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学者姓名：顾天奇
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Abstract ：
现有挖掘机主构件参数优化设计方法无法保证挖掘作业全过程多工况位置工作性能最优,且没有考虑作业过程中的能耗特性.研究了以典型工况作业全过程动力和能耗特性为目标的挖掘机工作装置主构件参数多目标优化设计方法.通过对基于ADAMS的参数化挖掘机虚拟样机的动力学仿真,分析了四种典型工况作业过程的液压缸驱动力和功率特性,确定了工作装置的优化工况,建立了新的综合考虑挖掘机典型工况作业过程液压缸驱动力传动比和功率特性的多目标优化数学模型,并结合实例对挖掘机整机工作装置参数化虚拟样机的铲斗、斗杆和动臂主构件参数进行顺序多目标优化.优化结果表明:该优化设计方法可显著提高挖掘机作业全过程工作装置传递动力的性能,降低液压缸能耗.
Keyword ：
主构件参数 主构件参数 多目标优化 多目标优化 挖掘机 挖掘机 虚拟样机 虚拟样机 过程特性 过程特性 顺序优化 顺序优化
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| GB/T 7714 | 林述温 , 陆哲 , 危世佳 et al. 挖掘机工作过程动力特性仿真及主构件参数多目标优化设计方法 [J]. | 中国机械工程 , 2025 , 36 (6) : 1371-1379 . |
| MLA | 林述温 et al. "挖掘机工作过程动力特性仿真及主构件参数多目标优化设计方法" . | 中国机械工程 36 . 6 (2025) : 1371-1379 . |
| APA | 林述温 , 陆哲 , 危世佳 , 陈剑雄 , 顾天奇 , 谢钰 . 挖掘机工作过程动力特性仿真及主构件参数多目标优化设计方法 . | 中国机械工程 , 2025 , 36 (6) , 1371-1379 . |
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In recent decades, metasurfaces have shown remarkable advancements in the development of integrated and miniaturized optical devices. Among these, metalenses have emerged as a prominent and significant area of research. In this paper, a broadband achromatic metalens is designed to operate across a wide wavelength range, specifically from 9.6 mu m to 11.6 mu m. To efficiently achieve the optimization of initial metalens parameters, we employ an envelope-based layering strategy that divides the sample space into multiple adjacent floors. This approach effectively reduces the loss rate and computational burden in a comprehensive manner. An enhanced Archimedes optimization algorithm is utilized to obtain the optimal solution. It incorporates the oppositionbased learning with Sine map and elite retention strategy to enhance the search capability and avoid getting trapped in local optima. Following the optimization process, the proposed metalens achieves an average focusing efficiency of 53.64 %, with chromatic aberration correction accomplished at a coefficient of variation of only 2.27 %. This accomplishment signifies a substantial advancement in the field of achromatic metalenses.
Keyword ：
Achromatic metalens Achromatic metalens Long-wavelength infrared Long-wavelength infrared Optimization design Optimization design PB phase PB phase
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| GB/T 7714 | Gu, Tianqi , Zhang, Yihao , Cai, Hangbin et al. High-performance achromatic metalens in the long-wavelength infrared regime [J]. | PHYSICS LETTERS A , 2025 , 542 . |
| MLA | Gu, Tianqi et al. "High-performance achromatic metalens in the long-wavelength infrared regime" . | PHYSICS LETTERS A 542 (2025) . |
| APA | Gu, Tianqi , Zhang, Yihao , Cai, Hangbin , Tang, Dawei . High-performance achromatic metalens in the long-wavelength infrared regime . | PHYSICS LETTERS A , 2025 , 542 . |
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Abstract ：
Over recent decades, metasurfaces have achieved significant advancements in the development of integrated and miniaturized optical devices. A notable area of research within this field is the development of metalenses. In this study, we propose a broadband achromatic metalens that operates across a wide wavelength range from 9.6 mu m to 11.6 mu m. For the initial metalens, based on the geometric phase principle, micro adjustments are made to the dimensions of individual nanopillars to compensate for phase deviations. To efficiently optimize this metalens, we employ a hierarchical iteration strategy that divides the optimization space into overlapping groups, significantly reducing the loss rate and computational effort. Within each group, an improved reptile search algorithm (IRSA) is proposed to find the optimal solution. This algorithm incorporates a quantum mutation strategy to address the issues of premature convergence and imbalance during its search process. The results indicate that the proposed metalens attains an average focusing efficiency of 39.7% and the correction of chromatic aberration is achieved with a coefficient of variation of only 2.7%. This achievement represents a significant advancement in the field of achromatic metalenses.
