Improvement of High-Speed Detection Algorithm for Nonwoven Material Defects Based on Machine Vision

Defect detection is vital in the nonwoven material industry,ensuring surface quality before producing finished products.Recently,deep learning and computer vision advancements have revolutionized defect detection,making it a widely adopted approach in various industrial fields.This paper mainly studied the defect detection method for nonwoven materials based on the improved Nano Det-Plus model.Using the constructed samples of defects in nonwoven materials as the research objects,transfer learning experiments were conducted based on the Nano DetPlus object detection framework.Within this framework,the Backbone,path aggregation feature pyramid network(PAFPN)and Head network models were compared and trained through a process of freezing,with the ultimate aim of bolstering the model's feature extraction abilities and elevating detection accuracy.The half-precision quantization method was used to optimize the model after transfer learning experiments,reducing model weights and computational complexity to improve the detection speed.Performance comparisons were conducted between the improved model and the original Nano Det-Plus model,YOLO,SSD and other common industrial defect detection algorithms,validating that the improved methods based on transfer learning and semi-precision quantization enabled the model to meet the practical requirements of industrial production.

Hybrid multi-objective optimization of microstructural and mechanical properties of B_4C/A356 composites fabricated by FSP using TOPSIS and modified NSGA-Ⅱ

A356alloy was used as the base metal to produce boron carbide(B4C)/A356composites using friction stir processing(FSP).The microstructural and mechanical properties of B4C/A356composites were optimized using artificial neural network(ANN)and non-dominated sorting genetic algorithm-II(NSGA-II).Firstly,microstructural properties of the composites fabricated in different processing conditions were investigated.Results show that FSP parameters such as rotational speed,traverse speed and tool pin profile significantly affect the size of the primary silicon(Si)particles of the base metal,as well as the dispersion quality and volume fraction of reinforcing B4C particles in the composite layer.Higher rotational to traverse speeds ratio accompanied by threaded pin profile leads to better particles distribution,finer Si particles and smaller B4C agglomerations.Secondly,hardness and tensile tests were performed to study mechanical properties of the composites.FSP changes the fracture mechanism from brittle form in the as-received metal to very ductile form in the FSPed specimens.Then,a relation between the FSP parameters and microstructural and mechanical properties of the composites was established using ANN.A modified NSGA-II by incorporating diversity preserving mechanism called theεelimination algorithm was employed to obtain the Pareto-optimal set of FSP parameters.

Comparison Among Depths of Penetration of Different Targets Subjected to Rigid Projectile Impact

The ratios of depth of penetration (DOP) of different targets under the same penetration condition was investigated according to the dimensionless formula of DOP of different targets penetrated by a non-deformable projectile.Results show that various targets may be equivalent to each other.The applicable range of the equivalence and the feasibility of targets substitution were discussed by integrating the available test data.

Design of Sustainable Multifunctional Nanocoatings：A Goal-driven Multiscale Systems Approach

Polymer nanocomposites have a great potential to be a dominant coating material in a wide range of applications in the automotive,aerospace,ship-making,construction,and pharmaceutical industries.However,how to realize design sustainability of this type of nanostructured materials and how to ensure the true optimality of the product quality and process performance in coating manufacturing remain as a mountaintop area.The major challenges arise from the intrinsic multiscale nature of the material-process-product system and the need to manipulate the high levels of complexity and uncertainty in design and manufacturing processes.In this work,the challenging objectives of sustainable design and manufacturing are simultaneously accomplished by resorting to multiscale systems theory and engineering sustainability principles.The principal idea is to achieve exceptional system performance through concurrent characterization and optimization of materials,product and associated manufacturing processes covering a wide range of length and time scales.Multiscale modeling and simulation techniques ranging from microscopic molecular modeling to classical continuum modeling are seamlessly coupled.The integration of different methods and theories at individual scales allows the quantitative prediction of macroscopic system performance from the fundamental molecular behavior.Furthermore,mathematically rigorous and methodologically viable approaches are pursued to achieve sustainability-goal-oriented design of material-process-product systems.The introduced methodology can greatly facilitate experimentalists in novel material invention and new knowledge discovery.At the same time,it can provide scientific guidance and reveal various new opportunities and effective strategies for achieving sustainable manufacturing.The methodological attractiveness will be fully demonstrated by a detailed case study on the design of thermoset nanocomposite coatings.

