Field-assisted machining of difficult-to-machine materials

Difficult-to-machine materials (DMMs) are extensively applied in critical fields such as aviation,semiconductor,biomedicine,and other key fields due to their excellent material properties.However,traditional machining technologies often struggle to achieve ultra-precision with DMMs resulting from poor surface quality and low processing efficiency.In recent years,field-assisted machining (FAM) technology has emerged as a new generation of machining technology based on innovative principles such as laser heating,tool vibration,magnetic magnetization,and plasma modification,providing a new solution for improving the machinability of DMMs.This technology not only addresses these limitations of traditional machining methods,but also has become a hot topic of research in the domain of ultra-precision machining of DMMs.Many new methods and principles have been introduced and investigated one after another,yet few studies have presented a comprehensive analysis and summarization.To fill this gap and understand the development trend of FAM,this study provides an important overview of FAM,covering different assisted machining methods,application effects,mechanism analysis,and equipment design.The current deficiencies and future challenges of FAM are summarized to lay the foundation for the further development of multi-field hybrid assisted and intelligent FAM technologies.

Optimization of steel casting feeding system based on BP neural network and genetic algorithm

The trial-and-error method is widely used for the current optimization of the steel casting feeding system, which is highly random, subjective and thus ineff icient. In the present work, both the theoretical and the experimental research on the modeling and optimization methods of the process are studied. An approximate alternative model is established based on the Back Propagation(BP) neural network and experimental design. The process parameters of the feeding system are taken as the input, the volumes of shrinkage cavities and porosities calculated by simulation are simultaneously taken as the output. Thus, a mathematical model is established by the BP neural network to combine the input variables with the output response. Then, this model is optimized by the nonlinear optimization function of the genetic algorithm. Finally, a feeding system optimization of a steel traveling wheel is conducted. No shrinkage cavities and porosities are induced through the optimization. Compared to the initial design scheme, the process yield is increased by 4.1% and the volume of the riser is decreased by 5.48×10~6 mm3.

Research on Fuzzy Control for Automatic Transmission of Tracked Vehicles

A principle of fuzzy control for tracked vehicles is proposed to make its automatic transmission system be able to adapt complex running conditions, and a model of its power train is established to be used in simulation. Based on the fuzzy control method, a fuzzy shift control system composed of a basic shift strategy and a fuzzy modification module is developed to improve the dynamic characteristics and cross-country maneuverability. Simulation results show that the fuzzy shift strategy can improve the shift quality under manifold driving conditions and avoid cycled shift effectively.Therefore, the proposed fuzzy shift strategies are proved to be feasible and practicable.

Simulations of Coarsening Behavior for M_(23)C_6 Carbides in AISI H13 Steel

Based on the local equilibrium assumption, coarsening behavior of M23C6 carbide at 700℃ in H13 steel was simulated by DICTRA software. The results from the calculations were compared with transmission electron microscopy （TEM） observations. The results show the interracial energy for M23C6 in H13 steel at 700℃ is thus probably 0.7J·m^-2, which fits the experiments well. The influence of composition and temperature on the coarsening rate was also investigated by simulations. Simulations show a decrease in the coarsening rate when V/Mo ratio is increased, while the coarsening rate increases with increasing temperature.

Mechanism of Strength Loss of No-bake Phosphate Bonded Sand Mold/Core

The strength loss mechanism of the phosphate bonded sand mold/core was studied. The morphology and composition of phosphate membrane on the surface of sands was analyzed with electron probe X-ray microanalyzer. Results show that magnesium causes cracks in cured phosphate membrane and results in the decrease of sand molds/cores strength. However, the addition of magne-sium significantly enhanced hygroscopy resistance of phosphate membrane. In addition, the phosphate binder added with the magnesium modifier has more rapid hardening reaction speed compared that without or with low magnesium binder. It can be concluded that the phosphate binder with the addition of magnesium modifier is favorably used in high humid and cold circumstance.

Mierostrueture and Properties of Coating from Cemented Carbide on Surface of Hl3 Steel

The microstructures and properties of coating from cemented carbide on the substrate of H 13 by vacuum powder sintering were studied. The effect of sintering temperature on the microstructures of coating was discussed. The interface characteristics between coating and H 13 steel substrate, microhardness distribution and wear resistance in the coating were analyzed. The coating from cemented carbide with thickness of 1-3 mm by vacuum powder sintering at temperature ranging from 1280℃to 1300 ℃ was obtained. The experimental results indicated that the coating with microhardness of HV 1600 favorable to wear resistance is strongly bonded with the H 13 steel substrate by mutual diffusion and penetration of Fe,Cr, Mo,V in substrate towards the coating and W, Co,Ni in coating towards the substrate.

