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Research experimental on surface integrity and parameters optimization of micro-milling dual-phase titanium alloy

SURFACE TOPOGRAPHY-METROLOGY AND PROPERTIES 2025年第1期13卷

作者： Zhao, Haiyue Cao, Yan Gorbachev, Sergey Kuzin, Victor Du, Jiang He, Weiliang Xian Technol Univ Sch Mech & Elect Engn 2 Xuefu Middle Rd Xian 710021 Shaanxi Peoples R China Xian Technol Univ Sch Comp Sci & Engn 2 Xuefu Middle Rd Xian 710021 Shaanxi Peoples R China Chongqing Univ Educ Sch Artificial Intelligence Chongjiao RdNanshan St Chongqing 400065 Peoples R China Russian Acad Engn 9 Bldg 4Gazetny Pereulok Moscow 125009 Russia Dept Aeronaut Engn Xianyang 712000 Shaanxi Provinc Peoples R China

As the application of dual-phase polycrystalline materials in micro-components expands, the surface integrity evaluation criteria developed for macro-scale machining are become insufficient. To investigate the effects of cutting parameters on surface integrity at the micro-scale, a typical dual-phase titanium alloy was selected as the subject for micro-milling. First, a physical experimental platform for micro-milling was established. Subsequently, a single-factor experimental method was employed to analyze the effects of cutting parameters on the micro-morphology, surface roughness, and micro-hardness of the processed dual-phase titanium alloy. Following this, orthogonal experimental range analysis and response surface variance analysis were conducted to evaluate the significance of cutting parameters on the target factors. Finally, cutting parameters were optimized using the signal-to-noise ratio method and response surface methodology, followed by physical experimental validation. Results reveal that feed per tooth significantly influences surface roughness, while cutting depth least. In contrast, spindle speed is the primary factor affecting micro-hardness, with feed per tooth having minimal effect. Optimal parameters minimize both surface roughness and micro-hardness, with experimental and theoretical values differing by no more than 5%. The findings provide both theoretical and experimental support for the surface integrity and parameters optimization of dual-phase alloys in micro-machining.

关键词： micro-milling dual-phase titanium alloy surface integrity parameters optimization

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In-plane compression properties and parameters optimization of a lightweight and high-strength bamboo honeycomb sandwich material

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COMPOSITES SCIENCE AND TECHNOLOGY 2025年 261卷

作者： Yu, Minggong Wang, Zhangheng Jiang, Xiawang Wang, Di Song, Ling Zhao, Shan Liu, Jingyi Sun, Delin Cent South Univ Forestry & Technol Coll Mat Sci & Engn Changsha 410004 Hunan Peoples R China

Bamboo is a green and sustainable structural material. A new bamboo honeycomb sandwich material (BHSM) was designed and prepared with the bamboo integrated material as panel and the hexagonal bamboo honeycomb core (HBHC) as core layer, and its in-plane compression properties is analyzed using analytical approach, finite element method and response surface method and verified experimentally. The results show that better in-plane compression properties are achieved when the rho*/rho of HBHC of BHSM is higher than 0.155. The optimum compressive properties were achieved when the rho*/rho of HBHC was 0.25, the tf/T was 0.24, and the H/L was 0.19. Under this condition, the stress of the BHSM was 12.62 MPa, which was in error with the prediction model of 9.17 %. Furthermore, the in-plane compression properties of BHSM at optimal structural parameters were better than those of some metals and alloys, and it was 2-5 times that of ordinary carbon fiber polymers and their reinforcements. This work shows that BHSM is a promising green, sustainable, lightweight and high-strength structural material. BHSM can be used in areas such as construction materials, packaging materials and furniture products.