Optimized algorithm in mine production planning, mined material destination, and ultimate pit limit

An integral connection exists among the mine production planning, the mined material destination, and the ultimate pit limit （UPL） in the mining engineering economy. This relation is reinforced by real information and the benefits it engenders in the mining economy. Hence, it is important to create optimizing algorithms to reduce the errors of economic calculations. In this work, a logical mathematical algorithm that considers the important designing parameters and the mining economy is proposed. This algorithm creates an optimizing repetitive process among different designing constituents and directs them into the maximum amount of the mine economical parameters. This process will produce the highest amount of ores and the highest degree of safety. The modeling produces a new relation between the concept of the cutoff grade, mine designing, and mine planning, and it provides the maximum benefit by calculating the destination of the ores. The proposed algorithm is evaluated in a real case study. The results show that the net present value of the mine production is increased by 3% compared to previous methods of production design and UPL.

Multi-objective steady-state optimization of two-chamber microbial fuel cells

A microbial fuel cell(MFC)is a novel promising technology for simultaneous renewable electricity generation and wastewater treatment.Three non-comparable objectives,i.e.power density,attainable current density and waste removal ratio,are often conflicting.A thorough understanding of the relationship among these three conflicting objectives can be greatly helpful to assist in optimal operation of MFC system.In this study,a multiobjective genetic algorithm is used to simultaneously maximizing power density,attainable current density and waste removal ratio based on a mathematical model for an acetate two-chamber MFC.Moreover,the level diagrams method is utilized to aid in graphical visualization of Pareto front and decision making.Three biobjective optimization problems and one three-objective optimization problem are thoroughly investigated.The obtained Pareto fronts illustrate the complex relationships among these three objectives,which is helpful for final decision support.Therefore,the integrated methodology of a multi-objective genetic algorithm and a graphical visualization technique provides a promising tool for the optimal operation of MFCs by simultaneously considering multiple conflicting objectives.

薄膜级碳酸钙填充母粒的试产

以"活化"了的6000目湿法重质碳酸钙粉料为主体,添加适量载体、少量分散剂等助剂;经混料、挤出造粒后制成碳酸钙填充母粒;该产品熔融、扩散性能好,在聚乙烯薄膜生产中应用前景广阔。

Optimum blending of iron ore from Choghart stockpiles by using goal programming

Iron and steel industry is an important sector of Iran's economy.Choghart iron ore mine is an important iron ore producer of Iran steel industry.Phosphorous contained in the iron ore concentrates of Choghart mine has a detrimental effect on the steel making process,whereby this causes cracks to form in the refractory lining of blast furnaces.In the past,about 1.43 Mt of low-grade and 4.53 Mt of high-phosphorous materials had been transported to low grade and high phosphorous stockpiles,respectively,for future beneficiation.As a result of the progressive depletion of high-grade ore and establishment of beneficiation plant in Choghart,exploitation of these two stockpiles in this mine became an important issue.In this work,a linear goal programming(GP) model was developed in order to determine the optimum iron ore blend in terms of quality from low grade and high phosphorous stockpiles of Choghart mine.The model was solved by the SOLVER V.9 program.Results show that feeding with acceptable quality(w(Fe)≥50% and w(P)≤1.2%,mass fraction) materials can be blended from stockpiles that satisfy the needs of the Choghart processing line.

Insecticidal Effect of Different Plant Extracts against Tribolium confusum （du val） （Coleoptera：Tenebrionidae）

Ethanolic extracts of five plant material from Eucalyptus gluaca, Melia azadrach, Mentha arvensis, Olea europaea leaves and periearp of Punica granatum were investigated for insecticidal activity against the confused flour beetle Tribolium confusum DuVal in the laboratory. Different concentrations 2.5%, 5%, 7.5%, 10% using filter paper test were implemented in the experiment. Mortality was assessed after 24, 48, 72 hrs of treatment and LDs0 were calculated at respective time intervals. Data analysis was made by using factorial Complete Randomized Design （CRD）. The results revealed that all of the tested materials with some variations had lethal effects against the pest as compared with the untreated check. The time 24 h showed higher insecticidal effect with the tested concentrations for the larvae and adult of Tribolium confusum. Strong toxicity effect was observed at concentration 5% of M.. arvensis for adult followed by E. gluaca, O. europaea, M.. azedrach and P. granatum. For larval stage the extract of O. europaea and E. gluaca with concentration 7.5%, 1%, respectively caused high mortality followed by M. arvensis, M. azedrach and P. granatum. The LDs0 values for adults and larvae were calculated to be 1.33 and 1.42 with M.. arvensis and O. europaea, respectively.

