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The High-Efficiency Design Method for Capacitive MEMS Accelerometer

MICROMACHINES 2023年第10期14卷 1891-1891页

作者： Liu, Wen Zhao, Tianlong He, Zhiyuan Ye, Jingze Gong, Shaotong Wang, Xianglong Yang, Yintang Xidian Univ Sch Microelect Xian 710071 Peoples R China Shandong Univ State Key Lab Crystal Mat Jinan 250100 Peoples R China

In this research, a high-efficiency design method of the capacitive MEMS accelerometer is proposed. As the MEMS accelerometer has high precision and a compact structure, much research has been carried out, which mainly focused on the structural design and materials selection. To overcome the inconvenience and inaccuracy of the traditional design method, an orthogonal design and the particle swarm optimization (pso) algorithm are introduced to improve the design efficiency. The whole process includes a finite element method (FEM) simulation, high-efficiency design, and verification. Through the theoretical analysis, the working mechanism of capacitive MEMS accelerometer is clear. Based on the comparison among the sweep calculation results of these parameters in the FEM software, four representative structural parameters are selected for further study, and they are le, nf, lf and wPM, respectively. le and lf are the length of the sensing electrode and fixed electrode on the right. nf is the number of electrode pairs, and wPM is the width of the mass block. Then, in order to reduce computation, an orthogonal design is adopted and finally, 81 experimental groups are produced. Sensitivity SV and mass Ma are defined as evaluation parameters, and structural parameters of experimental groups are imported into the FEM software to obtain the corresponding calculation results. These simulation data are imported into neural networks with the pso algorithm. For a comprehensively accurate examination, three cases are used to verify our design method, and every case endows the performance parameters with different weights and expected values. The corresponding structural parameters of each case are given out after 24 iterations. Finally, the maximum calculation errors of SV and Ma are 1.2941% and 0.1335%, respectively, proving the feasibility of the high-efficiency design method.

关键词： capacitive MEMS accelerometer high-efficiency design method FEM orthogonal design pso algorithm

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Nondestructive characterization of elastic modulus under different tensile stresses through laser ultrasound combined inversion technique

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International Journal of Modern Physics B 2024年第4期38卷 2450059-2450059页

作者： Le Van, Nguyen Jeyaprakash, N. Yang, Che-Hua Department of Mechanical Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Industrial Education University of Technology Education-The University of Danang Danang City50000 Viet Nam Graduate Institute of Manufacturing Technology National Taipei University of Technology Taipei10608 Taiwan

Stainless steel (SS) is widely used in many fields including aeronautics, automobiles, marine and mechanical industries due to its outstanding feature such as good corrosion resistance and hardness. However, changes in material properties under stress, particularly changes in Young's modulus, result in the formation of cracks, a reduction in load-bearing capacity, and fatigue damage. So, the structural integrity needs to be evaluated based on a precise measurement of mechanical properties. In this study, Stainless Steel 304 (SS-304) is used as the base material and various tensile stresses are applied ranging from 0MPa to 100MPa with increment of 10MPa in each step. Nondestructive Laser Ultrasound Technique (LUT) has been used to characterize the elastic modulus under various tensile stresses. An inverse program was developed based on the Particle Swarm Optimization (pso) algorithms to determine material properties. Nonlinear Gauss fitting method was proposed and established the fitting equation and nonlinear curve for Young's modulus and residual stress. The outcome of this research shows that when tensile stress is applied, the mechanical properties decrease by shifting the dispersion curve and also it is evident that the dispersion curves move toward the high-frequency-thickness while increasing the tensile stress. When the tensile stress was increased from 0MPa to 100MPa, the value of Young's modulus decreased from 201.7GPa to 193.5GPa. Especially, the predominant changes were observed during 30-100MPa. This observation displays the bonding strength and binding energy between the atomics. Further, the proposed nonlinear Gauss fitting substantiated the experimental values and confirmed that the thickness accuracy is close to the inversion values, with an average difference of 4.32%. This research suggests a potential nondestructive method to determine the residual stress of a material by calculating the changes in the elastic modulus. © 2024 World Scientific Publ