关键词： Bamboo Honeycomb sandwich material In-plane compression Finite element method parameters optimization

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parameters optimization and nonlinearity analysis of grating eddy current displacement sensor using neural network and genetic algorithm

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2009年第8期10卷 1205-1212页

作者： Hong-li QI Hui ZHAO Wei-wen LIU Hai-bo ZHANG Department of Instrument Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China Instrumentation Science and Dynamic Measurement Laboratory North University of China Taiyuan 030051 China

A grating eddy current displacement sensor(GECDS) can be used in a watertight electronic transducer to realize long range displacement or position measurement with high accuracy in difficult industry *** parameters optimization of the sensor is essential for economic and efficient *** paper proposes a method to combine an artificial neural network(ANN) and a genetic algorithm(GA) for the sensor parameters optimization.A neural network model is developed to map the complex relationship between design parameters and the nonlinearity error of the GECDS,and then a GA is used in the optimization process to determine the design parameter values,resulting in a desired minimal nonlinearity error of about 0.11%.The calculated nonlinearity error is 0.25%.These results show that the proposed method performs well for the parameters optimization of the GECDS.

关键词： Grating eddy current displacement sensor (GECDS) Artificial neural network (ANN) Genetic algorithm (GA) parameters optimization Nonlinearity error

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parameters optimization of nanopatterned sapphire substrates for enhancing light extraction efficiency of GaN-based LEDs

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OPTICS COMMUNICATIONS 2020年第0期464卷 125548-000页

作者： Zhang, Pengcheng Wen, Qiuling Xu, Xipeng Huaqiao Univ Inst Mfg Engn Xiamen 361021 Peoples R China Xiamen Key Lab Photoelect Mat Machining Xiamen 361021 Fujian Peoples R China

The nanopatterned structures play an important role in enhancing the light extraction efficiency (LEE) of GaN-based light-emitting diodes (LEDs). Three-dimensional finite-difference time-domain (3D-FDTD) method was carried out to calculate the LEE enhancement of GaN-based LEDs designed on periodic nanostructures with different geometries. Orthogonal experiment method was employed to obtain the optimal structure parameters and analyze the weighting factor of critical parameters affecting the LEE enhancement. The results of orthogonal experiment showed that the height/depth of the periodic nanostructures is the dominated factor to influence the LEE enhancement, followed by the diameter and the spacing of the periodic nanostructures. It was also found that the far-field intensities of LEDs with periodic convex nanostructures were stronger than those with periodic concave nanostructures. The critical parameters of periodic convex nanostructures were further optimized by single factor method, and their optimal parameters were obtained. The optimal LEE enhancement of GaN-based LEDs grown on cone-shaped nanopillar and column-shaped nanopillar array patterned sapphire substrates are 1.95 and 1.97, respectively. This means the cone-shaped and column-shaped nanopillar structures have almost identical LEE enhancement of GaN-based LEDs.

关键词： parameters optimization Nanopatterned sapphire substrates Light extraction efficiency GaN-based light-emitting diodes Orthogonal experiment method

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parameters optimization considering the trade-off between cutting power and MRR based on Linear Decreasing Particle Swarm Algorithm in milling

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JOURNAL OF CLEANER PRODUCTION 2020年 262卷 121388-121388页

作者： Han, Fujun Li, Li Cai, Wei Li, Congbo Deng, Xingguo Sutherland, John W. Southwest Univ Coll Engn & Technol Chongqing 400715 Peoples R China Chongqing Univ State Key Lab Mech Transmiss Chongqing 400044 Peoples R China Chongqing Three Gorges Univ Coll Mech Engn Chongqing 404130 Peoples R China Purdue Univ Environm & Ecol Engn W Lafayette IN 47906 USA

