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A Combined Calibration Method for Workpiece Positioning in Robotic Machining Systems and a hybrid optimization algorithm for Improving Tool Center Point Calibration Accuracy

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APPLIED SCIENCES-BASEL 2025年第3期15卷 1033-1033页

作者： Hao, Daxian Zhang, Gang Zhao, Huan Ding, Han Huazhong Univ Sci & Technol State Key Lab Intelligent Mfg Equipment & Technol Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Wuxi Res Inst Wuxi 214174 Peoples R China

This paper addresses the machining requirements for large aerospace structural components using robotic systems and proposes a method for rapid workpiece positioning that combines the simplicity of vision-based positioning with the precision of contact-based methods. To enhance the accuracy of robot calibration, a novel approach utilizing a ruby probe for sphere-to-sphere contact calibration of the Tool Center Point (TCP) is introduced. A robot contact calibration model is formulated, transforming the calibration process into a nonlinear least squares (NLS) optimization problem. To tackle the challenges of NLS optimization, a hybrid LM-D algorithm is developed, integrating the Levenberg-Marquardt (L-M) and DIviding RECTangle (DIRECT) algorithms in an iterative process to achieve the global optimum. This algorithm ensures computational efficiency while maximizing the likelihood of finding a globally optimal solution. An iterative convergence termination criterion for TCP calibration is established to determine global convergence, further enhancing the algorithm's efficiency. Experimental validation was performed on industrial robots, demonstrating the proposed algorithm's superior performance in global convergence and iteration efficiency compared to traditional methods. This research provides an effective and practical solution for TCP calibration in industrial robotic applications.

关键词： robotic machining hybrid optimization algorithm sphere-to-sphere TCP calibration combined calibration

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Damage detection of civil structures based on hybrid optimization algorithm and combined correlation function of heterogeneous responses

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MEASUREMENT 2025年 246卷

作者： Zhang, Guangcai Wan, Chunfeng Yang, Zhiyuan Xie, Liyu Xue, Songtao Southeast Univ Minist Educ Key Lab Concrete & Prestressed Concrete Struct Nanjing Peoples R China Tongji Univ Dept Disaster Mitigat Struct Shanghai 200092 Peoples R China Tohoku Inst Technol Dept Architecture Sendai Japan

Accurate and robust damage detection of civil structures subjected to ambient excitations is crucial for ensuring safety and maintaining structural integrity. Heuristic algorithms and traditional reference point-defined correlation function methods have been employed in recent years. However, most single-method optimization strategies suffer from drawbacks such as slow convergence for global search optimizers and strong reliance on the initial guess for local search optimizers. Additionally, selecting the optimal reference point a priori is difficult, and identification accuracy would be severely compromised if the selected reference point exhibits poor response sensitivity to damage. To overcome these limitations, this paper proposes a novel output-only damage detection method for civil structures based on the hybrid optimization algorithm and combined correlation function of heterogeneous responses. The hybrid optimization algorithm integrates the local search operator of the BroydenFletcher-Goldfarb-Shanno (BFGS) algorithm into the global search optimizer of the hybrid Jaya and differential evolution algorithm (HJDEA), leveraging their comprehensive exploration and good convergence capacities. A new objective function is formulated based on the combined correlation function among acceleration and strain, eliminating the need for a reference point. To demonstrate the effectiveness of the proposed method, numerical studies on the Guangzhou new TV tower and a complex three-dimensional space truss structure are conducted. Furthermore, the effect of noise level, sampling frequency, sampling duration, and number of data points are investigated. The results show that the proposed method based on HJDEA-BFGS algorithm and combined correlation function with heterogeneous responses can achieve less than 0.4% mean error for varying damage scenarios and maintains robustness under noise levels up to 20%, demonstrating its reliability for real-world applications.