Keyword ：
Chromatic aberration Chromatic aberration Dielectric metalens Dielectric metalens Geometric phase Geometric phase Long-wavelength infrared Long-wavelength infrared
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| GB/T 7714 | Gu, Tianqi , Zhang, Yihao , Tang, Dawei et al. An all-dielectric achromatic metalens with high performance in the long-wavelength infrared regime [J]. | OPTICS COMMUNICATIONS , 2025 , 582 . |
| MLA | Gu, Tianqi et al. "An all-dielectric achromatic metalens with high performance in the long-wavelength infrared regime" . | OPTICS COMMUNICATIONS 582 (2025) . |
| APA | Gu, Tianqi , Zhang, Yihao , Tang, Dawei , Fang, Bing . An all-dielectric achromatic metalens with high performance in the long-wavelength infrared regime . | OPTICS COMMUNICATIONS , 2025 , 582 . |
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Due to the high accuracy of computation, radial basis function (RBF) is widely recognized as a versatile and effective method for interpolating and approximating discrete points in various fields. However, RBF is quite sensitive to outliers, which can easily lead to distorted results. In this article, a novel overlapped domain-based RBF (ODRBF) method is proposed, in which the concept of effective domain is introduced to build a moving model, and Student's t-regression and Gaussian mixture model (GMM) clustering are used for dealing with local anomalies. By introducing the effective domain, the estimated points and domain radius are constructed and the global model can be transformed into local estimation models. In each effective domain, a series of estimation models are iteratively generated through Student's t-regression, and based on the distances between the estimation model and discrete points, GMM clustering is used to subsequently select the data as the input of the next regression. This iterative strategy in each effective domain ensures the removal of multiple outliers. Then, the preserved points in the processed effective domain are used to obtain local estimated value by RBF. The proposed method demonstrates strong robustness to highly contaminated dataset in the reconstruction of the simulation and experimental datasets.
Keyword ：
Effective domain Effective domain Gaussian mixture model clustering Gaussian mixture model clustering Radial basis function Radial basis function Student 's t -distribution Student 's t -distribution
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| GB/T 7714 | Gu, Tianqi , Wang, Jun , Tang, Dawei et al. Reconstruction of measurement data with multiple outliers using novel domain-based RBF [J]. | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2024 , 214 . |
| MLA | Gu, Tianqi et al. "Reconstruction of measurement data with multiple outliers using novel domain-based RBF" . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING 214 (2024) . |
| APA | Gu, Tianqi , Wang, Jun , Tang, Dawei , Wang, Jian , Guo, Tong . Reconstruction of measurement data with multiple outliers using novel domain-based RBF . | MECHANICAL SYSTEMS AND SIGNAL PROCESSING , 2024 , 214 . |
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Metalenses have attracted a great deal of research interests due to the property of light controllability. How to enhance the focusing effect of metalens has always been a key problem that many researchers have been working on. In this paper, we propose a novel sub-dimensional resonance-based optimization method for dielectric metalens with golden angle spiral arrays. The waveguiding effect is first applied to the initial design of the quasiperiodic metalens through the defined equivalent period. Then the genetic algorithm is improved for adjusting the sub-dimensional structure of the initial metalens. The optimization results show that the peak intensity of central hot spot increases by 32 % while keeping the full width at half maximum (FWHM) almost unchanged. At the same time, the field intensity of side lobes around the hot spot decreases, which means that a potential way for high-contrast imaging is provided.
Keyword ：
Dielectric metalens Dielectric metalens Genetic algorithm Genetic algorithm Golden angle spiral Golden angle spiral High-contrast imaging High-contrast imaging Quasi-periodic arrays Quasi-periodic arrays
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| GB/T 7714 | Gu, Tianqi , Guo, Ziming , Tang, Dawei et al. Design and optimization of dielectric metalens with quasi-periodic arrays [J]. | OPTICAL MATERIALS , 2024 , 148 . |
| MLA | Gu, Tianqi et al. "Design and optimization of dielectric metalens with quasi-periodic arrays" . | OPTICAL MATERIALS 148 (2024) . |
| APA | Gu, Tianqi , Guo, Ziming , Tang, Dawei , Luo, Tianzhi . Design and optimization of dielectric metalens with quasi-periodic arrays . | OPTICAL MATERIALS , 2024 , 148 . |
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To enhance the excavator performance considering the digging force and boom lift force under typical working conditions, this paper aims to solve the complex multiobjective optimization of the excavator by proposing a new knowledge-based method. The digging force at multiple key points is utilized to characterize the excavator's performance during the working process. Then, a new optimization model is developed to address the imbalanced optimization quality among subobjectives obtained from the ordinary linear weighted model. The new model incorporates the loss degree relative to the optimal solution of each subobjective, aiming to achieve a more balanced optimization. Knowledge engineering is integrated into the optimization process to improve the optimization quality, utilizing a knowledge base incorporating seven different types of knowledge to store and reuse the information related to optimization. Furthermore, a knowledge-based multiobjective algorithm is proposed to perform the knowledge-guided optimization. Experimental results demonstrate that the proposed knowledge-based method outperforms existing methods, resulting in an average increase of 15.1% in subobjective values.