关键词： Stainless steel laser ultrasound technique pso algorithm Young’s modulus Poisson ratio tensile stress

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A pso-based semi-analytical force prediction model for chamfered carbide tools considering different material flow state caused by edge geometry

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INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES 2020年第0期169卷 105329-000页

作者： Weng, Jian Zhuang, Kejia Hu, Cheng Ding, Han Wuhan Univ Technol Sch Mech & Elect Engn Hubei Digital Mfg Key Lab Wuhan 430070 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China

The prediction of force in metal cutting is essential when estimating tool wear, surface quality and energy consumption. As a significant characteristic in tool design, edge geometry results in more challenges in force modeling especially under the condition of cutting with chamfered insert. In this paper, a semi-analytical model is proposed to describe the effect of chamfered edge on cutting force considering multiple material flow state. In orthogonal cutting, shear effect is calculated based on the unequal division shear-zone model and Johnson-Cook's material constitutive law. Two kinds of chip-tool contact patterns are considered to discuss the effect of tool edge, chip flows on both chamfered edge and rake face when chamfer length is close to Uncut Chip Thickness (UCT), or chip flows only on chamfered edge when chamfer length is much larger than UCT. Edge force coefficients of chamfered edge are modeled as linear functions with respect to shear stress, chamfer length and chamfer angle. The variation of edge force with respect to edge geometry is studied through Finite Element Method (FEM) simulations. The modified force prediction model is established by introducing a factor S to describe the trend of edge effect with respect to the ratio of chamfer length to UCT. Finally, a modified force prediction model is presented and the constants in the model can be calibrated through a Particle Swarm Optimization (pso)-based algorithm. Experiments of orthogonal cutting AISI304 with different chamfered carbide inserts are performed to validate the correctness and feasibility of the proposed model. The experimental results show that this model is effective in predicting the cutting force components under the condition of different edge preparations and cutting parameters.

关键词： Semi-analytical mode Cutting force Chamfered tool pso algorithm

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Steel Moment-Resisting Frame Reliability via the Interval Analysis by FCM-pso Approach considering Various Uncertainties

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JOURNAL OF EARTHQUAKE ENGINEERING 2020年第1期24卷 109-128页

作者： Jough, Fooad Karimi Ghaleh Sensoy, Serhan Islamic Azad Univ Dept Civil Engn Sarab Branch Sarab Iran Eastern Mediterranean Univ Fac Engn Dept Civil Engn Famagusta North Cyprus Turkey

One important issue in compiling siesmic fragility curves is blending and incorporating uncertainties into the model under seismic conditions. Methods used in this regard are either approximate, costly and time-consuming. To address this, the optimized fuzzy method is used. To compile the fragility curve, epistemic and aleatory uncertainties have been incorporated in which model parameters are fuzzy values and FCM-pso method is used to estimate mean and standard deviation of fragility curve. The FCM-pso algorithm is trained using scenarios compiled via the IDA method. Results obtained from the full Monte Carlo method were used for verification. The method employed here is advantageous with regard to both accuracy and execution time.

关键词： pso algorithm Fuzzy Method Collapse Fragility Curve Epistemic Uncertainty Interval Analysis

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Determination of Soil Properties Affecting Soil Aggregate Tensile Strength in a Semiarid Region of Iran Using a Hybrid algorithm

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COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS 2021年第17期52卷 1981-1992页

作者： Hojjatnooghi, Fatemeh Shirani, Hossein Pazira, Ebrahim Besalatpour, Ali Asghar Torkashvand, Ali Mohammadi Islamic Azad Univ Dept Soil Sci Sci & Res Branch Tehran Iran Vali E Asr Univ Rafsanjan Coll Agr Dept Soil Sci Rafsanjan Iran

