioxin values for participants were obtained from blood samples. Analyses were conducted of occurrence of 16 specific categories of birth defects and developmental disabilities. Children were categorized as conceived before and after the start of participants’ Vietnam War service. Children conceived before the start of Vietnam War service were treated as being conceived when their fathers had unquantifiable dioxin values. Children conceived after the start of Vietnam War service for participants with missing dioxin values were excluded from primary analyses, but were used to assess the impact of their exclusion on conclusions. Correlation between values for specific categories for multiple children fathered by the same participant was accounted for. The dose-response relationship was treated as a step function increasing for dioxin values larger than adaptively identified individual thresholds changing with the specific category. Results: For 15 of 16 specific categories, the probability of occurrence increased substantially for a sufficiently high dioxin level above identified thresholds. Exclusion of children due to missing dioxin likely did not affect these results. Conclusions: Results supported the conclusion of substantial adverse effects on a wide variety of specific categories of birth defects and developmental disabilities due to sufficiently high exposures to dioxin, a toxic contaminant of Agent Orange used for herbicide spraying in the Vietnam War. Results may hold more generally, but might also have been affected by a variety of limitations.

Adaptability of bipedicled scalp advancement flap for coverage of huge scalp defects after tumor resection

Background:Several reconstructive techniques have been used to reconstruct scalp defects.Numerous researchers have studied the utilization of bipedicled scalp advancement flaps for scalp defect coverage.In this study,we will assess the adaptability of a bipedicled scalp advancement flap for coverage of huge scalp defects after tumor resection.Methods:This study was performed at the Plastic Surgery Department,Fayoum University Hospital,on 20 patients with huge scalp tumors treated by adequate excision and reconstructed using a bipedicled scalp advancement flap from December 2021 to July 2023.Results:The study was conducted on 20 patients:16(80%)were men and 4(20%)were women presenting with large scalp tumors.The mean age was 57.4 years(33-68 years).The sites of the tumors were 10(50%)occipital,6(30%)parietal,and 4(20%)parieto-occipital.No major complications occurred postoperatively,and the bipedicled flaps survived well in all cases,with no necrosis.Conclusion:Huge scalp defects after tumor resection can be safely reconstructed with a large versatile bipedicled advancement scalp flap,either transversely or longitudinally oriented,with favorable functional results and accepted aesthetic results,apart from the alopecic area over the grafted donor site,which can be treated by tissue expansion if desired later.

Retinal nerve fiber layer defects and chronic kidney disease:the Kailuan Eye Study

AIM:To investigate whether retinal nerve fiber layer defects(RNFLDs)is a potential risk factor for chronic kidney disease(CKD)in Chinese adults.METHODS:The Kailuan Eye Study was a populationbased study that included 14440 participants.All participants underwent detailed assessments,RNFLDs were diagnosed using color fundus photographs.RESULTS:Overall,12507 participants[8533 males(68.23%)]had complete systemic examination data and at least one evaluable fundus photograph.RNFLDs were found in 621 participants[5.0%;95%confidence interval(CI):4.6%-5.34%],and 70 cases of multiple RNFLDs were found(11.27%).After adjusting multiple factors,RNFLDs was significantly associated with CKD severity,the ORs of CKD stage 3,stage 4 and stage 5 were 1.698,4.167,and 9.512,respectively.Multiple RNFLDs were also associated with CKD severity after adjusting multiple factors,the ORs of CKD stage 3 and stage 5 were 4.465 and 11.833 respectively.Furthermore,2294 participants had CKD(18.34%,95%CI:17.68%-18.99%).After adjusting for other factors,CKD presence was significantly correlated with the presence of RNFLDs.CONCLUSION:The strongest risk factors for RNFLDs are CKD and hypertension.Conversely,RNFLDs can be an ocular feature in patients with CKD.Fundoscopy can help detect systemic diseases,and assessment for RNFLDs should be considered in CKD patients.