CHARACTER DETECTION AND RECOGNITION SYSTEM OF BEER BOTTLES

An optical imaging system and a configuration characteristic algorithm are presented to reduce the difficulties in extracting intact characters image with weak contrast, in recognizing characters on fast moving beer bottles. The system consists of a hardware subsystem, including a rotating device, CCD, 16 mm focus lens, a frame grabber card, a penetrating lighting and a computer, and a software subsystem. The software subsystem performs pretreatment, character segmentation and character recognition. In the pretreatment, the original image is filtered with preset threshold to remove isolated spots. Then the horizontal projection and the vertical projection are used respectively to retrieve the character segmentation. Subsequently, the configuration characteristic algorithm is applied to recognize the characters. The experimental results demonstrate that this system can recognize the characters on beer bottles accurately and effectively; the algorithm is proven fast, stable and robust, making it suitable in the industrial environment.

Fault diagnosis of HVAC system with imbalanced data using multi-scale convolution composite neural network

Accurate fault diagnosis of heating,ventilation,and air conditioning(HVAC)systems is of significant importance for maintaining normal operation,reducing energy consumption,and minimizing maintenance costs.However,in practical applications,it is challenging to obtain sufficient fault data for HVAC systems,leading to imbalanced data,where the number of fault samples is much smaller than that of normal samples.Moreover,most existing HVAC system fault diagnosis methods heavily rely on balanced training sets to achieve high fault diagnosis accuracy.Therefore,to address this issue,a composite neural network fault diagnosis model is proposed,which combines SMOTETomek,multi-scale one-dimensional convolutional neural networks(M1DCNN),and support vector machine(SVM).This method first utilizes SMOTETomek to augment the minority class samples in the imbalanced dataset,achieving a balanced number of faulty and normal data.Then,it employs the M1DCNN model to extract feature information from the augmented dataset.Finally,it replaces the original Softmax classifier with an SVM classifier for classification,thus enhancing the fault diagnosis accuracy.Using the SMOTETomek-M1DCNN-SVM method,we conducted fault diagnosis validation on both the ASHRAE RP-1043 dataset and experimental dataset with an imbalance ratio of 1:10.The results demonstrate the superiority of this approach,providing a novel and promising solution for intelligent building management,with accuracy and F1 scores of 98.45%and 100%for the RP-1043 dataset and experimental dataset,respectively.

Printed Circuit Board (PCB) Surface Micro Defect Detection Model Based on Residual Network with Novel Attention Mechanism

Printed Circuit Board(PCB)surface tiny defect detection is a difficult task in the integrated circuit industry,especially since the detection of tiny defects on PCB boards with large-size complex circuits has become one of the bottlenecks.To improve the performance of PCB surface tiny defects detection,a PCB tiny defects detection model based on an improved attention residual network(YOLOX-AttResNet)is proposed.First,the unsupervised clustering performance of the K-means algorithm is exploited to optimize the channel weights for subsequent operations by feeding the feature mapping into the SENet(Squeeze and Excitation Network)attention network;then the improved K-means-SENet network is fused with the directly mapped edges of the traditional ResNet network to form an augmented residual network(AttResNet);and finally,the AttResNet module is substituted for the traditional ResNet structure in the backbone feature extraction network of mainstream excellent detection models,thus improving the ability to extract small features from the backbone of the target detection network.The results of ablation experiments on a PCB surface defect dataset show that AttResNet is a reliable and efficient module.In Torify the performance of AttResNet for detecting small defects in large-size complex circuit images,a series of comparison experiments are further performed.The results show that the AttResNet module combines well with the five best existing target detection frameworks(YOLOv3,YOLOX,Faster R-CNN,TDD-Net,Cascade R-CNN),and all the combined new models have improved detection accuracy compared to the original model,which suggests that the AttResNet module proposed in this paper can help the detection model to extract target features.Among them,the YOLOX-AttResNet model proposed in this paper performs the best,with the highest accuracy of 98.45% and the detection speed of 36 FPS(Frames Per Second),which meets the accuracy and real-time requirements for the detection of tiny defects on PCB surfaces.This study can provide some new ideas for other real-time online detection tasks of tiny targets with high-resolution images.

