The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can caus...The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.展开更多
Background Plant tissue culture has emerged as a tool for improving cotton propagation and genetics,but recalcitrance nature of cotton makes it difficult to develop in vitro regeneration.Cotton’s recalcitrance is inf...Background Plant tissue culture has emerged as a tool for improving cotton propagation and genetics,but recalcitrance nature of cotton makes it difficult to develop in vitro regeneration.Cotton’s recalcitrance is influenced by genotype,explant type,and environmental conditions.To overcome these issues,this study uses different machine learning-based predictive models by employing multiple input factors.Cotyledonary node explants of two commercial cotton cultivars(STN-468 and GSN-12)were isolated from 7–8 days old seedlings,preconditioned with 5,10,and 20 mg·L^(-1) kinetin(KIN)for 10 days.Thereafter,explants were postconditioned on full Murashige and Skoog(MS),1/2MS,1/4MS,and full MS+0.05 mg·L^(-1) KIN,cultured in growth room enlightened with red and blue light-emitting diodes(LED)combination.Statistical analysis(analysis of variance,regression analysis)was employed to assess the impact of different treatments on shoot regeneration,with artificial intelligence(AI)models used for confirming the findings.Results GSN-12 exhibited superior shoot regeneration potential compared with STN-468,with an average of 4.99 shoots per explant versus 3.97.Optimal results were achieved with 5 mg·L^(-1) KIN preconditioning,1/4MS postconditioning,and 80%red LED,with maximum of 7.75 shoot count for GSN-12 under these conditions;while STN-468 reached 6.00 shoots under the conditions of 10 mg·L^(-1) KIN preconditioning,MS with 0.05 mg·L^(-1) KIN(postconditioning)and 75.0%red LED.Rooting was successfully achieved with naphthalene acetic acid and activated charcoal.Additionally,three different powerful AI-based models,namely,extreme gradient boost(XGBoost),random forest(RF),and the artificial neural network-based multilayer perceptron(MLP)regression models validated the findings.Conclusion GSN-12 outperformed STN-468 with optimal results from 5 mg·L^(-1) KIN+1/4MS+80%red LED.Application of machine learning-based prediction models to optimize cotton tissue culture protocols for shoot regeneration is helpful to improve cotton regeneration efficiency.展开更多
Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,su...Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.展开更多
Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planti...Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.展开更多
A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,wh...A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.展开更多
介绍了STEP-NC的概念、数据模型及其结构特点,然后通过对比MLP(Machining Line Planner)和STEP-NC数控程序对特征和操作的不同定义方法,分析了在MLP中特征及加工工艺与STEP-NC的对应关系,探讨了在MLP中实现输出STEP-NC格式的零件加工程...介绍了STEP-NC的概念、数据模型及其结构特点,然后通过对比MLP(Machining Line Planner)和STEP-NC数控程序对特征和操作的不同定义方法,分析了在MLP中特征及加工工艺与STEP-NC的对应关系,探讨了在MLP中实现输出STEP-NC格式的零件加工程序的方法。展开更多
Electrochemical machining (ECM) is one of the best al ternatives for producing complex shapes in advanced materials used in aircraft a nd aerospace industries. However, the reduction of the stray material removal co n...Electrochemical machining (ECM) is one of the best al ternatives for producing complex shapes in advanced materials used in aircraft a nd aerospace industries. However, the reduction of the stray material removal co ntinues to be major challenges for industries in addressing accuracy improvement . This study presents a method of improving machining accuracy in ECM by using a dual pole tool with a metallic bush outside the insulated coating of a cathode tool. The bush is connected with anode and so the electric field at the side gap area is substantially weakened. The modeling and simulation indicate that the p ositive bush brings down the current density at the side gap area of the machine d hole and hence reduces the stray material removal there. It has been experimen tally observed that the machining accuracy and the process stability are signifi cantly improved.展开更多
The Al 2O 3 particles reinforced aluminum matrix composite (Al 2O 3p/Al) are more and more widely used for their excellent physical and chemical properties. However, their poor machinability leads to severe tool wear ...The Al 2O 3 particles reinforced aluminum matrix composite (Al 2O 3p/Al) are more and more widely used for their excellent physical and chemical properties. However, their poor machinability leads to severe tool wear and bad machined surface. In this paper laser assisted machining is adopted in machining Al 2O 3p/Al composite and good result was obtained. The result of experiment shows in machining Al 2O 3p/Al composites the cutting force is reduced in 30%～50%, the tool wear is reduced in 20%～30% and machined surface quality is improved in laser assisted machining as compared with conventional cutting. The physical model of the cutting process is set up and explains the reason why the cutting forced are reduced. The state of the particles is the main influence of the change. When the material of cutting zone is heating by laser, the aluminum matrix becomes softer and easier in plastic deformation, which leads to the reduction of the pushing force from the tool to the machined surface. The soften aluminum matrix is more easy to be squeezed out from the machined surface, and it leads the concentration of the Al 2O 3 particles in the surface layer of machined surface. The softening effect of laser heating on aluminum matrix reduces the pushing forces of the Al 2O 3 particles on the clearance face of cutting tool, which is just the reason for the severe cutting tool wear in conventional machining of Al 2O 3p/Al composite. Because the Al 2O 3 particles were pushed in during the cutting process, the particles increased in the surface layer. Because of the difference in thermal conductivity and thermal expansion between the Al-matrix and Al 2O 3 particle, residual stress is changed in the matrix after machining due to the extrusion of the tool, deformation of the matrix and displacement of the Al 2O 3 particle in the matrix. Temperature gradient comes into the cutting zone and the work-piece surface layer, it will lead to the increase of thermal stress and misfit dislocation in the matrix. The residual stress is compressive in the laser assisted hot cutting surface, the compressive stress is nearly triple times than that in the conventional cutting surface. Some analysis on the mechanism of laser heat assisted machining of Al 2O 3p/Al composite is given in the paper too.展开更多