关键词： Broyden-Fletcher-Goldfarb-Shanno Combined correlation function Damage detection Heterogeneous responses hybrid optimization algorithm Output-only method

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Development of hybrid optimization algorithm for structures furnished with seismic damper devices using the particle swarm optimization method and gravitational search algorithm

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Earthquake Engineering and Engineering Vibration 2022年第2期21卷 455-474页

作者： Najad Ayyash Farzad Hejazi Civil Engineering University Putra MalaysiaSeri Kembangan 43300Malaysia

Previous studies about optimizing earthquake structural energy dissipation systems indicated that most existing techniques employ merely one or a few parameters as design variables in the optimization process,and thereby are only applicable only to simple,single,or multiple degree-of-freedom *** current approaches to optimization procedures take a specific damper with its properties and observe the effect of applying time history data to the building;however,there are many different dampers and isolators that can be ***,there is a lack of studies regarding the optimum location for various viscous and wall *** main aim of this study is hybridization of the particle swarm optimization(PSO) and gravitational search algorithm(GSA) to optimize the performance of earthquake energy dissipation systems(i.e.,damper devices) simultaneously with optimizing the characteristics of the *** types of structural dampers device are considered in this study:(ⅰ) variable stiffness bracing(VSB) system,(ⅱ) rubber wall damper(RWD),(ⅲ) nonlinear conical spring bracing(NCSB) device,(iv) and multi-action stiffener(MAS) *** many parameters may affect the design of seismic resistant structures,this study proposes a hybrid of PSO and GSA to develop a hybrid,multi-objective optimization method to resolve the aforementioned *** characteristics of the above-mentioned damper devices as well as the section size for structural beams and columns are considered as variables for development of the PSO-GSA optimization algorithm to minimize structural seismic response in terms of nodal displacement(in three directions) as well as plastic hinge formation in structural members simultaneously with the weight of the *** that,the optimization algorithm is implemented to identify the best position of the damper device in the structural frame to have the maximum effect and minimize the seismic structure *** examine the performance

关键词： hybrid optimization algorithm structures earthquake seismic damper devices particle swarm optimization method gravitational search algorithm

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Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework:turnkey project-oriented rapid manufacturing system configuration

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Advances in Manufacturing 2024年第4期12卷 698-725页

作者： Shu-Lian Xie Feng Xue Wei-Min Zhang Jia-Wei Zhu Zi-Wei Jia School of Mechanical Engineering Tongji UniversityShanghai201804People’s Republic of China

In the context of increasingly prominent product personalization and customization trends,intelligent manufacturing-oriented turnkey projects can provide manufacturers with fast and convenient turnkey services for manufacturing *** key characteristic is the transformation of the traditional design process into a configuration ***,the scope of configuration resources in existing research is limited;the cost and time required for manufacturing system construction are overlooked;and the integration of the system layout configuration is rarely considered,making it difficult to meet the manufacturing system configuration requirements of turnkey *** response,this study establishes a multi-factor integrated rapid configuration model and proposes a solution method for manufacturing systems based on the requirements of turnkey *** configuration model considers the system construction cost and duration and the product manufacturing cost and duration,as optimization *** differences in product feature-dividing schemes and configuration of processes,equipment,tools,fixtures,and layouts were considered *** proposed model-solving method is a three-layer hybrid optimization algorithm framework with two optimization algorithm modules and an intermediate algorithm *** hybrid configuration algorithms are established based on non-dominated sorting genetic algorithm-Ⅲ(NSGAⅢ),non-dominated sorting genetic algorithm-Ⅱ(NSGAⅡ),multi-objective simulated annealing(MOSA),multi-objective neighborhood search(MONS),and tabu search(TS).These algorithms are compared and validated through a hydraulic valve block production case,and the TS and NSGAⅢ(TS-NSGAⅢ)hybrid algorithm exhibits the best *** case demonstrates the effectiveness of the proposed model and solution method.

关键词： Manufacturing systems Configuration Turnkey projects hybrid optimization algorithm Multi-objective optimization

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Model parameters estimation of aero-engine based on hybrid optimization algorithm

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航空动力学报 2011年第7期26卷 1665-1671页

作者： LI Qiu-hong LI Ye-bo JIANG Dian-wen (College of Energy and Power EngineeringNanjing University of Aeronautics and Astronautics Nanjing 210016 China

A hybrid optimization algorithm for the time-domain identification of multivariable,state space model for aero-engine was presented in this *** optimization procedure runs particle swarm optimization(PSO) and least squares optimization(LSO) "in series".PSO starts from an initial population and searches for the optimum solution by updating ***,it can sometimes run into a suboptimal *** LSO can start from the suboptimal solution of PSO,and get an optimum solution by conjugate gradient *** algorithm is suitable for the high-order multivariable system which has many parameters to be estimated in wide *** optimization algorithm is applied to estimate the parameters of a 4-input 4-output state variable model(SVM) for *** simulation results demonstrate the effectiveness of the proposed algorithm.

