Attention-relation network for mobile phone screen defect classification via a few samples

How to use a few defect samples to complete the defect classification is a key challenge in the production of mobile phone screens.An attention-relation network for the mobile phone screen defect classification is proposed in this paper.The architecture of the attention-relation network contains two modules:a feature extract module and a feature metric module.Different from other few-shot models,an attention mechanism is applied to metric learning in our model to measure the distance between features,so as to pay attention to the correlation between features and suppress unwanted information.Besides,we combine dilated convolution and skip connection to extract more feature information for follow-up processing.We validate attention-relation network on the mobile phone screen defect dataset.The experimental results show that the classification accuracy of the attentionrelation network is 0.9486 under the 5-way 1-shot training strategy and 0.9039 under the 5-way 5-shot setting.It achieves the excellent effect of classification for mobile phone screen defects and outperforms with dominant advantages.

Optimization of Fixture Number in Large Thin-Walled Parts Assembly Based on IPSO

There are lots of researches on fixture layout optimization for large thin-walled parts.Current researches focus on the positioning problem,i.e.,optimizing the positions of a constant number of fixtures.However,how to determine the number of fixtures is ignored.In most cases,the number of fixtures located on large thin-walled parts is determined based on engineering experience,which leads to huge fixture number and extra waste.Therefore,this paper constructs an optimization model to minimize the number of fixtures.The constraints are set in the optimization model to ensure that the part deformation is within the surface profile tolerance.In addition,the assembly gap between two parts is also controlled.To conduct the optimization,this paper develops an improved particle swarm optimization(IPSO)algorithm by integrating the shrinkage factor and adaptive inertia weight.In the algorithm,particles are encoded according to the fixture position.Each dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization efficiency.Finally,a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality requirements.This research proposes a method to optimize the number of fixtures,which can reduce the number of fixtures and achieve deformation control at the same time.

Development of Fixture Layout Optimization for Thin-Walled Parts:A Review

An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades.However,few papers systematically review these researches.By analyzing existing literature,this paper summarizes the process of fixture layout optimization and the methods applied.The process of optimization is made up of optimization objective setting,assembly variation/deformation modeling,and fixture layout optimization.This paper makes a review of the fixture layout for thin-walled parts according to these three steps.First,two different kinds of optimization objectives are introduced.Researchers usually consider in-plane variations or out-of-plane deformations when designing objectives.Then,modeling methods for assembly variation and deformation are divided into two categories:Mechanism-based and data-based methods.Several common methods are discussed respectively.After that,optimization algorithms are reviewed systematically.There are two kinds of optimization algorithms:Traditional nonlinear programming and heuristic algorithms.Finally,discussions on the current situation are provided.The research direction of fixture layout optimization in the future is discussed from three aspects:Objective setting,improving modeling accuracy and optimization algorithms.Also,a new research point for fixture layout optimization is discussed.This paper systematically reviews the research on fixture layout optimization for thin-walled parts,and provides a reference for future research in this field.

Meter-Scale Thin-Walled Structure with Lattice Infill for Fuel Tank Supporting Component of Satellite:Multiscale Design and Experimental Verification

Lightweight thin-walled structures with lattice infill are widely desired in satellite for their high stiffness-to-weight ratio and superior buckling strength resulting fromthe sandwich effect.Such structures can be fabricated bymetallic additive manufacturing technique,such as selective laser melting(SLM).However,the maximum dimensions of actual structures are usually in a sub-meter scale,which results in restrictions on their appliance in aerospace and other fields.In this work,a meter-scale thin-walled structure with lattice infill is designed for the fuel tank supporting component of the satellite by integrating a self-supporting lattice into the thickness optimization of the thin-wall.The designed structure is fabricated by SLM of AlSi10Mg and cold metal transfer welding technique.Quasi-static mechanical tests and vibration tests are both conducted to verify the mechanical strength of the designed large-scale lattice thin-walled structure.The experimental results indicate that themeter-scale thin-walled structure with lattice infill could meet the dimension and lightweight requirements of most spacecrafts.