For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chippin...For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chipping, which ordinarily occupies quite a lot of time. Therefore, besides the control of the machining parameters, the control of the optimum discharge gap and the conversion of different machining states is also needed. In this paper, the adaptive fuzzy control system of servomechanism for EDM combined with ultrasonic vibration is studied, the servomechanism of which is composed of the stepping motor comprising variable steps and the inductive synchronizer. The fuzzy control technology is used to realize the control of the frequency and the step of the servomechanism. The adaptive fuzzy controller has three inputs and two outputs, which can well meet the actual control requirements. The constitution of the fuzzy control regulation for the step frequency is the key to the design of the whole fuzzy control system of the servomechanism. The step frequency is mainly determined by the position error and the change rate of the position error. When the value of the position error is high or medium, the controlled parameters are selected to eliminate the error; when the position error is lower, the controlled parameters are selected to avoid the over-orientation and thus keep the stability of the system. According to these, a fuzzy control table is established in advanced, which is used to express the relations between the fuzzy input parameters and the fuzzy output parameters. The input parameters and the output parameters are all expressed by the level-values in fuzzy field. Therefore, the output parameters used for control can be obtained for the fuzzy control table according to the detected actual input parameters, by which the EDM combined with ultrasonic vibration is improved and the machining efficiency is increased. In addition, a stimulation program is designed by means of Microsoft Visual Basic展开更多
A new concept of banana vibrating screen which has the same effect as traditional banana vibrating screen in a new way was put forward.The dynamic model of vibrating screen was established and its working principle wa...A new concept of banana vibrating screen which has the same effect as traditional banana vibrating screen in a new way was put forward.The dynamic model of vibrating screen was established and its working principle was analyzed when the action line of the exciting force did not act through the centroid of screen box.Moreover,the dynamic differential equations of centroid and screen surface were obtained.The motions of centroid and screen surface were simulated with actual parameters of the design example in Matlab/Simulink.The results show that not only the amplitude has a significant decrease from 9.38 to 4.10 mm,but also the throwing index and vibrating direction angle have a significant decrease from 10.49 to 4.59,and from 58.10° to 33.29°,respectively,along the screen surface,which indicates that motion characteristics of vibrating screen are consistent with those of traditional banana vibrating screen only by means of a single angle of screen surface.What's more,such banana vibrating screen of variable linear trajectory with greater processing capacity could be obtained by adjusting the relative position of force center and the centroid of screen box properly.展开更多
The influences of the mask wall angle on the current density distribution,shape of the evolving cavity and machining accuracy were investigated in electrochemical machining(ECM) by mask.A mathematical model was develo...The influences of the mask wall angle on the current density distribution,shape of the evolving cavity and machining accuracy were investigated in electrochemical machining(ECM) by mask.A mathematical model was developed to predict the shape evolution during the ECM by mask.The current density distribution is sensitive to mask wall angle.The evolution of cavity is determined by the current density distribution of evolving workpiece surface.The maximum depth is away from the center of holes machined,which leads to the island appearing at the center of cavity for mask wall angles greater than or equal to 90°(β≥90°).The experimental system was established and the simulation results were experimentally verified.The results indicate that the simulation results of cavity shape are consistent with the actual ones.The experiments also show that the repetition accuracy of matrix-hole for β≥90° is higher than that for β<90°.A hole taper is diminished,and the machining accuracy is improved with the mask wall angle increasing.展开更多
In heavy duty machine tools, hydrostatic turntable is often used as a means for providing rotational motion and supporting workpiece, so the accuracy of turntable is crucial for part machining. In order to analyze the...In heavy duty machine tools, hydrostatic turntable is often used as a means for providing rotational motion and supporting workpiece, so the accuracy of turntable is crucial for part machining. In order to analyze the influence of load-indcued errors on machining accuracy, an identification model of load-induced errors based on the deformation caused by applied load of hydrostatic turntable of computerized numerical control(CNC) gantry milling heavy machine is proposed. Based on multi-body system theory and screw theory, the space machining accuracy model of heavy duty machine tool is established with consideration of identified load-induced errors. And then, the influence of load-induced errors on space machining accuracy and the roundness error of a milled hole is analyzed. The analysis results show that load-induced errors have a big influence on the roundness error of machined hole, especially when the center of the milled hole is far from that of hydrostatic turntable.展开更多
In this study, a newly developed titanium superalloy, i.e., the Ti-5553 alloy has used for hot machining. This material replaced Ti-grade-5 alloy in the application of aerospace, automobile, and biomedical sector. How...In this study, a newly developed titanium superalloy, i.e., the Ti-5553 alloy has used for hot machining. This material replaced Ti-grade-5 alloy in the application of aerospace, automobile, and biomedical sector. However, similar to Ti-grade-5 alloy, the Ti-5553 alloy has a low thermal conductivity which makes it difficult-to-cut material categories hence, high tool wear, cutting force and bad surface finish. Hot machining of Ti-5553 has been studied at different machining condition (room and hot) using Deform-2D finite element analysis. The result from the simulation test was compared with the experimental value and reduction of cutting and thrust forces was observed. The experiment was carried out with the same input parameters as simulation, and good coherence between them observed. Additionally, cutting zone temperature, effective stress, etc. for both room and elevated the temperature are also discussed.展开更多