Excess Activity Tuned by Distorted Tetrahedron in CoMoO_(4) for Oxygen Evolution

Oxygen vacancies enable modulating surface reconstruction of transition metal oxides containing metal-oxygen polyhedrons into metallic oxyhydroxide for oxygen evolution reaction(OER),while revealing reconstructing mechanism is stuck by the requirement to precisely control exact sites of these vacancies.Herein,oxygen vacancies are localized only within MoO_(4)tetrahedrons rather than CoO_(6)octahedrons in CoMoO_(4)catalyst,guaranteeing coherent reconstruction of CoO_(6)octahedrons into pure CoOOH with tunable activities for OER.Meanwhile,distorted tetrahedron accelerates the dissolution of Mo atoms into alkaline electrolyte,triggering spontaneous transition of partial CoMoO_(4)into Co(OH)_(2).CoO_(6)octahedrons in both CoMoO_(4)and Co(OH)_(2)can transform pure CoOOH completely at lower potential,resulting in excess intrinsic activity whose summit is identified by overpotential at 10 mA cm^(-2)with 22.9%reduction and Tafel slope with 65.3%reduction.Well-defined manipulation over the distorted polyhedrons offers one versatile knob to precisely modulate electronic structure of oxide catalysts with outstanding OER performance.

Design and implementation of a jellyfish otolith-inspired MEMS vector hydrophone for low-frequency detection

Detecting low-frequency underwater acoustic signals can be a challenge for marine applications.Inspired by the notably strong response of the auditory organs of pectis jellyfish to ultralow frequencies,a kind of otolith-inspired vector hydrophone(OVH)is developed,enabled by hollow buoyant spheres atop cilia.Full parametric analysis is performed to optimize the cilium structure in order to balance the resonance frequency and sensitivity.After the structural parameters of the OVH are determined,the stress distributions of various vector hydrophones are simulated and analyzed.The shock resistance of the OVH is also investigated.Finally,the OVH is fabricated and calibrated.The receiving sensitivity of the OVH is measured to be as high as−202.1 dB@100 Hz(0 dB@1 V/μPa),and the average equivalent pressure sensitivity over the frequency range of interest of the OVH reaches−173.8 dB when the frequency ranges from 20 to 200 Hz.The 3 dB polar width of the directivity pattern for the OVH is measured as 87°.Moreover,the OVH is demonstrated to operate under 10 MPa hydrostatic pressure.These results show that the OVH is promising in low-frequency underwater acoustic detection.

First-principles study on the synergistic effects of codoped anatase TiO_2 photocatalysts codoped with N/Vor C/Cr

An effective compensated codoping approach is described to modify the photoelectrochemical prop- erties of anatase TiO2 by doping with nonmetals （N or C） and transition metals （V or Cr） impurities. Here, com- pensated codoped TiO2 systems are constructed with different dopant species and sources, and then their dopant formation energies and electronic structures are performed to study the stability and visible-light photoactivity by first-principles plane-wave ultrasoft pseudopotential calculations, respectively. The calculated results demonstrate that the codoping with transition metals facilitates the enhancement of the concentration of p-type dopants （N and C） in a host lattice. Especially, compensated codoping not only reduces the energy gap, to enhance the optical ab sorption, and eliminate the local trapping, to improve carrier mobility and conversion efficiency, but it also keeps the oxidation-reduction potential of the conduction band edge. These results are conducive to the understanding of the synergistic mechanism of the photocatalytic activity of TiO2 that is enhanced by codoping.

Fabrication of sapphire rib waveguides using a femtosecond laser

We demonstrate a method for fabricating sapphire rib waveguides with femtosecond laser micromachining technology. Finite difference beam propagation method(FD-BPM) is applied to design sapphire rib waveguides. We explore the process of etching on a sapphire substrate surface via direct laser ablation. Rib waveguides that satisfies the dimensions of our design were fabricated. Actual light propagation performance is tested, and with the cut-back method, the insertion loss of 2.9±0.5 dB/cm is measured.

Experimental investigation for ultra-precision cutting of nickel based superalloy with the assistance of magnetic field

Nickel based superalloy is an important material because of its excellent properties under high temperatures.However,it is a difficult-to-machine material due to its low thermal conductivity,which can cause undesired localized high temperatures in the processing area.In this study,magnetic field-assisted end face turning experiments of nickel-based superalloy is carried out under the assistance of external magnetic fields of different strengths formed by permanent magnets.The experiment results show that,compared with ordinary machining,the chip morphology is improved,the oscillation of cutting force F_(c),F_(a),and Ffare significantly reduced by 90%,88%,and 78%,and the surface roughness Ra is improved from 23 to 13 nm,the P-V value of the fan-shaped area of the machined surface is reduced,and hardness and ductility are improved after the magnetic field is applied.The experiment results indicate that the application of a magnetic field is an efficient and convenient approach to improve the cutting performance of nickel based superalloy.