Research on the Encapsulation Device for Lunar Samples

The encapsulation of lunar samples is a core research area in the third phase of the Chinese Lunar Exploration Program.The seal assembly,opening and closing mechanism(OCM),and locking mechanism are the core components of the encapsulation device of the lunar samples,and the requirements of a tight seal,lightweight,and low power make the design of these core components difficult.In this study,a combined sealing assembly,OCM,and locking mechanism were investigated for the device.The sealing architecture consists of rubber and an Ag-In alloy,and a theory was built to analyze the seal.Experiments of the electroplate Au coating on the knife-edge revealed that the hermetic seal can be significantly improved.The driving principle for coaxial double-helical pairs was investigated and used to design the OCM.Moreover,a locking mechanism was created using an electric initiating explosive device with orifice damping.By optimizing the design,the output parameters were adjusted to meet the requirements of the lunar explorer.The experimental results showed that the helium leak rate of the test pieces were not more than 5×10^(-11) Pa·m^(3)·s^(-1),the minimum power of the OCM was 0.3 W,and the total weight of the principle prototype was 2.9 kg.The explosive driven locking mechanism has low impact.This investigation solved the difficulties in achieving tight seal,light weight,and low power for the lunar explorer,and the results can also be used to explore other extraterrestrial objects in the future.

Effectiveness of Histopathological Examination of Ultrasound-guided Puncture Biopsy Samples for Diagnosis of Extrapulmonary Tuberculosis

Objective To evaluate the diagnostic value of histopathological examination of ultrasound-guided puncture biopsy samples in extrapulmonary tuberculosis(EPTB).Methods This study was conducted at the Shanghai Public Health Clinical Center.A total of 115patients underwent ultrasound-guided puncture biopsy,followed by MGIT 960 culture(culture),smear,Gene Xpert MTB/RIF(Xpert),and histopathological examination.These assays were performed to evaluate their effectiveness in diagnosing EPTB in comparison to two different diagnostic criteria:liquid culture and composite reference standard(CRS).Results When CRS was used as the reference standard,the sensitivity and specificity of culture,smear,Xpert,and histopathological examination were(44.83%,89.29%),(51.72%,89.29%),(70.11%,96.43%),and(85.06%,82.14%),respectively.Based on liquid culture tests,the sensitivity and specificity of smear,Xpert,and pathological examination were(66.67%,72.60%),(83.33%,63.01%),and(92.86%,45.21%),respectively.Histopathological examination showed the highest sensitivity but lowest specificity.Further,we found that the combination of Xpert and histopathological examination showed a sensitivity of 90.80%and a specificity of 89.29%.Conclusion Ultrasound-guided puncture sampling is safe and effective for the diagnosis of EPTB.Compared with culture,smear,and Xpert,histopathological examination showed higher sensitivity but lower specificity.The combination of histopathology with Xpert showed the best performance characteristics.

An electromagnetic semi-active dynamic vibration absorber for thin-walled workpiece vibration suppression in mirror milling

As critical components of aircraft skins and rocket fuel storage tank shells,large thin-walled workpieces are susceptible to vibration and deformation during machining due to their weak local stiffness.To address these challenges,we propose a novel tunable electromagnetic semi-active dynamic vibration absorber(ESADVA),which integrates with a magnetic suction follower to form a followed ESADVA(follow-ESADVA)for mirror milling.This system combines a tunable magnet oscillator with a follower,enabling real-time vibration absorption and condition feedback throughout the milling process.Additionally,the device supports self-sensing and frequency adjustment by providing feedback to a linear actuator,which alters the distance between magnets.This resolves the traditional issue of being unable to directly monitor vibration at the machining point due to space constraints and tool interference.The frequency shift characteristics and vibration absorption performance are comprehensively investigated.Theoretical and experimental results demonstrate that the prototyped follow-ESADVA achieves frequency synchronization with the milling tool,resulting in a vibration suppression rate of approximately 47.57%.Moreover,the roughness of the machined surface decreases by18.95%,significantly enhancing the surface quality.The results of this work pave the way for higher-quality machined surfaces and a more stable mirror milling process.

Numerical Analysis of Cold-Formed Thin-Walled Steel Short Columns with Pitting Corrosion during Bridge Construction

Pitting corrosion is harmful during bridge construction,which will lead to uneven roughness of steel surfaces and reduce the thickness of steel.Hence,the effect of pitting corrosion on the mechanical properties of cold-formed thin-walled steel stub columns is studied,and the empirical formulas are established through regression fitting to predict the ultimate load of web and flange under pitting corrosion.In detail,the failure modes and load-displacement curves of specimens with different locations,area ratios,and depths are obtained through a large number of non-linear finite element analysis.As for the specimens with pitting corrosion on the web,all the specimens are subject to local buckling failure,and the failure mode will not change with pitting corrosion,but the failure location will change with pitting corrosion location;the size,location,and area ratio of pitting corrosion have little influence on the ultimate load of cold-formed thin-walled steel short columns,but the loss rate of pitting corrosion section area has a greater impact on the ultimate bearing capacity.As for the specimen with flange pitting corrosion,the location and area ratio of pitting corrosion have less influence on the ultimate load of cold-formed thin-walled steel short columns,and the section area loss rate has greater influence on the ultimate bearing capacity;the impact of web pitting corrosion on the ultimate load is greater than that of flange pitting corrosion under the same condition of pitting corrosion section area.The prediction formulas of limit load which are suitable for pitting corrosion of web and flange are established,which can provide a reference for performance evaluation of corroded cold-formed thin-walled steel.