Based on the distribution characteristic of magnetic field along the polish wheel,the four-axis linkage technique is advanced to replace a standard five-axis one to figure low-gradient optical surfaces with a raster t...Based on the distribution characteristic of magnetic field along the polish wheel,the four-axis linkage technique is advanced to replace a standard five-axis one to figure low-gradient optical surfaces with a raster tool-path in magnetorheological finishing(MRF).After introducing the fundaments of such simplification,the figuring reachability of a four-axis system for the low-gradient optics was theoretically analyzed.Further validation including magnetic field intensity and influence function characteristic was performed to establish its application.To demonstrate the correctness,feasibility and applicability of such technique,a K4 spherical part was figured by two iterations of MRF with surface form error improved to 0.219λPV and 0.027λRMS.Meanwhile,the surface roughness was also improved a lot in MRF process.These theoretical analyses and experimental results both indicate that high form accuracy and excellent surface quality can be obtained by using the four-axis linkage technique in the process of figuring low-gradient optical elements,and the four-axis linkage system undoubtedly is much more easy to control and much more economical.展开更多
Powder Mixed Electric Discharge Machining (PMEDM) has different mechanism from conventional EDM, which can improve the surface roughness and surface quality distinctly and to obtain nearly mirror surface effects. It i...Powder Mixed Electric Discharge Machining (PMEDM) has different mechanism from conventional EDM, which can improve the surface roughness and surface quality distinctly and to obtain nearly mirror surface effects. It is a useful finish machining method and is researched and applied by many countries. However there are little research on rough machining of PMEDM. Experiments show that PMEDM machining makes discharge breakdown easier, enlarges the discharge gaps and widens discharge passage, and at last forms even distributed and "large and shadow" shaped etched cavities. Because of much loss of discharge energy in the discharge gaps and reduction of ejecting force on the melted material, the machining efficiency gets lower and the surface roughness gets small in PMEDM machining in comparison with conventional EDM machining. This paper performs experimental research on the machining efficiency and surface roughness of PMEDM in rough machining. The machining efficiency of PMEDM can be highly increased by selecting proper discharge parameters (increasing peak current, reducing pulse width) with approximate surface roughness in comparison with conventional EDM machining. Although PMEDM can improve machining efficiency in rough efficiency, but a series of problems like electrode wear, efficiently separation of machined scraps from the powder mixed working fluid, should be solved before PMEDM machining is really applied in rough machining. Experiments result shows that powder mixed EDM machining can obviously improve machining efficiency at the same surface roughness by selecting proper discharging parameters, and can provide reference accordingly for the application of PMEDM machining technology in rough machining.展开更多
This paper describes a new method of surface modification by Electrical Discharge Machining (EDM). By using ordinary EDM machine tool and kerosene fluid, a hard ceramic layer can be created on the workpiece surface wi...This paper describes a new method of surface modification by Electrical Discharge Machining (EDM). By using ordinary EDM machine tool and kerosene fluid, a hard ceramic layer can be created on the workpiece surface with Ti or other compressed powder electrode in a certain condition. This new revolutionary method is called Electrical Discharge Coating (EDC). The process of EDC begins with electrode wear during EDM,then a kind of hard carbide is created through the thermal and chemical reaction between the worn electrode material and the carbon particle decomposed from kerosene fluid under high temperature. The carbide is piled up on a workpiece quickly and becomes a hard layer of ceramic about 20 μm in several minutes. This paper studies the principle and process of EDC systemically by using Ti powder green compact electrode. In order to obtain a layer of compact ceramic film, it is very important to select proper electric pulse parameters, such as pulse width, pulse interval, peak current. Meantime, the electrode materials and its forming mode will effect the machining surface quality greatly. This paper presents a series of experiment results to study the EDC process by adopt different technology parameters. Experiments and analyses show that a compact TiC ceramic layer can be created on the surface of metal workpiece. The hardness of ceramic layer is more 3 times higher than the base body, and the hardness changes gradiently from surface to base body. The method will have a great future because many materials can be easily added to the electrode and then be coated on the workpiece surface. Gearing the parameters ceramic can be created with different thickness. The switch between deposition and removal process is carried out easily by changing the polarity, thus the gear to the thickness and shape of the composite ceramic layer is carried out easily. This kind of composite ceramic layer will be used to deal with the surface of the cutting tools or molds possibly, in order to lengthen their life. It also can be found wide application in the fields of surface repairing and strengthening of the ship or aircraft.展开更多
Ultrasonic machining (USM) is considered as an effective method for machining hard and brittle materials such as glass, engineering ceramics, semiconductors, diamonds, metal composites and so on. However, the low mate...Ultrasonic machining (USM) is considered as an effective method for machining hard and brittle materials such as glass, engineering ceramics, semiconductors, diamonds, metal composites and so on. However, the low material removal rate due to using abrasive slurry limits further application of USM. Rotary ultrasonic machining (rotary USM) superimposes rotational movement on the tool head that vibrates at ultrasonic frequency (20 kHz) simultaneously. The tool is made of mild steel coated or bonded with diamond abrasive. Therefore, abrasive slurry is abandoned and coolant is used to carry debris out of working area. Compared with USM, rotary USM can obtain much higher material removal rate, deep holes, and fine precision, which leads to its further application. Combined with CNC technology, rotary USM can be used to conduct contour machining of hard and brittle materials. In this paper, the movement of abrasive particles in tool tip of rotary ultrasonic machining is analyzed. The impacting and grinding of abrasive in tool tip to machined surface are considered as main factors to material removal rate. The process of crack forming and growing in one loading and unloading cycle can be described as following stages: a) When abrasive particle acts the pressure on work-piece, the macro cracks in periphery of contact area are exerted increasing tensile stress. b) As the tensile stress increase to the critical of material tension, the one of cracks in periphery of contact area begins to propagate around contact area and develop beneath the surface to certain depth. c) Indentation area varies with increasing of load, the circle crack around contact area steadily or dynamical propagates towards inside of work-piece. d) As tensile stress in crack increases to critical of crack steady failure, circle crack suddenly becomes conic crack. e) Further increase load, the crack continues to grow while contact area is surrounded by conic cracks. f) During unloading, conic crack begins to close, some of cracks continue their extension towards the surface and forms a circle groove. The mathematical model for material removal rate shows that the factors affecting on material removal rate are static load, grid and concentration of abrasive, mechanical properties of machined materials, rotational speed of tool and feed speed of work-piece.展开更多