Association of Congenital Heart Defects (CHD) with Factors Related to Maternal Health and Pregnancy in Newborns in Puerto Rico

Background:Given the pervasive issues of obesity and diabetes both in Puerto Rico and the broader United States,there is a compelling need to investigate the intricate interplay among body mass index(BMI),pregesta-tional,and gestational maternal diabetes,and their potential impact on the occurrence of congenital heart defects(CHD)during neonatal development.Methods:Using the comprehensive System of Vigilance and Surveillance of Congenital Defects in Puerto Rico,we conducted a focused analysis on neonates diagnosed with CHD between 2016 and 2020.Our assessment encompassed a range of variables,including maternal age,gestational age,BMI,pregestational diabetes,gestational diabetes,hypertension,history of abortion,and presence of preeclampsia.Results:A cohort of 673 patients was included in our study.The average maternal age was 26 years,within a range of 22 to 32 years.The mean gestational age measured 39 weeks,with a median span of 38 to 39 weeks.Of the 673 patients,274(41%)mothers gave birth to neonates diagnosed with CHD.Within this group,22 cases were linked to pre-gestational diabetes,while 202 were not;20 instances were associated with gestational diabetes,compared to 200 without;and 148 cases exhibited an overweight or obese BMI,whereas 126 displayed a normal BMI.Conclusion:We identified a statistically significant correlation between pre-gestational diabetes mellitus and the occurrence of CHD.However,our analysis did not show a statistically significant association between maternal BMI and the likelihood of CHD.These results may aid in developing effective strategies to prevent and manage CHD in neonates.

Interface optimization and defects suppression via Na F introduction enable efficient flexible Sb_(2)Se_(3) thin-film solar cells

Sb_(2)Se_(3) with unique one-dimensional(1D) crystal structure exhibits exceptional deformation tolerance,demonstrating great application potential in flexible devices.However,the power conversion efficiency(PCE) of flexible Sb_(2)Se_(3) photovoltaic devices is temporarily limited by the complicated intrinsic defects and the undesirable contact interfaces.Herein,a high-quality Sb_(2)Se_(3) absorber layer with large crystal grains and benign [hkl] growth orientation can be first prepared on a Mo foil substrate.Then NaF intermediate layer is introduced between Mo and Sb_(2)Se_(3),which can further optimize the growth of Sb_(2)Se_(3)thin film.Moreover,positive Na ion diffusion enables it to dramatically lower barrier height at the back contact interface and passivate harmful defects at both bulk and heterojunction.As a result,the champion substrate structured Mo-foil/Mo/NaF/Sb_(2)Se_(3)/CdS/ITO/Ag flexible thin-film solar cell delivers an obviously higher efficiency of 8.03% and a record open-circuit voltage(V_(OC)) of 0.492 V.This flexible Sb_(2)Se_(3) device also exhibits excellent stability and flexibility to stand large bending radius and multiple bending times,as well as superior weak light photo-response with derived efficiency of 12.60%.This work presents an effective strategy to enhance the flexible Sb_(2)Se_(3) device performance and expand its potential photovoltaic applications.

Track Defects Recognition Based on Axle-Box Vibration Acceleration and Deep- Learning Techniques

As an important component of load transfer,various fatigue damages occur in the track as the rail service life and train traffic increase gradually,such as rail corrugation,rail joint damage,uneven thermite welds,rail squats fas-tener defects,etc.Real-time recognition of track defects plays a vital role in ensuring the safe and stable operation of rail transit.In this paper,an intelligent and innovative method is proposed to detect the track defects by using axle-box vibration acceleration and deep learning network,and the coexistence of the above-mentioned typical track defects in the track system is considered.Firstly,the dynamic relationship between the track defects(using the example of the fastening defects)and the axle-box vibration acceleration(ABVA)is investigated using the dynamic vehicle-track model.Then,a simulation model for the coupled dynamics of the vehicle and track with different track defects is established,and the wavelet power spectrum(WPS)analysis is performed for the vibra-tion acceleration signals of the axle box to extract the characteristic response.Lastly,using wavelet spectrum photos as input,an automatic detection technique based on the deep convolution neural network(DCNN)is sug-gested to realize the real-time intelligent detection and identification of various track problems.Thefindings demonstrate that the suggested approach achieves a 96.72%classification accuracy.

In-doping collaboratively controlling back interface and bulk defects to achieve efficient flexible CZTSSe solar cells

Focusing on the low open circuit voltage(V_(OC))and fill factor(FF)in flexible Cu_(2)ZnSn(S,Se)_(4)(CZTSSe)solar cells,indium(In)ions are introduced into the CZTSSe absorbers near Mo foils to modify the back interface and passivate deep level defects in CZTSSe bulk concurrently for improving the performance of flexible device.The results show that In doping effectively inhibits the formation of secondary phase(Cu(S,Se)_(2))and VSndefects.Further studies demonstrate that the barrier height at the back interface is decreased and the deep level defects(Cu_(Sn)defects)in CZTSSe bulk are passivated.Moreover,the carrier concentration is increased and the V_(OC) deficit(V_(OC,def))is decreased significantly due to In doping.Finally,the flexible CZTSSe solar cell with 10.01%power conversion efficiency(PCE)has been obtained.The synergistic strategy of interface modification and bulk defects passivation through In incorporation provides a new thought for the fabrication of efficient flexible kesterite-based solar cells.