Evaluation of Fatigue Cracking Propagation： A Case Study of Airfield Infrastructure Systems

The challenges posed by fatigue propagation on engineering materials and infrastructural facilities have necessitate for proper appraisal. Fatigue involvements in engineering systems are complex requiring indepth analysis and optimization of the governing phenomena. The pervasive demand for suitable solutions to this circumstance has been the greatest problem faced by the systems engineers in the quest for delivering sustainable infrastructural development. Consequently, the removal of interdisciplinary boundaries and merge of design platforms pose a great challenge for an unprepared project engineering and technology community. It is imperative to understand the mechanisms promoting fatigue occurrences for a complete model conceptualisation and analysis improvement. In this paper, the duo evaluation--linear and effective crack length measurements are clearly shown to beacon the fatigue investigation for modem project engineering and technology. The paper has also examined the airfield pavement where this concept could be very useful. Such breakthrough would require accurate fatigue simulation and modelling platforms for inbuilt reliability and prudent resources management. Amongst the benefits of the fatigue analysis is the provision of an enabling environment for the sustainable management of engineering and technology projects.

College English Teaching Materials in China： A Critical Review

Quality English language teaching （ELT） materials play a key role in achieving teaching objectives. This paper first provides a brief historical overview of the development of college English teaching materials in China. Then by investigating studies on college English teaching materials for non-English major students from different perspectives, suggestions are proposed to provide guidance for effective ELT materials writing and evaluation： （1） Language corpora, providing empirical data concerning language usage, have a distinctive advantage in ELT materials writing and evaluation; （2） principles for ESP materials writing are developed; and （3） a systematic approach combining qualitative analysis with quantitative analysis to materials evaluation is suggested to ensure the validity and reliability of materials evaluation

Apparatus Prototype for Purposes of Teaching in Bio-digesters

A mathematical model is developed based on a simplified mechanism of anaerobic digestion. The main objective is to quantitatively analyze the digestion process to optimize operating conditions and maintenance of this equipment, which could be used to test different materials and be able to apply these results to the possible scaling to bio-digesters installed in the field. The experiments were carried out in a hybrid system bio-digester photovoltaic cells. The bio-digester is made of stainless steel with dimensions to treat an average of 10 kg of raw material and produce biogas from different organic materials. The reactor has been conditioned with temperature sensors, pressure and methane gas that allow monitoring the concentration of the gas and the conditions of operation during the time of digestion. The system has a photovoltaic array to provide the energy required to keep the temperature constant, The experiment was conducted using materials such as goat manure mixed with household waste, and various formulations of these materials were prepared. The experimental results were used to test the mathematical model.

The Research to Quality Supervision and Management of Power Enterprises

Intensive in-depth development of resources, centralized purchasing and gradually expand under the category of environment, this paper studies how to use information technology tools to construction quality supervision and management system that focuses on the quality of supervision and project management, quality control process management, quality monitoring statistics report management, platform management-related content in four areas. Through the construction quality supervision and management system, to better enhance the quality of electric power enterprise management level, to ensure that the material quality, quantity of time and supplies. strengthening quality supervision and management can not only effectively reduce material procurement costs, but also enhance the competitiveness of enterprises.

Synthesis/design optimization of SOFC-PEM hybrid system under uncertainty

Solid oxide fuel cell–proton exchange membrane(SOFC–PEM) hybrid system is being foreseen as a valuable alternative for power generation. As this hybrid system is a conceptual design, many uncertainties involving input values should be considered at the early stage of process optimization. We present in this paper a generalized framework of multi-objective optimization under uncertainty for the synthesis/design optimization of the SOFC–PEM hybrid system. The framework is based on geometric, economic and electrochemical models and focuses on evaluating the effect of uncertainty in operating parameters on three conflicting objectives: electricity efficiency, SOFC current density and capital cost of system. The multi-objective optimization provides solutions in the form of a Pareto surface, with a range of possible synthesis/design solutions and a logical procedure for searching the global optimum solution for decision maker. Comparing the stochastic and deterministic Pareto surfaces of different objectives, we conclude that the objectives are considerably influenced by uncertainties because the two trade-off surfaces are different.