As the cutting speed goes higher, the mechanism of chip deformation will be changed significantly, i.e., continuous chip in low cutting speed will shift to serrated chip with shear localization. For the shear localize...As the cutting speed goes higher, the mechanism of chip deformation will be changed significantly, i.e., continuous chip in low cutting speed will shift to serrated chip with shear localization. For the shear localized chip, the parameters used to assess the chip deformation for continuous chip, such as shorten coefficient ξ, shear angle φ and shear strain ε, can not describe the chip deformation correctly or comprehensively. This paper deals with the assessment of chip deformation of shear localization. There are two deformation regions in shear localized chip, one is the chip segment body with relative smaller plastic deformation, another one is the boundary between segments with shear localization, so called shear band. Considering the two distinct deformation regions, two parameters are used to define their deformation respectively. According to the analysis of chip formation process, the equations have been deduced to calculate the shear strains of shear band ε, shear strain of chip segment ε 1 and shear rate so that the shear localized chip deformation can be assessed correctly and comprehensively. By use of this assessment, the chip deformation in machining selenium treated stainless steel (STSS) and common stainless steel at various cutting conditions is investigated. The experiment results obtained by the machining of stainless steel prove that: (1) the shear strain and strain rate increase with the increasing of cutting speed; (2) the shear strain in shear band can be over 10 when cutting speed exceeding 200 m/min for both types of stainless steel, and it is much higher than the strain of chip segment. The difference will be enlarged as the cutting speed increasing; (3) As the comparison, the shear strain for the STSS is a little lower than that for JIS304; (4) The stain rate is extremely high (= 2.5×10 5 1/s ). In range of cutting speed less than 180 m/min, the strain rate for STSS is lower than that for JIS304. However, when the cutting speed is higher than 180 m/min, the strain rate for STSS is higher than that for JIS304.展开更多
Wire electric discharge machining(WEDM)process is used for precision manufacturing.The accuracy of machining is function of various parameters like current,voltage,wire speed,gap between wire and work piece,wire oscil...Wire electric discharge machining(WEDM)process is used for precision manufacturing.The accuracy of machining is function of various parameters like current,voltage,wire speed,gap between wire and work piece,wire oscillation,work material,wire material,etc.Once the process parameters are selected,it is important that the wire vibrations are less to obtain a good surface finish.Due to the importance of wire vibration in obtaining the surface finish,it is necessary to study the wire vibration.This paper discusses different models of wire vibration presented in the literature and simulates a closed form solution of wire vibration using MATLAB.The transverse vibration of wire is analysed as forced vibration of moving wire with excitation due to the sparks during machining.The resulting partial differential equation is solved by using finite difference method and vibration is also simulated in the finite element package‘ANSYS’.The wire behaviour is investigated under different operating conditions and results of the two methods are展开更多
Tungsten heavy alloys have come up as one of the best alternatives for high density fragmenting devices and armor piercing ammunition.Machining is mandatory for obtaining the final shapes of such kind of ammunitions.H...Tungsten heavy alloys have come up as one of the best alternatives for high density fragmenting devices and armor piercing ammunition.Machining is mandatory for obtaining the final shapes of such kind of ammunitions.However,due to high density and elastic stiffness of WHAs,cutting forces will be higher than for most of the metals and alloys;thus,making the machining operation challenging.The machining variable,namely,cutting force components are significantly influenced by the cutting parameters.This paper makes use of Oxley’s predictive analytical model in conjunction with Johnson-Cook constitutive equation to predict forces under different speed and feed combinations during machining of 95 W tungsten heavy alloy.The cutting forces,so predicted by Ml,are considered as input data for the optimization of cutting parameters(cutting speed and feed)using Response Surface Method(RSM).展开更多
基金Projects(U22B2084,52275483,52075142)supported by the National Natural Science Foundation of ChinaProject(2023ZY01050)supported by the Ministry of Industry and Information Technology High Quality Development,China。
文摘The gears of new energy vehicles are required to withstand higher rotational speeds and greater loads,which puts forward higher precision essentials for gear manufacturing.However,machining process parameters can cause changes in cutting force/heat,resulting in affecting gear machining precision.Therefore,this paper studies the effect of different process parameters on gear machining precision.A multi-objective optimization model is established for the relationship between process parameters and tooth surface deviations,tooth profile deviations,and tooth lead deviations through the cutting speed,feed rate,and cutting depth of the worm wheel gear grinding machine.The response surface method(RSM)is used for experimental design,and the corresponding experimental results and optimal process parameters are obtained.Subsequently,gray relational analysis-principal component analysis(GRA-PCA),particle swarm optimization(PSO),and genetic algorithm-particle swarm optimization(GA-PSO)methods are used to analyze the experimental results and obtain different optimal process parameters.The results show that optimal process parameters obtained by the GRA-PCA,PSO,and GA-PSO methods improve the gear machining precision.Moreover,the gear machining precision obtained by GA-PSO is superior to other methods.