As mechanical engineering is growing a current and urgent issue is rising in the manufacturing process, which is the ability to improve efficiency while reducing energy consumption during the processes. Cutting parameters are an important part of the computer numerical control (CNC) machining process, so a reasonable selection of cutting parameters can significantly enhance the machine's energy efficiency. Previous studies mainly focused on cutting power (P) and material removal rate (MRR), respectively, without considering the trade-off relationship between them;In this paper, an optimization model of cutting parameters is developed by establishing a multi-objective model where P and MRR are identified. The proposed model utilizes the Grey Correlation Analysis (GRA) and experimental to determine the weight of the objective. After the Linear Decreasing Particle Swarm (LDPS) optimization algorithm was utilized to solve the model, several application cases are given and their results demonstrate the ability of our method through comparing with the traditional approach. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： parameters optimization Energy efficiency Grey correlation analysis Linear decreasing particle swarm algorithm Energy consumption

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parameters optimization of ASE Source for the Improvement of Optical Power Stability in Space Radiation Environment

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JOURNAL OF LIGHTWAVE TECHNOLOGY 2022年第8期40卷 2612-2618页

作者： Tan, Shen Li, Yan Wang, Xiaowei Jin, Zhizhong Zhang, Haoshi Jin, Jing Beihang Univ Sch Instrument Sci & Opt Elect Engn Beijing 100191 Peoples R China

A parameter optimization model of amplified spontaneous emission (ASE) source in space radiation environment has been developed based on the ASE source model and the radiation-induced attenuation (RIA) model of erbium-doped fiber (EDF). The RIA model considers color center generation and annealing process at the same time. Using the radiation attenuation and recovery spectra obtained at the dose rate of 30 Gy/min, the color center generation and recovery parameters in the EDF are obtained. Based on the ASE source model, the parameter optimization model at the high dose rate of 30 Gy/min is established. Then, the model is successfully extrapolated to a small dose rate of 0.06 Gy/min. These effects of the spectral shape, pump power, and fiber length on the output power stability of the ASE source are investigated using this model at the dose of 0.06 Gy/min. Finally, the experiment is performed to evaluate the simulation, and it is suggested that the output power fluctuation of the optimized ASE source is less than 3% within the radiation dose range of 300 Gy.

关键词： Color Absorption Image color analysis optimization Mathematical models Fitting Optical pumping ASE source parameters optimization power fluctuation RIA model

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parameters optimization for eutrophic lake water treatment by a novel process of iron-carbon micro-electrolysis coupled with catalytic ozonation using response surface methodology

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WATER SUPPLY 2021年第5期21卷 2414-2424页

作者： Jiang, Shanqing Cao, Yu Han, Pei Zhang, Yanan Zhang, Hankun Zhang, Qiuya Xu, Xia Zhou, Yuanyuan Wang, Liping Changzhou Univ Sch Environm & Safety Engn Changzhou 213164 Peoples R China Suntime Environm Remediat Co Ltd Changzhou 213000 Peoples R China

A novel process of iron-carbon micro-electrolysis (ICME) coupled with catalytic ozonation (CO) for treatment of eutrophic lake water was developed. A series of batch experiments with ICME alone and CO alone was designed to investigate the effects of process parameters, such as initial pH, dose of Fe-C, time of micro-electrolysis, ozone flux, dose of TiO2/activated carbon (TiO2/AC), and time of ozonation, on the removal rates of total nitrogen (TN), total phosphorus (TP), CODMn and Chl-a. The process parameters were optimized using response surface methodology. The results showed that initial pH, dose of Fe-C and ozone flux had significant effects on removal of TN, TP, CODMn and Chl-a. Within the range of selected operating conditions, the optimized values of initial pH, dose of Fe-C, time of micro-electrolysis, ozone flux, dose of TiO2/AC, and time of ozonation were 3.8, 13.7 g/L, 29.6 min, 3.19 L/min, 294.74 mg/L and 106.73 min, respectively. Furthermore, ICME alone had significant advantages in TP and CODMn removal and CO alone favored TN and Chl-a. Under the optimal process conditions, the final removal rates of TN, TP, CODMn, and Chl-a by the hybrid ICME-CO process reached 75.33%, 86.29%, 94.42% and 97.57%, respectively. The present research provides a new alternative technology with promise for treatment of eutrophic lake water.

