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Investigation of electrostatically tunable adhesion and instability of flying head slider

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Friction 2024年第3期12卷 462-473页

作者： Fan ZHANG Yu WANG Yueqiang HU Mingquan ZHANG Baotong LI School of mechanical engineering Xi’an Jiaotong UniversityXi’an 710049China National engineering Research Center for High Efficiency Grinding College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China

The interfacial adhesion between microstructures is inevitable in a micro-electro-mechanical system(e.g.,hard disk drive(HDD)),which may lead to complicated microtribodynamics *** research has investigated the effect of surface potential on the interfacial adhesion and microtribodynamics of the head–disk interface(HDI)in an HDD.A dynamic continuum surface force model,where the electrowetting is considered,is proposed to evaluate the interfacial interaction,and then employed into a two-degree-of-freedom(2DOF)model to theoretically analyze the potential influence mechanism on the *** results confirm that the elimination of potential can effectively repress the adhesion retention,which is further proved by the measured slider response with a laser Doppler vibrometer(LDV).Moreover,the effect of the potential on the adhesion-induced instability is also analyzed through the phase *** tells that the critical stable flying height can be lowered with the elimination of potential.

关键词： electric field(EF) retention instability adhesion

Battery pack capacity estimation for electric vehicles based on enhanced machine learning and field data

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Journal of Energy Chemistry 2024年第5期92卷 605-618页

作者： Qingguang Qi Wenxue Liu Zhongwei Deng Jinwen Li Ziyou Song Xiaosong Hu college of mechanical and Vehicle engineering Chongqing UniversityChongqing 400044China School of mechanical and Electrical engineering University of Electronic Science and Technology of ChinaChengdu 611731SichuanChina Department of mechanical engineering National University of SingaporeSingapore 117575Singapore

Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion *** numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery *** challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity *** fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field *** proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction ***,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation ***,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV ***,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 *** results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing *** work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.

关键词： Electricvehicle Lithium-ion battery pack Capacity estimation Machine learning Field data

Electrical discharge and arc milling with automatic tracking of optimal flushing direction:A novel high-efficiency compound machining method

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Chinese Journal of Aeronautics 2024年第3期37卷 351-364页

作者： Xinlei WU Yonghong LIU Pengxin ZHANG Liang QI Dege LI Chi MA Renjie JI college of mechanical and Electronic engineering China University of Petroleum(East China)Qingdao 266580China School of mechanical and Power engineering Nanjing Tech UniversityNanjing 211816China

The arc milling method has the advantages of high machining efficiency and low cost and is independent of the strength and hardness of machined ***,frequent electrode back-offs and the risk of workpiece burning may occur if erosion products are not removed *** this study,it was found that the flushing method of the working medium had a significant impact on the machining performance of arc *** on this,a novel highefficiency compound machining method of electrical discharge and arc milling with automatic tracking of the optimal flushing direction was *** automatic tracking optimizer for external working medium injection was designed to determine the optimal external flushing direction according to the feed *** influence of flushing methods,working mediums,and machining parameters on the machining efficiency,tool electrode wear rate,machining error,and surface integrity of titanium alloys were *** results indicated that better machining performance and environmental friendliness were achieved using the compound flushing method of outer compressed air and inner deionized ***,the automatic tracking flushing method in the opposite direction of the feed direction showed superior results compared to other *** material removal rate with the opposite direction injection could be increased up to 1.62 times that of the same direction,and the relative electrode wear rate could be reduced by 14.76%.This novel method has broad application prospects for machining parts with difficult-to-cut materials in aerospace and military industries.