文摘Background Plant tissue culture has emerged as a tool for improving cotton propagation and genetics,but recalcitrance nature of cotton makes it difficult to develop in vitro regeneration.Cotton’s recalcitrance is influenced by genotype,explant type,and environmental conditions.To overcome these issues,this study uses different machine learning-based predictive models by employing multiple input factors.Cotyledonary node explants of two commercial cotton cultivars(STN-468 and GSN-12)were isolated from 7–8 days old seedlings,preconditioned with 5,10,and 20 mg·L^(-1) kinetin(KIN)for 10 days.Thereafter,explants were postconditioned on full Murashige and Skoog(MS),1/2MS,1/4MS,and full MS+0.05 mg·L^(-1) KIN,cultured in growth room enlightened with red and blue light-emitting diodes(LED)combination.Statistical analysis(analysis of variance,regression analysis)was employed to assess the impact of different treatments on shoot regeneration,with artificial intelligence(AI)models used for confirming the findings.Results GSN-12 exhibited superior shoot regeneration potential compared with STN-468,with an average of 4.99 shoots per explant versus 3.97.Optimal results were achieved with 5 mg·L^(-1) KIN preconditioning,1/4MS postconditioning,and 80%red LED,with maximum of 7.75 shoot count for GSN-12 under these conditions;while STN-468 reached 6.00 shoots under the conditions of 10 mg·L^(-1) KIN preconditioning,MS with 0.05 mg·L^(-1) KIN(postconditioning)and 75.0%red LED.Rooting was successfully achieved with naphthalene acetic acid and activated charcoal.Additionally,three different powerful AI-based models,namely,extreme gradient boost(XGBoost),random forest(RF),and the artificial neural network-based multilayer perceptron(MLP)regression models validated the findings.Conclusion GSN-12 outperformed STN-468 with optimal results from 5 mg·L^(-1) KIN+1/4MS+80%red LED.Application of machine learning-based prediction models to optimize cotton tissue culture protocols for shoot regeneration is helpful to improve cotton regeneration efficiency.
基金funded through India Meteorological Department,New Delhi,India under the Forecasting Agricultural output using Space,Agrometeorol ogy and Land based observations(FASAL)project and fund number:No.ASC/FASAL/KT-11/01/HQ-2010.
文摘Background Cotton is one of the most important commercial crops after food crops,especially in countries like India,where it’s grown extensively under rainfed conditions.Because of its usage in multiple industries,such as textile,medicine,and automobile industries,it has greater commercial importance.The crop’s performance is greatly influenced by prevailing weather dynamics.As climate changes,assessing how weather changes affect crop performance is essential.Among various techniques that are available,crop models are the most effective and widely used tools for predicting yields.Results This study compares statistical and machine learning models to assess their ability to predict cotton yield across major producing districts of Karnataka,India,utilizing a long-term dataset spanning from 1990 to 2023 that includes yield and weather factors.The artificial neural networks(ANNs)performed superiorly with acceptable yield deviations ranging within±10%during both vegetative stage(F1)and mid stage(F2)for cotton.The model evaluation metrics such as root mean square error(RMSE),normalized root mean square error(nRMSE),and modelling efficiency(EF)were also within the acceptance limits in most districts.Furthermore,the tested ANN model was used to assess the importance of the dominant weather factors influencing crop yield in each district.Specifically,the use of morning relative humidity as an individual parameter and its interaction with maximum and minimum tempera-ture had a major influence on cotton yield in most of the yield predicted districts.These differences highlighted the differential interactions of weather factors in each district for cotton yield formation,highlighting individual response of each weather factor under different soils and management conditions over the major cotton growing districts of Karnataka.Conclusions Compared with statistical models,machine learning models such as ANNs proved higher efficiency in forecasting the cotton yield due to their ability to consider the interactive effects of weather factors on yield forma-tion at different growth stages.This highlights the best suitability of ANNs for yield forecasting in rainfed conditions and for the study on relative impacts of weather factors on yield.Thus,the study aims to provide valuable insights to support stakeholders in planning effective crop management strategies and formulating relevant policies.
文摘Machine picking in cotton is an emerging practice in India,to solve the problems of labour shortages and production costs increasing.Cotton production has been declining in recent years;however,the high density planting system(HDPS)offers a viable method to enhance productivity by increasing plant populations per unit area,optimizing resource utilization,and facilitating machine picking.Cotton is an indeterminate plant that produce excessive vegeta-tive growth in favorable soil fertility and moisture conditions,which posing challenges for efficient machine picking.To address this issue,the application of plant growth retardants(PGRs)is essential for controlling canopy architecture.PGRs reduce internode elongation,promote regulated branching,and increase plant compactness,making cotton plants better suited for machine picking.PGRs application also optimizes photosynthates distribution between veg-etative and reproductive growth,resulting in higher yields and improved fibre quality.The integration of HDPS and PGRs applications results in an optimal plant architecture for improving machine picking efficiency.However,the success of this integration is determined by some factors,including cotton variety,environmental conditions,and geographical variations.These approaches not only address yield stagnation and labour shortages but also help to establish more effective and sustainable cotton farming practices,resulting in higher cotton productivity.
基金supported by National Natural Science Foundation of China(Grant No.12432018,12372346)the Innovative Research Groups of the National Natural Science Foundation of China(Grant No.12221002).
文摘A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.