关键词： catalytic ozone eutrophic lake water iron-carbon micro-electrolysis parameters optimization response surface methodology

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parameters optimization for wavelet denoising based on normalized spectral angle and threshold constraint machine learning

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JOURNAL OF APPLIED REMOTE SENSING 2012年第1期6卷 063579-1-063579-9页

作者： Li, Hao Ma, Yong Liang, Kun Tian, Yong Wang, Rui Huazhong Univ Sci & Technol Dept Elect & Informat Engn Wuhan 430074 Peoples R China

Wavelet parameters (e. g., wavelet type, level of decomposition) affect the performance of the wavelet denoising algorithm in hyperspectral applications. Current studies select the best wavelet parameters for a single spectral curve by comparing similarity criteria such as spectral angle (SA). However, the method to find the best parameters for a spectral library that contains multiple spectra has not been studied. In this paper, a criterion named normalized spectral angle (NSA) is proposed. By comparing NSA, the best combination of parameters for a spectral library can be selected. Moreover, a fast algorithm based on threshold constraint and machine learning is developed to reduce the time of a full search. After several iterations of learning, the combination of parameters that constantly surpasses a threshold is selected. The experiments proved that by using the NSA criterion, the SA values decreased significantly, and the fast algorithm could save 80% time consumption, while the denoising performance was not obviously impaired. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/***.6.063579]

关键词： hyperspectral wavelet denoising parameters optimization machine learning

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parameters optimization design for LCL-type STATCOMs under complex power grid

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JOURNAL OF POWER ELECTRONICS 2020年第2期20卷 566-579页

作者： Wang, Xiangyu Wang, Minglei Wang, Liguo Fu, Guangjie Qiao, Jinxin Harbin Inst Technol Sch Elect Engn & Automat Harbin Peoples R China Northeast Petr Univ Sch Elect Engn & Informat Daqing Peoples R China

LCL filter parameters and control parameters are interdependent and inter-restricted. They can all affect the stability of a static synchronous compensator (STATCOM) under the effects of a complex power grid such as harmonic grid voltage and grid impedance variation. An advanced parameters optimization method integrated with LCL filter and control strategy is proposed. At first, the ABC-Pareto algorithm (Pareto multi-objective optimization of an artificial bee colony algorithm) is used to reasonably choose the LCL filter parameters. Under the premise of using capacitor current feedback active damping control and grid voltage feedforward control, the mathematical models of the STATCOM are derived. The constraints of control performances on the control parameters are obtained. According to these constraints, it is possible to construct a satisfactory 3D space. The control parameters can be chosen reasonably by finding the optimized space when the power grid is changed. Simulation and experimental results show the effectiveness and superiority of the proposed method.

关键词： ABC-Pareto algorithm Complex power grid LCL-type STATCOM parameters optimization

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parameters optimization of polygonal fuzzy neural networks based on GA-BP hybrid algorithm

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INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS 2014年第5期5卷 815-822页

作者： Yang, Yongqiang Wang, Guijun Yang, Yang Tianjin Normal Univ Sch Math Sci Tianjin 300387 Peoples R China

Based on the extensive operations of polygonal fuzzy numbers, a GA-BP hybrid algorithm for polygonal fuzzy neural network is designed. Firstly, an optimal solution is obtained by the global searching ability of GA algorithm for the untrained polygonal fuzzy neural network. Secondly, some parameters for connection weights and threshold values are appropriately optimized by using an improved BP algorithm. Finally, through a simulation example, we demonstrate that the GA-BP hybrid algorithm based on the polygonal fuzzy neural network can not only avoid the initial values' dependence and local convergence of the original BP algorithm, but also overcome a blindness problem of the traditional GA algorithm.

关键词： Polygonal fuzzy numbers Polygonal fuzzy neural network GA-BP hybrid algorithm parameters optimization

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