Exploring device physics of perovskite solar cell via machine learning with limited samples

Perovskite solar cells(PsCs)have developed tremendously over the past decade.However,the key factors influencing the power conversion efficiency(PCE)of PSCs remain incompletely understood,due to the complexity and coupling of these structural and compositional parameters.In this research,we demon-strate an effective approach to optimize PSCs performance via machine learning(ML).To address chal-lenges posed by limited samples,we propose a feature mask(FM)method,which augments training samples through feature transformation rather than synthetic data.Using this approach,squeeze-and-excitation residual network(SEResNet)model achieves an accuracy with a root-mean-square-error(RMSE)of 0.833%and a Pearson's correlation coefficient(r)of 0.980.Furthermore,we employ the permu-tation importance(PI)algorithm to investigate key features for PCE.Subsequently,we predict PCE through high-throughput screenings,in which we study the relationship between PCE and chemical com-positions.After that,we conduct experiments to validate the consistency between predicted results by ML and experimental results.In this work,ML demonstrates the capability to predict device performance,extract key parameters from complex systems,and accelerate the transition from laboratory findings to commercialapplications.

A Fault Detection Method for Electric Vehicle Battery System Based on Bayesian Optimization SVDD Considering a Few Faulty Samples

Accurate and reliable fault detection is essential for the safe operation of electric vehicles.Support vector data description(SVDD)has been widely used in the field of fault detection.However,constructing the hypersphere boundary only describes the distribution of unlabeled samples,while the distribution of faulty samples cannot be effectively described and easilymisses detecting faulty data due to the imbalance of sample distribution.Meanwhile,selecting parameters is critical to the detection performance,and empirical parameterization is generally timeconsuming and laborious and may not result in finding the optimal parameters.Therefore,this paper proposes a semi-supervised data-driven method based on which the SVDD algorithm is improved and achieves excellent fault detection performance.By incorporating faulty samples into the underlying SVDD model,training deals better with the problem of missing detection of faulty samples caused by the imbalance in the distribution of abnormal samples,and the hypersphere boundary ismodified to classify the samplesmore accurately.The Bayesian Optimization NSVDD(BO-NSVDD)model was constructed to quickly and accurately optimize hyperparameter combinations.In the experiments,electric vehicle operation data with four common fault types are used to evaluate the performance with other five models,and the results show that the BO-NSVDD model presents superior detection performance for each type of fault data,especially in the imperceptible early and minor faults,which has seen very obvious advantages.Finally,the strong robustness of the proposed method is verified by adding different intensities of noise in the dataset.

Mechanical behavior of 2G NPR bolt anchored rock samples under static disturbance loading

The deep mining of coal resources is accompanied by severe environmental challenges and various potential engineering hazards.The implementation of NPR(negative Poisson's ratio)bolts are capable of controlling large deformations in the surrounding rock effectively.This paper focuses on studying the mechanical properties of the NPR bolt under static disturbance load.The deep nonlinear mechanical experimental system was used to study the mechanical behavior of rock samples with different anchored types(unanchored/PR anchored/2G NPR anchored)under static disturbance load.The whole process of rock samples was taken by high-speed camera to obtain the real-time failure characteristics under static disturbance load.At the same time,the acoustic emission signal was collected to obtain the key characteristic parameters of acoustic emission such as acoustic emission count,energy,and frequency.The deformation at the failure of the samples was calculated and analyzed by digital speckle software.The findings indicate that the failure mode of rock is influenced by different types of anchoring.The peak failure strength of 2G NPR bolt anchored rock samples exhibits an increase of 6.5%when compared to the unanchored rock samples.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 62.16%and 62.90%,respectively.The maximum deformation of bearing capacity exhibits an increase of 59.27%,while the failure time demonstrates a delay of 42.86%.The peak failure strength of the 2G NPR bolt anchored ones under static disturbance load exhibits an increase of 5.94%when compared to the rock anchored by PR(Poisson's ratio)bolt.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 47.16%and 43.86%,respectively.The maximum deformation of the bearing capacity exhibits an increase of 50.43%,and the failure time demonstrates a delay of 32%.After anchoring by 2G NPR bolt,anchoring support effectively reduces the risk of damage caused by static disturbance load.These results demonstrate that the support effect of 2G NPR bolt materials surpasses that of PR bolt.