文摘Electrochemical machining (ECM) is one of the best al ternatives for producing complex shapes in advanced materials used in aircraft a nd aerospace industries. However, the reduction of the stray material removal co ntinues to be major challenges for industries in addressing accuracy improvement . This study presents a method of improving machining accuracy in ECM by using a dual pole tool with a metallic bush outside the insulated coating of a cathode tool. The bush is connected with anode and so the electric field at the side gap area is substantially weakened. The modeling and simulation indicate that the p ositive bush brings down the current density at the side gap area of the machine d hole and hence reduces the stray material removal there. It has been experimen tally observed that the machining accuracy and the process stability are signifi cantly improved.
文摘The Al 2O 3 particles reinforced aluminum matrix composite (Al 2O 3p/Al) are more and more widely used for their excellent physical and chemical properties. However, their poor machinability leads to severe tool wear and bad machined surface. In this paper laser assisted machining is adopted in machining Al 2O 3p/Al composite and good result was obtained. The result of experiment shows in machining Al 2O 3p/Al composites the cutting force is reduced in 30%～50%, the tool wear is reduced in 20%～30% and machined surface quality is improved in laser assisted machining as compared with conventional cutting. The physical model of the cutting process is set up and explains the reason why the cutting forced are reduced. The state of the particles is the main influence of the change. When the material of cutting zone is heating by laser, the aluminum matrix becomes softer and easier in plastic deformation, which leads to the reduction of the pushing force from the tool to the machined surface. The soften aluminum matrix is more easy to be squeezed out from the machined surface, and it leads the concentration of the Al 2O 3 particles in the surface layer of machined surface. The softening effect of laser heating on aluminum matrix reduces the pushing forces of the Al 2O 3 particles on the clearance face of cutting tool, which is just the reason for the severe cutting tool wear in conventional machining of Al 2O 3p/Al composite. Because the Al 2O 3 particles were pushed in during the cutting process, the particles increased in the surface layer. Because of the difference in thermal conductivity and thermal expansion between the Al-matrix and Al 2O 3 particle, residual stress is changed in the matrix after machining due to the extrusion of the tool, deformation of the matrix and displacement of the Al 2O 3 particle in the matrix. Temperature gradient comes into the cutting zone and the work-piece surface layer, it will lead to the increase of thermal stress and misfit dislocation in the matrix. The residual stress is compressive in the laser assisted hot cutting surface, the compressive stress is nearly triple times than that in the conventional cutting surface. Some analysis on the mechanism of laser heat assisted machining of Al 2O 3p/Al composite is given in the paper too.
文摘For electro-discharge machining, only in the optimum state could the highest material removal rate be realized. In practical machining process, the timely elevation of the tool electrode is needed to eliminate chipping, which ordinarily occupies quite a lot of time. Therefore, besides the control of the machining parameters, the control of the optimum discharge gap and the conversion of different machining states is also needed. In this paper, the adaptive fuzzy control system of servomechanism for EDM combined with ultrasonic vibration is studied, the servomechanism of which is composed of the stepping motor comprising variable steps and the inductive synchronizer. The fuzzy control technology is used to realize the control of the frequency and the step of the servomechanism. The adaptive fuzzy controller has three inputs and two outputs, which can well meet the actual control requirements. The constitution of the fuzzy control regulation for the step frequency is the key to the design of the whole fuzzy control system of the servomechanism. The step frequency is mainly determined by the position error and the change rate of the position error. When the value of the position error is high or medium, the controlled parameters are selected to eliminate the error; when the position error is lower, the controlled parameters are selected to avoid the over-orientation and thus keep the stability of the system. According to these, a fuzzy control table is established in advanced, which is used to express the relations between the fuzzy input parameters and the fuzzy output parameters. The input parameters and the output parameters are all expressed by the level-values in fuzzy field. Therefore, the output parameters used for control can be obtained for the fuzzy control table according to the detected actual input parameters, by which the EDM combined with ultrasonic vibration is improved and the machining efficiency is increased. In addition, a stimulation program is designed by means of Microsoft Visual Basic
基金Projects(50574091, 50774084) supported by the National Natural Science Foundation of ChinaProject(50921001) supported by the Innovative Research Group Science Foundation,ChinaProject supported by Jiangsu Scientific Researching Fund Project ("333" Project),China
文摘A new concept of banana vibrating screen which has the same effect as traditional banana vibrating screen in a new way was put forward.The dynamic model of vibrating screen was established and its working principle was analyzed when the action line of the exciting force did not act through the centroid of screen box.Moreover,the dynamic differential equations of centroid and screen surface were obtained.The motions of centroid and screen surface were simulated with actual parameters of the design example in Matlab/Simulink.The results show that not only the amplitude has a significant decrease from 9.38 to 4.10 mm,but also the throwing index and vibrating direction angle have a significant decrease from 10.49 to 4.59,and from 58.10° to 33.29°,respectively,along the screen surface,which indicates that motion characteristics of vibrating screen are consistent with those of traditional banana vibrating screen only by means of a single angle of screen surface.What's more,such banana vibrating screen of variable linear trajectory with greater processing capacity could be obtained by adjusting the relative position of force center and the centroid of screen box properly.
基金Project(50635040) supported by the National Natural Science Foundation of ChinaProject(2009AA044205) supported by the National High Technology Research and Development ProgramProject(BK2008043) supported by the Jiangsu Provincial Natural Science Foundation,China
文摘The influences of the mask wall angle on the current density distribution,shape of the evolving cavity and machining accuracy were investigated in electrochemical machining(ECM) by mask.A mathematical model was developed to predict the shape evolution during the ECM by mask.The current density distribution is sensitive to mask wall angle.The evolution of cavity is determined by the current density distribution of evolving workpiece surface.The maximum depth is away from the center of holes machined,which leads to the island appearing at the center of cavity for mask wall angles greater than or equal to 90°(β≥90°).The experimental system was established and the simulation results were experimentally verified.The results indicate that the simulation results of cavity shape are consistent with the actual ones.The experiments also show that the repetition accuracy of matrix-hole for β≥90° is higher than that for β<90°.A hole taper is diminished,and the machining accuracy is improved with the mask wall angle increasing.