Evaluation of tool wear and cutting performance based on FEM simulation

An accurate estimation of tool wear morphology can provide the opportunity to investigate the influence of tool wear on cutting performance as well as reduce the overall production cost.However,tool wear prediction is still a very challenging research issue.In this paper,a novel method for simulating the actual chip formation and wear evolution thorough the 3 D finite element model has been carried out.In order to improve the accuracy of simulation results,the influence of worn tool,stress and temperature distribution on wear rate are considered.Then cutting experiment has been conducted by turning AISI1045 with uncoated carbide tools to validate the accuracy of the proposed model.The comparison between experimental and simulation results show good agreement which proves the ability of the proposed model in forecasting the tool wear.The validated finite element model has been further utilized studying how the worn tool affects the cutting performance including actual cutting rake,stress distribution,cutting force and temperature.The results of this paper not only provide a clear understanding of wear evolution between tool rake face and chip,but also are meaningful to optimize tool design and cutting parameters.

Theoretical calculation and analysis of ZrO_(2) spherical nanometer powders

ZrO_(2) spherical nanometer powders containing 3.5 mol%Y_(2)O_(3) have been prepared via the coupling route of water/oil(W/O)emulsion with dimethyl oxalate homogenous precipitation.ZrO_(2) powders and their precursor powders have been characterized by XRD,TEM and SEM.According to the XRD result,phase volume fractions of powders were calculated by comparing the peaks’intensities of spectrum.Furthermore,phase crystal lattice constants were obtained using crystal interplanar spacing formula and Bragg equation.With these results,the theoretical density of powders was analyzed.Finally,powders’spherical degree was revealed via the method of comparison between theoretical density and actual density.

Mechanism and characterization of nanosecond laser rust-removal on AH36 steel

In this paper,the effects of different laser powers,repetition rates,and spot overlaps on the surface roughness,micromorphology,and Vickers hardness of rusted AH36 steel were researched in the rust removal experiment of fiber pulse laser on the marine steel surface.Then,the mechanical properties,corrosion resistance,and metallographic microstructure of the surface of samples after laser cleaning were analyzed.The experimental results show that when the processing parameters were the laser power of 40 W,the repetition rate of 110 k Hz,and the spot overlap of 50%,the rust removal effect on AH36 steel was the best,and it met the cleanliness standard of marine steel coating.Moreover,its Vickers hardness,mechanical properties,corrosion resistance,and repainting properties were superior to those of the original substrate.

Liquid-solid Coupling Characteristics in the Fluidized Bed Evaporator for Tobacco Refined Liquid

Consider a two-phase liquid-solid coupling effect, using Euler - Euler two-fluid model is solved using standard viscous term with k- e model and the velocity pressure coupling a simple algorithm to simulate liquid-solid two-phase flow characteristics of the fluid flow method bed, the applicability of the model to assess the drag. Different effects of a two-stage flow characteristics of fluidized bed flow characteristics, fluid and operating conditions affect the physical properties of the paper. We found from the simulation is the use of different drag coefficient models will greatly affect the results, which drag force model Syamlal - O＇ Brien is more suited to study the coupling characteristics of liquid flow in a fluidized bed of solid than Gidaspow. And velocity of the inert particles increase with the viscosity of the liquid increase. Further, the maximum speed of the inert particles in a fluidized bed by a central, which means the settling velocity in the fluidized bed of inert particles is the slowest; increasing liquid density and lead to increased speed of the inert particles; volume of the inert particles Score changes can also affect the speed of the particle velocity distribution, and there is no linear relationship.

Flexible Job Shop Composite Dispatching Rule Mining Approach Based on an Improved Genetic Programming Algorithm

To obtain a suitable scheduling scheme in an effective time range,the minimum completion time is taken as the objective of Flexible Job Shop scheduling Problems(FJSP)with different scales,and Composite Dispatching Rules(CDRs)are applied to generate feasible solutions.Firstly,the binary tree coding method is adopted,and the constructed function set is normalized.Secondly,a CDR mining approach based on an Improved Genetic Programming Algorithm(IGPA)is designed.Two population initialization methods are introduced to enrich the initial population,and a superior and inferior population separation strategy is designed to improve the global search ability of the algorithm.At the same time,two individual mutation methods are introduced to improve the algorithm’s local search ability,to achieve the balance between global search and local search.In addition,the effectiveness of the IGPA and the superiority of CDRs are verified through comparative analysis.Finally,Deep Reinforcement Learning(DRL)is employed to solve the FJSP by incorporating the CDRs as the action set,the selection times are counted to further verify the superiority of CDRs.

Heterodyne detection enhanced by quantum correlation

Heterodyne detectors as phase-insensitive(PI) devices have found important applications in precision measurements such as space-based gravitational-wave(GW) observation.However, the output signal of a PI heterodyne detector is supposed to suffer from signal-to-noise ratio(SNR) degradation due to image band vacuum and imperfect quantum efficiency.Here, we show that the SNR degradation can be overcome when the image band vacuum is quantum correlated with the input signal.We calculate the noise figure of the detector and prove the feasibility of heterodyne detection with enhanced noise performance through quantum correlation.This work should be of great interest to ongoing space-borne GW signal searching experiments.