On-machine inspection and compensation for thin-walled parts with sculptured surface considering cutting vibration and probe posture

On-machine inspection has a significant impact on improving high-precision and efficient machining of sculptured surfaces. Due to the lack of machining information and the inability to adapt the parameters to the dynamic cutting conditions, theoretical modeling of profile inspection usually leads to insufficient adaptation, which causes inaccuracy problems. To address the above issues, a novel coupled model for profile inspection is proposed by combining the theoretical model and the data-driven model. The key process is to first realize local feature extraction based on the acquired vibration signals. The hybrid sampling model, which fuses geometric feature terms and vibration feature terms, is modeled by the lever principle. Then, the weight of each feature term is adaptively assigned by a multi-objective multi-verse optimizer.Finally, an inspection error compensation model based on the attention mechanism considering different probe postures is proposed to reduce the impact of pre-travel and radius errors on inspection accuracy. The anisotropy of the probe system error and its influence mechanism on the inspection accuracy are analyzed quantitatively and qualitatively. Compared with the previous models, the proposed hybrid profile inspection model can significantly improve the accuracy and efficiency of on-machine sampling. The proposed compensation model is able to correct the inspection errors with better accuracy. Simulations and experiments demonstrate the feasibility and validity of the proposed methods. The proposed model and corresponding new findings contribute to high-precision and efficient on-machine inspection, and help to understand the coupling mechanism of inspection errors.

Sensitivity of springback and section deformation to process parameters in rotary draw bending of thin-walled rectangular H96 brass tube

In order to study the effects of the process parameters on springback and section deformation, a sensitivity analysis model was established based on the combination use of the multi-parameter sensitivity analysis method and the springback/section deformation prediction finite element model, and by using this model the sensitivities of the springback and the section deformation to process parameters were analyzed and compared. The results show that the most sensitive process conditions for springback angle are the boost speed and the pressure of pressure die, and the most sensitive process condition for section deformation is the number of cores. When the clamp force, the boost speed and the pressure of pressure die are utilized to control section deformation, the effect of these process parameters on springback should be considered. When the process parameters are mainly used to control springback, the effect of these process parameters on the section deformation should be always considered.

VIBRATION IN HIGH-SPEED MILLING OF THIN-WALLED COMPONENTS

To investigate the vibration principle in machining thin-walled components, a dynamic model for end milling of flexible structures is built based on considering the variations in the dynamic chip thickness and the differences between up-milling and down-milling. Two milling experiments verify the model. Experimental results show that the model can predict the milling force and displacements simultaneously in the dynamic milling process.

Selection of Test Samples for Monitoring Veterinary Drug Residue in Bred Animals

[Objective] This study aimed to compare the residue situation of cimaterol,a kind of forbidden veterinary drug in hair, urine and flesh of pig, so as to provide theoretical basis for monitoring veterinary drug residue in bred animals. [Method]Total three different concentrations of cimaterol were administered to pigs, and the residue amounts of cimaterol in pig hair, urine and flesh were monitored at different raising stage. [Result] During the administration period, the residue amount of cimaterol was highest in urine, so urine is the suitable sample for rapid detection of cimaterol in manufacturing enterprises. Cimaterol could be accumulated in pig hair,where cimaterol was metabolized slowly. Thus, pig hair can be used as the test sample for tracing illegal use of veterinary drugs and for vivo detection. Flesh can be used as test sample for direct judgment whether cimaterol residue exceeds the relevant standard. [Conclusion] This study will provide certain theoretical basis for drug monitor in animal husbandry.

Warm bending mechanism of extrados and intrados of large diameter thin-walled CP-Ti tubes

In order to develop the warming bending technology of the large diameter thin-walled（LDTW） commercial pure titanium alloy CP-Ti tubes, the warm bending mechanism of the extrados and intrados of LDTW CP-Ti tubes was researched. By EBSD analysis and Vickers hardness test, the changes of microstructure and strength of the tubes at different bending temperatures of 293, 423 and 573 K, were analyzed. The results show： 1） The extrados of the bent tube deforms mainly by slip, along with few twinning, and the preferred orientation is similar to that of the initial tube; the intrados of the bent tube experiences compression deformation mainly by {1 012} tensile twinning, and the twinning makes the preferred orientation of wall materials change sharply. 2） The Vickers hardness values of both the extrados and intrados of the samples after bending increase greatly; the Vickers hardness values of the intrados are much higher than those of the extrados, and Vickers hardness values of the RD-TD planes are always higher than those of the RD-LD planes, which are related to the different deformation mechanisms.