基金Projects(51575010,51575009)supported by the National Natural Science Foundations of ChinaProject(Z1511000003150138)supported by Beijing Nova Program,China
文摘In heavy duty machine tools, hydrostatic turntable is often used as a means for providing rotational motion and supporting workpiece, so the accuracy of turntable is crucial for part machining. In order to analyze the influence of load-indcued errors on machining accuracy, an identification model of load-induced errors based on the deformation caused by applied load of hydrostatic turntable of computerized numerical control(CNC) gantry milling heavy machine is proposed. Based on multi-body system theory and screw theory, the space machining accuracy model of heavy duty machine tool is established with consideration of identified load-induced errors. And then, the influence of load-induced errors on space machining accuracy and the roundness error of a milled hole is analyzed. The analysis results show that load-induced errors have a big influence on the roundness error of machined hole, especially when the center of the milled hole is far from that of hydrostatic turntable.
文摘In this study, a newly developed titanium superalloy, i.e., the Ti-5553 alloy has used for hot machining. This material replaced Ti-grade-5 alloy in the application of aerospace, automobile, and biomedical sector. However, similar to Ti-grade-5 alloy, the Ti-5553 alloy has a low thermal conductivity which makes it difficult-to-cut material categories hence, high tool wear, cutting force and bad surface finish. Hot machining of Ti-5553 has been studied at different machining condition (room and hot) using Deform-2D finite element analysis. The result from the simulation test was compared with the experimental value and reduction of cutting and thrust forces was observed. The experiment was carried out with the same input parameters as simulation, and good coherence between them observed. Additionally, cutting zone temperature, effective stress, etc. for both room and elevated the temperature are also discussed.
基金Project(91023042)supported by the National Natural Science Foundation of ChinaProject(2011CB013200)supported by the National Basic Research Program of China+1 种基金Project(B090302)supported by the Fund of Innovation,Graduate School of National University of Defense Technology,ChinaProject(CX2009B004)supported by the Hunan Provincial Innovation Foundation for Postgraduate,China
文摘Based on the distribution characteristic of magnetic field along the polish wheel,the four-axis linkage technique is advanced to replace a standard five-axis one to figure low-gradient optical surfaces with a raster tool-path in magnetorheological finishing(MRF).After introducing the fundaments of such simplification,the figuring reachability of a four-axis system for the low-gradient optics was theoretically analyzed.Further validation including magnetic field intensity and influence function characteristic was performed to establish its application.To demonstrate the correctness,feasibility and applicability of such technique,a K4 spherical part was figured by two iterations of MRF with surface form error improved to 0.219λPV and 0.027λRMS.Meanwhile,the surface roughness was also improved a lot in MRF process.These theoretical analyses and experimental results both indicate that high form accuracy and excellent surface quality can be obtained by using the four-axis linkage technique in the process of figuring low-gradient optical elements,and the four-axis linkage system undoubtedly is much more easy to control and much more economical.
文摘Powder Mixed Electric Discharge Machining (PMEDM) has different mechanism from conventional EDM, which can improve the surface roughness and surface quality distinctly and to obtain nearly mirror surface effects. It is a useful finish machining method and is researched and applied by many countries. However there are little research on rough machining of PMEDM. Experiments show that PMEDM machining makes discharge breakdown easier, enlarges the discharge gaps and widens discharge passage, and at last forms even distributed and "large and shadow" shaped etched cavities. Because of much loss of discharge energy in the discharge gaps and reduction of ejecting force on the melted material, the machining efficiency gets lower and the surface roughness gets small in PMEDM machining in comparison with conventional EDM machining. This paper performs experimental research on the machining efficiency and surface roughness of PMEDM in rough machining. The machining efficiency of PMEDM can be highly increased by selecting proper discharge parameters (increasing peak current, reducing pulse width) with approximate surface roughness in comparison with conventional EDM machining. Although PMEDM can improve machining efficiency in rough efficiency, but a series of problems like electrode wear, efficiently separation of machined scraps from the powder mixed working fluid, should be solved before PMEDM machining is really applied in rough machining. Experiments result shows that powder mixed EDM machining can obviously improve machining efficiency at the same surface roughness by selecting proper discharging parameters, and can provide reference accordingly for the application of PMEDM machining technology in rough machining.
文摘This paper describes a new method of surface modification by Electrical Discharge Machining (EDM). By using ordinary EDM machine tool and kerosene fluid, a hard ceramic layer can be created on the workpiece surface with Ti or other compressed powder electrode in a certain condition. This new revolutionary method is called Electrical Discharge Coating (EDC). The process of EDC begins with electrode wear during EDM,then a kind of hard carbide is created through the thermal and chemical reaction between the worn electrode material and the carbon particle decomposed from kerosene fluid under high temperature. The carbide is piled up on a workpiece quickly and becomes a hard layer of ceramic about 20 μm in several minutes. This paper studies the principle and process of EDC systemically by using Ti powder green compact electrode. In order to obtain a layer of compact ceramic film, it is very important to select proper electric pulse parameters, such as pulse width, pulse interval, peak current. Meantime, the electrode materials and its forming mode will effect the machining surface quality greatly. This paper presents a series of experiment results to study the EDC process by adopt different technology parameters. Experiments and analyses show that a compact TiC ceramic layer can be created on the surface of metal workpiece. The hardness of ceramic layer is more 3 times higher than the base body, and the hardness changes gradiently from surface to base body. The method will have a great future because many materials can be easily added to the electrode and then be coated on the workpiece surface. Gearing the parameters ceramic can be created with different thickness. The switch between deposition and removal process is carried out easily by changing the polarity, thus the gear to the thickness and shape of the composite ceramic layer is carried out easily. This kind of composite ceramic layer will be used to deal with the surface of the cutting tools or molds possibly, in order to lengthen their life. It also can be found wide application in the fields of surface repairing and strengthening of the ship or aircraft.