The present study was conducted to determine soil properties affecting soil aggregate stability in southeast Iran. For this purpose, 169 soil samples were collected at 0-20 cm depth, and some soil properties such as soil bulk density (BD), electrical conductivity (EC), calcium carbonate equivalent (CCE), and soil organic matter (OM) were determined. Subsequently, soil aggregate stability (as quantified by tensile strength (TS)) were determined using the indirect (Brazilian) method. Furthermore, soil properties affecting soil aggregate stability were determined using the Particle Swarm Optimization-Imperialist Competitive algorithm-Support Vector Regression (pso-ICA-SVR) hybrid algorithm, and after the sensitivity analysis, the importance of each selected property in terms of its impact on soil aggregate stability was recognized. The results indicated that OM, BD, EC, and dg (geometric mean particle diameter), in general, influence soil aggregate stability, and this selection was carefully made by the hybrid algorithm. Beside, after modeling using the features selected by the SVR method and performing the sensitivity analysis, BD and OM, among the selected properties, had the most significant effects on soil aggregate stability. In this study, the SVR method achieved greater accuracy in predicting the TS index compared to the Multiple-Linear Regression (MLR). The RMSE value (Root Mean Square Error) for the TS index using the MLR model was 30.77, while a lower RMSE value of 10.536 was observed for the SVR model.

关键词： Soil aggregate stability Brazilian method pso algorithm ICA algorithm SVR algorithm

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Tube inner wall defect detection method based on rotary scanning micro laser distance sensor

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MEASUREMENT SCIENCE AND TECHNOLOGY 2023年第12期34卷 125125-125125页

作者： An, Yang Liu, Xuxiang Pang, Ran Zhu, Xixin Wang, Xiaocen Qu, Zhigang Tianjin Univ Sci & Technol Coll Elect Informat & Automat 1038 Dagu Nanlu Tianjin 300222 Peoples R China Tianjin Univ Sci &Technol Adv Struct Integr Int Joint Res Ctr Tianjin Peoples R China Tianjin Univ State Key Lab Precis Measuring Technol & Instrumen 92 Weijin Rd Tianjin 300072 Peoples R China

In this paper, an inspection device to detect the inner wall defects of oil tubes is proposed, mainly consisting of a micro laser distance sensor and a stepper motor. When the inspection device moves along the axial direction inside the tube, the stepper motor drives the micro laser distance sensor to rotate and scan the inner wall of the tube so that the coordinate data of the 3D point cloud can be obtained. In order to obtain the pose transformation matrix for the laser distance sensor coordinate system with respect to the device flange coordinate system, a particle swarm optimization algorithm is introduced. Finally, experiments are carried out on two real oil tubes and point cloud data are obtained which provide 3D information about the inner walls of the tubes. The measuring error of tube eccentric wear is within 0.2 mm, which verifies the effectiveness of this novel method.

关键词： rotary scanning device oil tube eccentric wear detection pso algorithm 3D coordinate demonstration small measuring error

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Applying an improved particle swarm optimization algorithm to ship energy saving

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ENERGY 2023年第PartE期263卷

作者： Du, Wei Li, Yanjun Shi, Jianxin Sun, Baozhi Wang, Chunhui Zhu, Baitong Harbin Engn Univ Coll Power & Energy Engn Harbin 150001 Heilongjiang Peoples R China Harbin Engn Univ Coll Shipbuilding Engn Harbin 150001 Heilongjiang Peoples R China

Due to the increasingly competitive maritime market and stringent regulatory requirements, the optimization of ship energy efficiency is attracting more and more attention. The energy efficiency of ship navigation is affected by many factors such as ship structure, crew operation and navigation environment. In this paper, the proposed improved second-order oscillating pso algorithm is used to study the ship energy efficiency from the viewpoint of route optimization by considering the sea conditions and constraints. Firstly, a nonlinear optimization model for ship FOC (fuel oil consumption) considering the time-varying sea state is established. On this basis, the energy efficiency and economic benefits are analyzed in terms of multiple indicators e.g., FOC and CO2 emissions per unit distance and per unit mass of freight. Finally, the energy saving potential of the method is demonstrated with an example of an oil tanker. The results show that both FOC and emissions are reduced after optimization, and energy efficiency and economy are improved by 1.17% and 2.55%, respectively. This indicated that the considerable effect of the proposed method applied to ship energy saving optimization.