Keyword ：
excavator excavator knowledge engineering knowledge engineering multiobjective evolutionary algorithm multiobjective evolutionary algorithm multiobjective optimization multiobjective optimization Optimization design Optimization design
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| GB/T 7714 | Lu, Zhe , Lin, Shuwen , Chen, Jianxiong et al. A multi-objective collaborative optimization method for excavator working devices based on knowledge engineering [J]. | ADVANCES IN MECHANICAL ENGINEERING , 2024 , 16 (1) . |
| MLA | Lu, Zhe et al. "A multi-objective collaborative optimization method for excavator working devices based on knowledge engineering" . | ADVANCES IN MECHANICAL ENGINEERING 16 . 1 (2024) . |
| APA | Lu, Zhe , Lin, Shuwen , Chen, Jianxiong , Gu, Tianqi , Xie, Yu , Zhao, Zihao . A multi-objective collaborative optimization method for excavator working devices based on knowledge engineering . | ADVANCES IN MECHANICAL ENGINEERING , 2024 , 16 (1) . |
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The characteristic parameters, such as curvature radius of asperity, height distribution, and asperity density play a decisive role when studying the contact characteristics of rough surfaces. A new method of asperity definition based on curve fitting and peak refit, named the deterministic method, is proposed in this paper. The real topography of the rough surface is described by the moving least-squares method. And the local maximum of the curve is defined as the asperity, and the local minimum is defined as the valley. To improve the stability of characteristic parameters of the rough surfaces, this method regenerates a new asperity when the asperities are gathered too closely. Both the characteristic parameters obtained by the deterministic method and the spectral moment method are used in two typical elastic-elastoplastic-plastic contact models, to analyze the contact characteristics of rough surfaces. Numerical calculation results show that, compared to the spectral moment method, the deterministic method demonstrates greater consistency across different sampling intervals, indicating lower sensitivity to sampling interval variations. This improves the accuracy and stability of contact performance parameters, validating the effectiveness of the proposed method, which can serve as a feasible approach for analyzing fine contact on rough surfaces.
Keyword ：
Contact model Contact model Rough surfaces Rough surfaces Sampling interval Sampling interval The deterministic method The deterministic method
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| GB/T 7714 | Fang, Bing , Huang, Weibin , Luo, Yusheng et al. Quantitative Characterization of Surface Topography Using an Improved Deterministic Method [J]. | TRIBOLOGY LETTERS , 2024 , 72 (4) . |
| MLA | Fang, Bing et al. "Quantitative Characterization of Surface Topography Using an Improved Deterministic Method" . | TRIBOLOGY LETTERS 72 . 4 (2024) . |
| APA | Fang, Bing , Huang, Weibin , Luo, Yusheng , Xie, Limin , Gu, Tianqi . Quantitative Characterization of Surface Topography Using an Improved Deterministic Method . | TRIBOLOGY LETTERS , 2024 , 72 (4) . |
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Due to its capacity to depict intricate geometric shapes and topological structures, moving total least squares (MTLS) method has garnered considerable attention from a diverse spectrum of researchers, finding extensive utility in the domain of reverse engineering. Nonetheless, the utilization of MTLS becomes impractical when dealing with datasets containing outliers. Drawing inspiration from the construction principle of MTLS, a regionally asymptotic moving total least squares (RAMTLS) approach is proposed to achieve robust reconstruction of highly polluted measurement dataset, in which the Bayesian estimation and density-based spatial clustering of applications with noise (DBSCAN) are used for outlier detection. In contrast to the conventional method, the proposed approach employs a step-by-step iterative strategy to mitigate the adverse impact of outliers. Within this framework, Student-t distribution-based estimation with non-prior information is used to pre-fit the data within the support domain, followed by clustering the acquired absolute residuals. Upon the completion of the regression-clustering iteration, a weighted Bayesian estimation is further applied to the remaining data to ascertain the ultimate estimated value. Compared with existing competitive methods, the simulations and experiments emphasize the effectiveness and reliability of the proposed reconstruction method.