文摘Ultrasonic machining (USM) is considered as an effective method for machining hard and brittle materials such as glass, engineering ceramics, semiconductors, diamonds, metal composites and so on. However, the low material removal rate due to using abrasive slurry limits further application of USM. Rotary ultrasonic machining (rotary USM) superimposes rotational movement on the tool head that vibrates at ultrasonic frequency (20 kHz) simultaneously. The tool is made of mild steel coated or bonded with diamond abrasive. Therefore, abrasive slurry is abandoned and coolant is used to carry debris out of working area. Compared with USM, rotary USM can obtain much higher material removal rate, deep holes, and fine precision, which leads to its further application. Combined with CNC technology, rotary USM can be used to conduct contour machining of hard and brittle materials. In this paper, the movement of abrasive particles in tool tip of rotary ultrasonic machining is analyzed. The impacting and grinding of abrasive in tool tip to machined surface are considered as main factors to material removal rate. The process of crack forming and growing in one loading and unloading cycle can be described as following stages: a) When abrasive particle acts the pressure on work-piece, the macro cracks in periphery of contact area are exerted increasing tensile stress. b) As the tensile stress increase to the critical of material tension, the one of cracks in periphery of contact area begins to propagate around contact area and develop beneath the surface to certain depth. c) Indentation area varies with increasing of load, the circle crack around contact area steadily or dynamical propagates towards inside of work-piece. d) As tensile stress in crack increases to critical of crack steady failure, circle crack suddenly becomes conic crack. e) Further increase load, the crack continues to grow while contact area is surrounded by conic cracks. f) During unloading, conic crack begins to close, some of cracks continue their extension towards the surface and forms a circle groove. The mathematical model for material removal rate shows that the factors affecting on material removal rate are static load, grid and concentration of abrasive, mechanical properties of machined materials, rotational speed of tool and feed speed of work-piece.
文摘As the cutting speed goes higher, the mechanism of chip deformation will be changed significantly, i.e., continuous chip in low cutting speed will shift to serrated chip with shear localization. For the shear localized chip, the parameters used to assess the chip deformation for continuous chip, such as shorten coefficient ξ, shear angle φ and shear strain ε, can not describe the chip deformation correctly or comprehensively. This paper deals with the assessment of chip deformation of shear localization. There are two deformation regions in shear localized chip, one is the chip segment body with relative smaller plastic deformation, another one is the boundary between segments with shear localization, so called shear band. Considering the two distinct deformation regions, two parameters are used to define their deformation respectively. According to the analysis of chip formation process, the equations have been deduced to calculate the shear strains of shear band ε, shear strain of chip segment ε 1 and shear rate so that the shear localized chip deformation can be assessed correctly and comprehensively. By use of this assessment, the chip deformation in machining selenium treated stainless steel (STSS) and common stainless steel at various cutting conditions is investigated. The experiment results obtained by the machining of stainless steel prove that: (1) the shear strain and strain rate increase with the increasing of cutting speed; (2) the shear strain in shear band can be over 10 when cutting speed exceeding 200 m/min for both types of stainless steel, and it is much higher than the strain of chip segment. The difference will be enlarged as the cutting speed increasing; (3) As the comparison, the shear strain for the STSS is a little lower than that for JIS304; (4) The stain rate is extremely high (= 2.5×10 5 1/s ). In range of cutting speed less than 180 m/min, the strain rate for STSS is lower than that for JIS304. However, when the cutting speed is higher than 180 m/min, the strain rate for STSS is higher than that for JIS304.
文摘Wire electric discharge machining(WEDM)process is used for precision manufacturing.The accuracy of machining is function of various parameters like current,voltage,wire speed,gap between wire and work piece,wire oscillation,work material,wire material,etc.Once the process parameters are selected,it is important that the wire vibrations are less to obtain a good surface finish.Due to the importance of wire vibration in obtaining the surface finish,it is necessary to study the wire vibration.This paper discusses different models of wire vibration presented in the literature and simulates a closed form solution of wire vibration using MATLAB.The transverse vibration of wire is analysed as forced vibration of moving wire with excitation due to the sparks during machining.The resulting partial differential equation is solved by using finite difference method and vibration is also simulated in the finite element package‘ANSYS’.The wire behaviour is investigated under different operating conditions and results of the two methods are
文摘Tungsten heavy alloys have come up as one of the best alternatives for high density fragmenting devices and armor piercing ammunition.Machining is mandatory for obtaining the final shapes of such kind of ammunitions.However,due to high density and elastic stiffness of WHAs,cutting forces will be higher than for most of the metals and alloys;thus,making the machining operation challenging.The machining variable,namely,cutting force components are significantly influenced by the cutting parameters.This paper makes use of Oxley’s predictive analytical model in conjunction with Johnson-Cook constitutive equation to predict forces under different speed and feed combinations during machining of 95 W tungsten heavy alloy.The cutting forces,so predicted by Ml,are considered as input data for the optimization of cutting parameters(cutting speed and feed)using Response Surface Method(RSM).