关键词： Arc milling Dielectric Difficult-to-cut materials Electric discharge machining Erosion Material removal rate

Switching,explosion,and chaos of multi-wavelength soliton states in ultrafast fiber lasers

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Science China(Physics,Mechanics & Astronomy) 2024年第7期67卷 82-90页

作者： Zhi-Zeng Si Yue-Yue Wang Chao-Qing Dai college of Optical Mechanical and Electrical EngineeringZhejiang A&F UniversityLin’an 311300China

Because of the complexity and difficulty of realizing a multi-wavelength soliton state,reports on its internal dynamic characteristics are *** this study,the switching and periodic soliton explosion processes of the multi-wavelength soliton state in a negative dispersion passively mode-locked fiber laser are *** generation of the multi-wavelength soliton state undergoes the process of noise,oscillation,and stable mode-locking,and the splitting and annihilation of solitons with different group velocities directly impact the generation and disappearance of three *** and negative dispersion lead to different group velocities of *** presence and displacement of solitons with different group velocities cause soliton collisions,which lead to soliton explosions.A soliton experiences relative phase oscillation,chaos,and oscillation,as well as convergence and separation before and after an *** an increase in parameters related to pump power,single-soliton oscillation,multi-wavelength solitons,and chaos are found in experiments and simulations,proving the relevance and reliability between simulation and experimental *** work promotes the dynamical study of multi-soliton collisions in nonlinear science and the development of chaos theory in multi-comb lasers.

关键词： multi-wavelength fiber laser soliton explosion chaos state switching real-time dynamics

Lattice Boltzmann method formulation for simulation of thermal radiation effects on non-Newtonian Al_(2)O_(3) free convection in entropy determination

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 1085-1106页

作者： M.NEMATI M.SEFID A.KARIMIPOUR A.J.CHAMKHA Faculty of mechanical engineering Yazd UniversityYazd ***Iran Department of mechanical engineering Najafabad BranchIslamic Azad UniversityNajafabad ***Iran Faculty of engineering Kuwait College of Science and TechnologyDoha 35004Kuwait

The simultaneous investigation on the parameters affecting the flow of electrically conductive fluids such as volumetric radiation,heat absorption,heat generation,and magnetic field(MF)is very vital due to its existence in various sectors of industry and *** present research focuses on mathematical modeling to simulate the cooling of a hot component through power-law(PL)nanofluid convection *** temperature reduction of the hot component inside a two-dimensional(2D)inclined chamber with two different cold wall shapes is *** formulation of the problem is derived with the lattice Boltzmann method(LBM)by code writing via the FORTRAN *** variables such as the radiation parameter(0–1),the Hartmann number(0–75),the heat absorption/generation coefficient(−5–5),the fluid behavioral index(0.8–1.2),the Rayleigh number(103–105),the imposed MF angle(0°–90°),the chamber inclination angle(−90°–90°),and the cavity cold wall shape(smooth and curved)are *** findings indicate that the presence of radiation increases the mean Nusselt number value for the shear-thickening,Newtonian,and shear thinning fluids by about 6.2%,4%,and 2%,*** most cases,the presence of nanoparticles improves the heat transfer(HT)rate,especially in the cases where thermal conduction dominates *** is the lowest cooling performance index and MF effect for the cavity placed at an angle of 90°.The application in the design of electronic coolers and solar collectors is one of the practical cases of this numerical research.

关键词： thermal performance analysis heat absorption/generation power-law(PL)Al_(2)O_(3)nanofluid magnetohydrodynamics natural convection volumetric radiation inclined cavity

Optimized system for combined production of electricity/green hydrogen for multiple energy pathways:a case study of Egypt

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Clean Energy 2024年第4期8卷 219-236页

作者： Reda Ragab Mohamed HamdiHafez A.El Salmawy Mohamed A.Ismail mechanical Power engineering Department Zagazig UniversityZagazig 44519Egypt mechanical engineering Department College of EngineeringKing Faisal UniversityAl-Ahsa 31982Saudi Arabia