Clinical Efficacy of GBR Technique Combined with Temporary Bridgework-Guided Gingival Contouring in Treating Upper Anterior Tooth Loss with Labial Bone Defects

Objective:To investigate the clinical effect of the guided bone regeneration(GBR)technique combined with temporary bridgework-guided gingival contouring in treating upper anterior tooth loss with labial bone defects.Methods:From July 2023 to April 2024,80 patients with upper anterior tooth loss and labial bone defects were admitted to the hospital and selected as evaluation samples.They were divided into an observation group(n=40)and a control group(n=40)using a numerical table lottery scheme.The control group received treatment with the GBR technique,while the observation group received treatment with the GBR technique combined with temporary bridges to guide gingival contouring.The two groups were compared in terms of clinical red aesthetic scores(PES),labial alveolar bone density,labial bone wall thickness,gingival papillae,gingival margin levels,and patient satisfaction.Results:The PES scores of patients in the observation group were higher than those in the control group after surgery(P<0.05).The bone density of the labial alveolar bone and the thickness of the labial bone wall in the observation group were higher than those in the control group.The levels of gingival papillae and gingival margins were lower in the observation group after surgery(P<0.05).Additionally,patient satisfaction in the observation group was higher than in the control group(P<0.05).Conclusion:The GBR technique combined with temporary bridge-guided gingival contouring for treating upper anterior tooth loss with labial bone defects can improve the aesthetic effect of gingival soft tissue,increase alveolar bone density and the thickness of the labial bone wall,and enhance patient satisfaction.This approach is suitable for widespread application in healthcare institutions.

High quality repair of osteochondral defects in rats using the extracellular matrix of antler stem cells

BACKGROUND Cartilage defects are some of the most common causes of arthritis.Cartilage lesions caused by inflammation,trauma or degenerative disease normally result in osteochondral defects.Previous studies have shown that decellularized extracellular matrix(ECM)derived from autologous,allogenic,or xenogeneic mesenchymal stromal cells(MSCs)can effectively restore osteochondral integrity.AIM To determine whether the decellularized ECM of antler reserve mesenchymal cells(RMCs),a xenogeneic material from antler stem cells,is superior to the currently available treatments for osteochondral defects.METHODS We isolated the RMCs from a 60-d-old sika deer antler and cultured them in vitro to 70%confluence;50 mg/mL L-ascorbic acid was then added to the medium to stimulate ECM deposition.Decellularized sheets of adipocyte-derived MSCs(aMSCs)and antlerogenic periosteal cells(another type of antler stem cells)were used as the controls.Three weeks after ascorbic acid stimulation,the ECM sheets were harvested and applied to the osteochondral defects in rat knee joints.RESULTS The defects were successfully repaired by applying the ECM-sheets.The highest quality of repair was achieved in the RMC-ECM group both in vitro(including cell attachment and proliferation),and in vivo(including the simultaneous regeneration of well-vascularized subchondral bone and avascular articular hyaline cartilage integrated with surrounding native tissues).Notably,the antler-stem-cell-derived ECM(xenogeneic)performed better than the aMSC-ECM(allogenic),while the ECM of the active antler stem cells was superior to that of the quiescent antler stem cells.CONCLUSION Decellularized xenogeneic ECM derived from the antler stem cell,particularly the active form(RMC-ECM),can achieve high quality repair/reconstruction of osteochondral defects,suggesting that selection of decellularized ECM for such repair should be focused more on bioactivity rather than kinship.

Visualizing extended defects at the atomic level in a Bi_(2)Sr_(2)CaCu_(2)O8_(+σ) superconducting wire

The microstructure significantly influences the superconducting properties.Herein,the defect structures and atomic arrangements in high-temperature Bi_(2)Sr_(2)CaCu_(2)O8_(+σ) superconducting wire are directly characterized via stateof-the-art scanning transmission electron microscopy.Interstitial oxygen atoms are observed in both the charge reservoir layers and grain boundaries in the doped superconductor.Inclusion phases with varied numbers of CuO_(2) layers are found,and twist interfaces with different angles are identified.This study provides insights into the structures of Bi-2212 wire and lays the groundwork for guiding the design of microstructures and optimizing the production methods to enhance superconducting performance.