关键词： aero-engine state variable model(SVM) particle swarm optimization(PSO) least squares optimization(LSO) hybrid optimization algorithm

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An improved hybrid optimization algorithm for vibration based-damage detection

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ADVANCES IN ENGINEERING SOFTWARE 2016年 93卷 47-64页

作者： Nhamage, Idilson Antonio Lopez, Rafael Holdorf Fadel Miguel, Leandro Fleck Univ Eduardo Mondlane Dept Engn Civil Ave MocambiqueKm 1-5POB 257 Maputo Mozambique Univ Fed Santa Catarina Dept Engn Civil Rua Joao Pio Duarte da Silva BR-88040970 Florianopolis SC Brazil

In this paper, an improvement in the hybrid stochastic/deterministic Pincus-Nelder-Mead optimization algorithm (P-NMA) which enables to solve the target optimization problem of vibration-based damage detection is proposed. The proposed modification consists in reducing the sampling domain of the Pincus formula by assigning a maximum number of damaged elements, i.e., by allowing only a few elements of the sampling vector to be different from 1. Consequently, a new parameter which determines the maximum number of damaged elements (np(max)) is introduced and must be choose by the designer. Such a modification attempts to speed up the convergence of the original version of the P-NMA and thus, reducing its computational cost. A series of numerical examples, all selected from literature, was performed. To test the accuracy and efficiency of the proposed improved optimization algorithm (IP-NMA), its results were compared to those obtained by the P-NMA and the metaheuristic harmony search algorithm (HS). A statistical analysis was also performed in order to test the robustness of the three algorithms. The proposed improved optimization algorithm showed better performance (more accurate and required lower computational cost than the original version of the P-NMA and the metaheuristic HS), emphasizing its capacity in damage diagnosis and assessment. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Damage detection hybrid optimization algorithm Pincus-Nealder-Mead algorithm Representation formula of Pincus Structural health monitoring Global optimization

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Robust optimization for a nonlinear switched time-delay system with noisy output measurements using hybrid optimization algorithm

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2019年第16期356卷 9730-9762页

作者： Yuan, Jinlong Xie, Jun Liu, Chongyang Teo, Kok Lay Huang, Ming Fan, Houming Feng, Enmin Xiu, Zhilong Dalian Maritime Univ Sch Sci Dept Math Dalian 116026 Liaoning Peoples R China Dalian Maritime Univ Coll Transportat Engn Dalian 116026 Liaoning Peoples R China PLA Dalian Naval Acad Dept Basics Teaching & Res Off Math Dalian 116018 Liaoning Peoples R China Shandong Inst Business & Technol Sch Math & Informat Sci Yantai 264005 Peoples R China Curtin Univ Dept Math & Stat Perth WA 6102 Australia Tianjin Univ Finance & Econ Coordinated Innovat Ctr Computable Modeling Manag Tianjin 300222 Peoples R China Dalian Univ Technol Sch Math Sci Dalian 116024 Liaoning Peoples R China Dalian Univ Technol Sch Life Sci & Biotechnol Dalian 116024 Liaoning Peoples R China

This paper considers the problem of using noisy output data to estimate unknown switching times and unknown system parameters arising in 1,3-PD batch production process of glycerol induced by Klebsiella pneumonia. We formulate the problem as a robust optimization problem in which the unknown quantities are decision variables to be chosen optimally, with the cost function penalizing the mean and variance of the relative error between the output of the system and the measured actual noisy system output. This problem is governed by a switched time-delay system subject to continuous state inequality constraints arising from engineering specifications. A new time-scaling transformation and constraint transcription technique are used then to convert this resulting problem into a sequence of approximate subproblems. A hybrid optimization algorithm combined genetic algorithm with gradient-based method is developed to solve these resulting subproblems. Finally, we explore the correctness of the optimal switching times and system parameters obtained, as well as the effectiveness of the proposed algorithm. (C) 2019 Published by Elsevier Ltd on behalf of The Franklin Institute.