By optimal sizing of a wind/photovoltaic hybrid renewable-energy(RE)system,trimming the surplus capacity to reduce the fluctuations in the electricity supplied to the grid,and using it to produce green hydrogen through electrolysis,a stable output with maximum possible capacity factor(CF)is generated to maintain the electricity grid ***,the trimmed energy is used in a secondary conversion path that minimizes the weighted average cost of the energy generated from the entire *** surplus power-to-gas conversion allows the use of green hydrogen to produce electricity,methanol,or ammonia subject to the resource availability,site characteristics,and financial *** on robust site selection criteria,the best performance is obtained at two sites:Ras Ghareb and Minya,achieving the lowest energy cost with some variance in their *** the Ras Ghareb site,the optimally sized RE plant provided the grid with a quasi-steady capacity of 423 MW with a CF of 80.04%and was capable of injecting 2965.8648 GWh throughout the year with the lowest cost of 2.4355¢/kWh.A surplus of 3.9%of the total energy produced from the plant was directed to produce 1922-ton H_(2)/year,achieving the lowest cost of hydrogen production of$1.9745/kg H_(2).For the other selected site,Minya,the clipped energy is used to produce 3330.47-ton H_(2)/year with an optimized lowest cost of$3.5268/kg H_(2).The difference in hydrogen costs was attributed to the number of full operating hours of the electrolyser in both *** cost is mainly affected by the electricity price and the electrolyser *** both tending to decrease,future forecasts show hydrogen cost reductions.

关键词： hybrid renewable-energy system(HRES) green hydrogen electrolysis power-to-gas methanol ammonia

Real-Time Intelligent Diagnosis of Co-frequency Vibration Faults in Rotating Machinery Based on Lightweight-Convolutional Neural Networks

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Chinese Journal of mechanical engineering 2024年第2期37卷 264-282页

作者： Xin Pan Xiancheng Zhang Zhinong Jiang Guangfu Bin Beijing Key Laboratory of Health Monitoring and Self-recovery for High-End mechanical Equipment College of Mechanical and Electrical EngineeringBeijing University of Chemical TechnologyBeijing 100029China Key Laboratory of Engine Health Monitoring-Control and Networking(Ministry of Education) College of Mechanical and Electrical EngineeringBeijing University of Chemical TechnologyBeijing 100029China college of mechanical engineering Hunan University of Science and TechnologyXiangtan 411201China

The co-frequency vibration fault is one of the common faults in the operation of rotating equipment,and realizing the real-time diagnosis of the co-frequency vibration fault is of great significance for monitoring the health state and carrying out vibration suppression of the *** engineering scenarios,co-frequency vibration faults are highlighted by rotational frequency and are difficult to identify,and existing intelligent methods require more hardware conditions and are exclusively ***,Lightweight-convolutional neural networks(LW-CNN)algorithm is proposed in this paper to achieve real-time fault *** critical parameters are discussed and verified by simulated and experimental signals for the sliding window data augmentation *** on LW-CNN and data augmentation,the real-time intelligent diagnosis of co-frequency is ***,a real-time detection method of fault diagnosis algorithm is proposed for data acquisition to fault *** is verified by experiments that the LW-CNN and sliding window methods are used with high accuracy and real-time performance.

关键词： Co-frequency vibration Real-time diagnosis LW-CNN Data augmentation

Method for Detecting Industrial Defects in Intelligent Manufacturing Using Deep Learning

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Computers, Materials & Continua 2024年第1期78卷 1329-1343页

作者： Bowen Yu Chunli Xie college of mechanical and Electrical engineering Northeast Forestry UniversityHarbin150040China

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

关键词： Industrial defect detection deep learning intelligent manufacturing

Semantic Entity Recognition and Relation Construction Method for Assembly Process Document

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 537-556页

作者：顾星海花豹刘亚辉孙学民鲍劲松 college of mechanical engineering Donghua UniversityShanghai 201620China

Assembly process documents record the designers'intention or ***,common knowl-edge extraction methods are not well suitable for assembly process documents,because of its tabular form and unstructured natural language *** this paper,an assembly semantic entity recognition and relation con-struction method oriented to assembly process documents is ***,the assembly process sentences are extracted from the table through concerned region recognition and cell division,and they will be stored as a key-value object ***,the semantic entities in the sentence are identified through the sequence tagging model based on the specific attention mechanism for assembly operation *** syntactic rules are designed for realizing automatic construction of relation between ***,by using the self-constructed corpus,it is proved that the sequence tagging model in the proposed method performs better than the mainstream named entity recognition model when handling assembly process design *** effectiveness of the proposed method is also analyzed through the simulation experiment in the small-scale real scene,compared with manual *** results show that the proposed method can help designers accumulate knowledge automatically and efficiently.

关键词： assembly process design knowledge extraction named entity recognition text extraction in table dependency syntactic parsing attention mechanism