Effect of Vacancy Defects on the Properties of CoS_(2) and FeS_(2)

In order to explore the effect of vacancy defects on the structural,electronic,magnetic and optical properties of CoS_(2) and FeS_(2),first-principles calculation method was used to investigate the alloys.The calculated results of materials without vacancy are consistent with those reported in the literatures,while the results of materials with vacancy defect were different from those of literatures due to the difference vacancy concentration.The Co vacancy defect hardly changes the half-metallic characteristic of CoS_(2).The Fe vacancy defect changes FeS_(2) from semiconductor to half-metal,and the bottom of the spin-down conduction band changes from the p orbital state of S to the d(t_(2g))orbital state of Fe,while the top of the valence band remains the d orbital d(eg)state of Fe.The half-metallic Co vacancy defects of CoS_(2) and Fe vacancy defects of FeS_(2) are expected to be used in spintronic devices.S vacancy defects make both CoS_(2) and FeS_(2) metallic.Both the Co and S vacancy defects lead to the decrease of the magnetic moment of CoS_(2),while both the Fe and S vacancy defects lead to the obvious magnetic property of FeS_(2).Vacancy defects enhance the absorption coefficient of infrared band and long band of visible light obviously,and produce obvious red shift phenomenon,which is expected to be used in photoelectric devices.

A Hybrid Deep Learning and Machine Learning-Based Approach to Classify Defects in Hot Rolled Steel Strips for Smart Manufacturing

Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things(IoT)and artificial intelligence(AI).Quality control is an important part of today’s smart manufacturing process,effectively reducing costs and enhancing operational efficiency.As technology in the industry becomes more advanced,identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process.In this study,we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques,incorporating a global average pooling(GAP)layer and a machine learning-based SVM classifier,with the aim of enhancing accuracy.Initially,features are extracted by the VGG19 convolutional block.Then,after processing through the GAP layer,the extracted features are fed to the SVM classifier for classification.For this purpose,we collected images from publicly available datasets,including the Xsteel surface defect dataset(XSDD)and the NEU surface defect(NEU-CLS)datasets,and we employed offline data augmentation techniques to balance and increase the size of the datasets.The outcome of experiments shows that the proposed methodology achieves the highest metrics score,with 99.79%accuracy,99.80%precision,99.79%recall,and a 99.79%F1-score for the NEU-CLS dataset.Similarly,it achieves 99.64%accuracy,99.65%precision,99.63%recall,and a 99.64%F1-score for the XSDD dataset.A comparison of the proposed methodology to the most recent study showed that it achieved superior results as compared to the other studies.

SAM Era:Can It Segment Any Industrial Surface Defects?

Segment Anything Model(SAM)is a cutting-edge model that has shown impressive performance in general object segmentation.The birth of the segment anything is a groundbreaking step towards creating a universal intelligent model.Due to its superior performance in general object segmentation,it quickly gained attention and interest.This makes SAM particularly attractive in industrial surface defect segmentation,especially for complex industrial scenes with limited training data.However,its segmentation ability for specific industrial scenes remains unknown.Therefore,in this work,we select three representative and complex industrial surface defect detection scenarios,namely strip steel surface defects,tile surface defects,and rail surface defects,to evaluate the segmentation performance of SAM.Our results show that although SAM has great potential in general object segmentation,it cannot achieve satisfactory performance in complex industrial scenes.Our test results are available at:https://github.com/VDT-2048/SAM-IS.

Method for Detecting Industrial Defects in Intelligent Manufacturing Using Deep Learning

With the advent of Industry 4.0,marked by a surge in intelligent manufacturing,advanced sensors embedded in smart factories now enable extensive data collection on equipment operation.The analysis of such data is pivotal for ensuring production safety,a critical factor in monitoring the health status of manufacturing apparatus.Conventional defect detection techniques,typically limited to specific scenarios,often require manual feature extraction,leading to inefficiencies and limited versatility in the overall process.Our research presents an intelligent defect detection methodology that leverages deep learning techniques to automate feature extraction and defect localization processes.Our proposed approach encompasses a suite of components:the high-level feature learning block(HLFLB),the multi-scale feature learning block(MSFLB),and a dynamic adaptive fusion block(DAFB),working in tandem to extract meticulously and synergistically aggregate defect-related characteristics across various scales and hierarchical levels.We have conducted validation of the proposed method using datasets derived from gearbox and bearing assessments.The empirical outcomes underscore the superior defect detection capability of our approach.It demonstrates consistently high performance across diverse datasets and possesses the accuracy required to categorize defects,taking into account their specific locations and the extent of damage,proving the method’s effectiveness and reliability in identifying defects in industrial components.