关键词： Nonlinear programming Robust optimization Switched time-delay system Noisy output data hybrid optimization algorithm

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Optimal Power Flow Using a hybrid optimization algorithm of Particle Swarm optimization and Gravitational Search algorithm

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2015年第17期43卷 1958-1970页

作者： Radosavljevic, Jordan Klimenta, Dardan Jevtic, Miroljub Arsic, Nebojsa Univ Pristina Kosovska Mitrovica Fac Tech Sci Kosovska Mitrovica 38220 Serbia

This article presents a hybrid algorithm based on the particle swarm optimization and gravitational search algorithms for solving optimal power flow in power systems. The proposed optimization technique takes advantages of both particle swarm optimization and gravitational search algorithms by combining the ability for social thinking in particle swarm optimization with the local search capability of the gravitational search algorithm. Performance of this approach for the optimal power flow problem is studied and evaluated on standard IEEE 30-bus and IEEE 118-bus test systems with different objectives that reflect fuel cost minimization, voltage profile improvement, voltage stability enhancement, power loss reduction, and fuel cost minimization with consideration of the valve point effect of generation units. Simulation results show that the hybrid particle swarm optimization-gravitational search algorithm provides an effective and robust high-quality solution of the optimal power flow problem.

关键词： optimal power flow particle swarm optimization gravitational search algorithm hybrid optimization algorithm

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A homogeneous superconducting magnet design using a hybrid optimization algorithm

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MEASUREMENT SCIENCE AND TECHNOLOGY 2013年第12期24卷 125402. doi:10.1088/0957-0233/24/12/125402-125402. doi:10.1088/0957-0233/24/12/125402页

作者： Ni, Zhipeng Wang, Qiuliang Liu, Feng Yan, Luguang Chinese Acad Sci Inst Elect Engn Key Lab Appl Superconduct Beijing 100190 Peoples R China Univ Queensland Sch Informat Technol & Elect Engn Brisbane Qld 4072 Australia

This paper employs a hybrid optimization algorithm with a combination of linear programming (LP) and nonlinear programming (NLP) to design the highly homogeneous superconducting magnets for magnetic resonance imaging (MRI). The whole work is divided into two stages. The first LP stage provides a global optimal current map with several non-zero current clusters, and the mathematical model for the LP was updated by taking into account the maximum axial and radial magnetic field strength limitations. In the second NLP stage, the non-zero current clusters were discretized into practical solenoids. The superconducting conductor consumption was set as the objective function both in the LP and NLP stages to minimize the construction cost. In addition, the peak-peak homogeneity over the volume of imaging (VOI), the scope of 5 Gauss fringe field, and maximum magnetic field strength within superconducting coils were set as constraints. The detailed design process for a dedicated 3.0 T animal MRI scanner was presented. The homogeneous magnet produces a magnetic field quality of 6.0 ppm peak-peak homogeneity over a 16 cm by 18 cm elliptical VOI, and the 5 Gauss fringe field was limited within a 1.5 m by 2.0 m elliptical region.

关键词： magnetic resonance imaging animal imaging actively shielded technique hybrid optimization algorithm

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Dual secure robust watermarking scheme based on hybrid optimization algorithm for image security

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PERSONAL AND UBIQUITOUS COMPUTING 2021年第1期28卷 193-205页

作者： Alam, Shahzad Ahmad, Tanvir Doja, M. N. Pal, Om Jamia Millia Islamia Dept Comp Engn Fac Engn & Technol New Delhi 110025 India Govt India Minist Elect & Informat Technol New Delhi India

Digital watermarking is a technology that allows users to add copyright notifications or other confirmation messages to digital media. Image recognition is one of the applications of digital watermarking, which is used to identify digital images. The goal is not to prevent theft or theft of content but to provide a means of identifying the images and ensuring the integrity of the image. This paper proposes a dual security robust watermarking (DSRW) method based on a hybrid optimization algorithm for image protection in the DWT domain used in the IoT perceptive layer. First, we introduce the redistributed differential wavelet transform (RI-DWT) to induce the LH and HL subbands. Second, we proposed the advanced cat swarm optimization (ICSO) algorithm to find the best module for watermark inclusion. After the best batch selection, the inclusion procedure adds the binary score to the selected first-level approximate subband of the RI-DWT for each selected module. Optimal QR decomposition is used to estimate a single value in the image matrix. The main objective of the proposed watermarking plan is to ensure high robustness and security. The simulation results examine the significance of the proposed scheme and the validity of the proposed methods. The experiments are conducted to check various common image processing attacks, and the watermark extraction process generates high-quality image after different attacks.

关键词： Image authentication Watermarking Image security Subbands hybrid optimization algorithm

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