关键词： Ship energy saving pso algorithm Weather conditions Energy efficiency index

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Optimal allocation of reliability improvement target based on multiple correlation failures and risk uncertainty

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EKSPLOATACJA I NIEZAWODNOSC-MAINTENANCE AND RELIABILITY 2023年第1期25卷

作者： Jia, Shuoguo Yan, Changfeng Kang, Jianxiong Xie, Heping Wei, Yongqiao Lanzhou Univ Technol Sch Mech & Elect Engn Lanzhou 730050 Peoples R China Xuzhou XCMG Min Machinery Co Ltd Xuzhou 221000 Jiangsu Peoples R China

Optimal allocation of the reliability improvement target is essential for the system optimization design. In order to solve the problems that the optimization model is with loss of generality and the validity of the optimal solution is weakened, an optimal allocation method is proposed by considering multiple correlation failures and risk uncertainty in this paper. Two new concepts are presented, such as independent failure results in basic risk, and correlation failure leads to disturbance risk. A risk assessment machinery of "actual risk = basic risk + disturbance risk" is proposed. The action mechanisms of the three correlation failures are studied based on the cooperation game theory, and the generalized risk models are given under probability measure. Considering the improvement cost, the expectation and the variance of the reduction of system risk, a multi-objective optimal allocation model is developed, which is solved by using the pso algorithm. Finally, the proposed optimal allocation is implemented at the 2- stage NGW planetary reducer, and the results show that it is more efficient and feasible for engineering practice.

关键词： Multi-objective optimal allocation reliability improvement correlation failure risk uncertainty probability measure cooperation game theory pso algorithm

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Optimal sizing of stand-alone hybrid photovoltaic/wind system using BAT algorithm

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INTERNATIONAL JOURNAL OF AMBIENT ENERGY 2021年第8期42卷 920-928页

作者： Marsa, Nadia Houcine, Lassad Zaafouri, Abdurrahman Chaari, Abdelkader Univ Tunisia Lab Engn Ind Syst & Renewable Energies LISIER ENSIT Tunis Tunisia Univ Tunis Natl Higher Engn Sch Tunis ENSIT Tunis Tunisia

This paper presents a new optimal sizing methodology for a stand-alone PV-wind hybrid (PWH) energy system that is serving the electricity demand for an offshore petroleum platform. A BAT optimisation technique is implemented to minimise the annualised cost of the system (ACS) considering power balance constraint and to determine the optimal number of PV panels, wind turbines and batteries. The comparison of BAT algorithm with Homer and particle swarm optimisation algorithm is done in this paper and it shows that BAT algorithm finds optimal sizing of PWH easily with lower cost. The results show that considering reliability characteristics has a major impact on optimal sizing, load supply level and cost.

关键词： BAT algorithm pso algorithm Homer photovoltaic energy wind energy

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Face recognition algorithm based on particle swarm optimization and image feature compensation

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SOFTWAREX 2023年 22卷

作者： Zhang, Yanhu Yan, Lijuan Guangdong Songshan Polytech Shaoguan 512126 Guangdong Peoples R China

In order to improve face recognition accuracy, an IFC face recognition algorithm based on image feature compensation strategy for face recognition is proposed in this paper. The strategy adopts the method of extracting the image feature description by using the computational factors to compensate the features of the original image. Since the size of the feature compensation coefficients directly affects the recognition rate of the face recognition system, a modified pso algorithm is proposed for solving the optimal combination of feature compensation coefficients for multiple computation factors, so that the recognition rate of the system can be improved. Firstly, this paper introduces the relative concepts of feature compensation strategy and calculation factor. Secondly, the process and implementation of face recognition algorithm using feature compensation strategy are described. Thirdly, the improved pso algorithm for solving the optimal solution of the feature compensation coefficient is designed, during which the evaluation method is constructed to evaluate the merits of the feature compensation coefficient, and the implementation process of the improved pso algorithm is conceived. Finally, the algorithm proposed in this paper is verified by simulation experiment platform. It is demonstrated that the modified pso algorithm can significantly enhance the recognition rate of the system following its application to the feature compensation strategy face recognition system. On the ORL dataset, the recognition rate can be enhanced from 93.05% to 99.00% when the training image reaches 5, meanwhile, it still exhibits good performance on other datasets. (c) 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Image feature compensation Face recognition Compensation coefficient pso algorithm Image recognition

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