Keyword ：
Bayesian estimation Bayesian estimation DBSCAN clustering DBSCAN clustering Moving total least squares Moving total least squares Surface reconstruction Surface reconstruction
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| GB/T 7714 | Gu, Tianqi , Wang, Jun , Tang, Dawei et al. A novel reconstruction method with robustness for polluted measurement dataset [J]. | ADVANCED ENGINEERING INFORMATICS , 2024 , 62 . |
| MLA | Gu, Tianqi et al. "A novel reconstruction method with robustness for polluted measurement dataset" . | ADVANCED ENGINEERING INFORMATICS 62 (2024) . |
| APA | Gu, Tianqi , Wang, Jun , Tang, Dawei , Wang, Jian , Jiang, Xiangqian . A novel reconstruction method with robustness for polluted measurement dataset . | ADVANCED ENGINEERING INFORMATICS , 2024 , 62 . |
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Due to their good approximation accuracy and local fitting characteristics, the moving least squares (MLS) and moving total least squares (MTLS) methods are widely used in various engineering fields. However, neither of these two methods is robust and they cannot effectively deal with outliers in measurement data. To eliminate the negative influence of outliers and achieve robust reconstruction, a novel MTLS method is proposed in this paper, which introduces local Bayesian estimation combined with clustering using representatives (CURE) algorithm. In the support domain, this method adopts a two-step process to remove the abnormal points and adjust the weights of discrete points through compound weighting. Bayesian estimation is first performed on discrete points to derive the reference model, and the residuals are calculated as the input of CURE clustering. The points with large residuals are classified into one cluster and removed. The remaining points undergo repeated processing until the iteration concludes. A gradient weight function based on the residuals and a compact support weight function are combined to determine the final estimated value using weighted Bayesian estimation. The simulations and experiments demonstrate that the proposed reconstruction method achieves excellent accuracy and robustness, surpassing several existing methods when handling highly contaminated datasets.
Keyword ：
Bayesian estimation Bayesian estimation Clustering using representatives Clustering using representatives Measurement data Measurement data Moving total least squares Moving total least squares Outliers Outliers
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| GB/T 7714 | Gu, Tianqi , Kang, Cheng , Tang, Dawei et al. A robust reconstruction method based on local Bayesian estimation combined with CURE clustering [J]. | INFORMATION SCIENCES , 2024 , 680 . |
| MLA | Gu, Tianqi et al. "A robust reconstruction method based on local Bayesian estimation combined with CURE clustering" . | INFORMATION SCIENCES 680 (2024) . |
| APA | Gu, Tianqi , Kang, Cheng , Tang, Dawei , Lin, Shuwen , Luo, Tianzhi . A robust reconstruction method based on local Bayesian estimation combined with CURE clustering . | INFORMATION SCIENCES , 2024 , 680 . |
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To address the limitation of existing excavator optimization methods, which primarily focus on the force performance while neglecting energy consumption and fail to realize environmentally friendly and low-carbon designs, this paper proposes a new multi-objective collaborative optimization method for an excavator to reduce energy consumption during the working process while maintaining optimal performance. By formulating a mathematical model that quantifies the energy consumption during the working process, this paper optimizes the working conditions by analyzing the energy consumption characteristics under typical working conditions. To overcome the limitation of existing linear weighting methods in multi-objective optimization, such as imbalanced optimization quality among sub-objectives, this paper proposes a new modeling approach based on the loss degree of sub-objectives. A multi-objective collaborative optimization model for the excavator with reduced energy consumption is established, and a corresponding multi-objective collaborative optimization algorithm is developed and applied to achieve optimal solutions for sub-objectives. The optimization results demonstrate that applying the new multi-objective collaborative optimization method to the excavator achieves better optimization quality than traditional methods. It also provides a more balanced improvement in the optimization values of each sub-objective, resulting in a significant reduction in the energy consumption of the excavator during operation.
Keyword ：
energy consumption modeling energy consumption modeling energy-saving energy-saving excavator excavator excavator working performance excavator working performance multiobjective optimization multiobjective optimization
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| GB/T 7714 | Lu, Zhe , Lin, Shuwen , Chen, Jianxiong et al. A Multi-Objective Collaborative Optimization Method for the Excavator Working Device to Support Energy Consumption Reduction [J]. | ENERGIES , 2023 , 16 (20) . |
| MLA | Lu, Zhe et al. "A Multi-Objective Collaborative Optimization Method for the Excavator Working Device to Support Energy Consumption Reduction" . | ENERGIES 16 . 20 (2023) . |
| APA | Lu, Zhe , Lin, Shuwen , Chen, Jianxiong , Gu, Tianqi , Xie, Yu . A Multi-Objective Collaborative Optimization Method for the Excavator Working Device to Support Energy Consumption Reduction . | ENERGIES , 2023 , 16 (20) . |
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