Fundamentals and Processes of Fluid Pressure Forming Technology for Complex Thin-Walled Components

A new generation of fluid pressure forming technology has been developed for the three typical structures of tubes,sheets,and shells,and hard-to-deform material components that are urgently needed for aerospace,aircraft,automobile,and high-speed train industries.in this paper,an over all review is introduced on the state of the art in fundamentals and processes for lower-pressure hydroforming of tubular components,double-sided pressure hydroforming of sheet components,die-less hydroforming of ellipsoidai shells,and dual hardening hot medium forming af hard-to-deform materiais Particular attention is paid to deformation behavior,stress state adjustment,defect prevention,and typical applications.In addition,future development directions of fluid pressure forming technology are discussed,including hyper lower-loading forming for ultra-large non-uniform components,precision for ming for intermetallic compound and high-entropy alloy components,intelligent process and equipment,and precise finite element simulation of inhomogeneous and strong anisotropic thin shells.

Comparison of results analyzed by Chinese and European laboratories for FOREGS geochemical baselines mapping samples

Geochemical subsoil data obtained from China and European laboratories have been compared in this study. 787 C horizon subsoil samples from FOREGS （Forum of European Geological Surveys） geochemical baselines mapping project were sent to China＇s IGGE （Institute of Geophysical and Geochemical Exploration） laboratory and composited to 190 samples according to the 160 kin x 160 km GNT （Global Terrestrial Network） cells. In addition to the FOREGS elemental analysis package, Au, Pt, Pd, B, Ge, Br, CI, Se, N, Li and F were also analyzed by using the IGGE＇s 76 element analytical scheme. Geochemical data statistics, scatter plotting, and geochemical map compilation tech- niques have been employed to investigate differences between FOREGS and IGGE analytical results. The results of two datasets, the IGGE＇s analysis data for composited samples, and the FOREGS average data of samples in each GNT cell, agree extremely well lor about 23 elements, viz： SiO2, St, Al2O3, Zr, Ba, Fe2O3, Ti, Rb, Mn, Gd, CaO, Ga, MgO, P, Pb, Na2O, Y, Th, As, U Sc, Cr, and Co. There are slight differences between-laboratory biases shown as proportional errors between the datasets for Ni, K2O, Tb, Tl, Cu, S, Sin, La, Ce, Pr, Nd, Eu, Ho, Er, Tin, Yb, Lu, Ta, Nb, HE and Dy. For Cd, Cs, Be, Sb, In, Mo, I, Sn, and Te, the correlation of the two datasets and the similarity of the geochemical maps are fairly good, but obvious biases exist between the two datasets at values near detection limits.

Application of Modified Silica Coated Magnetite Nanoparticles for Removal of Iodine from Water Samples

The adsorption of iodine onto silica coated magnetite nanoparticles(im-SCMNPs) that modified with imidazole was investigated for removal of high concentrations of iodine from wastewater. Modified silica magnetite nanoparticles showed high efficiency in removing iodine from wastewater samples. The optimum pH for iodine removal was 7.0-8.0. The adsorption capacity was evaluated using both the Langmuir and Freundlich adsorption isotherm models. The size of the produced magnetite nanoparticles was determined by X-ray diffraction analysis and scanning electron microscopy. Synthesized magnetite nanoparticles showed the high adsorption capacity and would be a good method to increase adsorption efficiency for the removal of iodine in a wastewater treatment process. The Langmuir adsorption capacity(qmax) was found to be 140.84 mg/g of the adsorbent.

Novel method for the determination of five carbamate pesticides in water samples by dispersive liquid-liquid microextraction combined with high performance liquid chromatography

A novel method for the determination of five carbamate pesticides （metolcarb, carbofuran, carbaryl, isoprocard and diethofencard） in water samples was developed by dispersive liquid-liquid microextraction （DLLME） coupled with high performance liquid chromatography-diode array detector （HPLC-DAD）. Some experimental parameters that influence the extraction efficiency were studied and optimized to obtain the best extraction results. Under the optimum conditions for the method, the calibration curve was linear in the concentration range from 5 to 1000 ng mL^-1 for all the five carbamate pesticides, with the correlation coefficients （r^2） varying from 0.9984 to 0.9994. Good enrichment factors were achieved ranging from 80 to 177- fold, depending on the compound. The limits of detection （LODs） （S/N = 3） were ranged from 0.1 to 0.5 ng mL^-1. The method has been successfully applied to the analysis of the pesticide residues in environmental water samples.