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A novel minimum zone method for cylindricity error evaluation based on rotation projection method and adaptive particle swarm optimisation

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PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY 2025年 94卷 149-158页

作者： Cheng, Rongjun Jian, Hebang Li, Yu Huang, Qiangxian Zhang, Liansheng Li, Hongli Hefei Univ Technol Anhui Prov Key Lab Measuring Theory & Precis Instr Hefei Peoples R China Hefei Univ Technol Anhui Prov Engn Res Ctr Semicond Inspec Technol & Hefei Peoples R China

To realize an accurate and rapid evaluation of cylindricity error, a novel minimum zone algorithm based on rotation projection method and adaptive particle swarm optimisation (RPM-apso) is proposed. The principle of this method is to firstly transform the three-dimensional cylindrical coordinates into two-dimensional circular coordinates via rotation and projection, and then calculate the minimum zone roundness error that is equivalent to the minimum zone cylindricity error. apso algorithm is adopted twice to determine the optimal rotation angles and accurate roundness error of the projected coordinates respectively. Owing to the dimensionality reduction, the calculation difficulty is reduced and the computational efficiency is substantially improved. The effectiveness and accuracy of the proposed algorithm are verified by constructing two groups of cylindrical simulation datasets. Compared with other five intelligent optimisation algorithms and the results of the published literature, the RPM-apso algorithm is proved to be superior in terms of computational accuracy and convergence speed, which can provide an accurate, efficient and reliable method for the cylindricity error evaluation of micro-nano coordinate measuring machine.

关键词： Cylindricity error Minimum zone method apso algorithm Rotation projection

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Speaker recognition based on apso-K-means clustering algorithm

Speaker recognition based on APSO-K-means clustering Algorit...

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International Conference on Artificial Intelligence and Computational Intelligence

作者： Sha, Man Yang, Huixian Xiangtan Univ Coll Informat Engn Xiangtan Hunan Peoples R China Xiangtan Univ Fac Mat & Photoelect Phys Xiangtan Peoples R China

ISBN: (纸本)9780769538167

In this paper, combined with ant colony algorithm, particle swarm optimization algorithm, K-means clustering algorithm, we propose an apso-K-means clustering algorithm applied to speaker recognition. The algorithm utilizes the strong ability of the ant colony algorithm to process local extremum to avoid the sensitivity to local optimization of the PSO algorithm (apso). Meanwhile, it utilizes apso to guide the initialization of the cluster centers to improve the deficiency of the K-means clustering algorithm which depends on the initial value, which makes it easy to converge toward global optimality. The experiments in speaker recognition show that the new approach is better than the traditional method and effectively reduces the error recognition rate.

关键词： speaker recognition apso algorithm K-means cluster algorithm

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NONLINEAR DYNAMICS 2018年第3期91卷 1697-1711页

作者： Wu, Chengjin Lv, Shang Long, Juncai Yang, Jianhua Sanjuan, Miguel A. F. China Univ Min & Technol Sch Mechatron Engn Xuzhou 221116 Peoples R China Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA China Univ Min & Technol Jiangsu Key Lab Mine Mech & Elect Equipment Xuzhou 221116 Peoples R China Univ Rey Juan Carlos Dept Fis Nonlinear Dynam Chaos & Complex Syst Grp Tulipan S-N Madrid 28933 Spain Kaunas Univ Technol Dept Appl Informat Studentu 50-407 LT-51368 Kaunas Lithuania Univ Maryland Inst Phys Sci & Technol College Pk MD 20742 USA

We investigate the aperiodic stochastic resonance (ASR) in a bistable fractional-order system when the fractional order lies in the interval (0, 2]. We find that a weak aperiodic signal can be amplified and optimized by varying the fractional order in the nonlinear system, no matter whether it has the assistance of the noise or not. We focus mainly on the self-similarity of the response to the input aperiodic signal and the adaptive ASR. The self-similarity is a characteristic that the response of a nonlinear system matches the input signal well, in the absence of the noise excitation. The adaptive ASR is a technique for the optimal ASR to occur by modulating the fractional order, the noise intensity, or the bistable system parameters. In order to make the optimal ASR occur, an adaptive particle swarm optimization (apso) algorithm is used in this work as the method of parameter optimization. In previous works, only the periodic signal is optimized in a noisy bistable fractional-order system and the ASR induced by the fractional-order system has not been achieved. In engineering and scientific fields, not only periodic signals need to be processed, but also weak aperiodic ones. Moreover, the optimal ASR shows better results based on the apso algorithm. We believe that the results of this paper might have a positive contribution in the dynamics research.

关键词： Self-similarity Aperiodic stochastic resonance Fractional-order calculus Noise apso algorithm

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The multi-goal optimal analysis of stand-alone gas engine heat pump system with energy storage (ESGEHP) system

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ENERGY AND BUILDINGS 2017年 139卷 525-534页

作者： Zhang, Qiang Yang, Zhao Gao, Yi-De Tianjin Univ Dept Thermal Energy Engn Tianjin 300072 Peoples R China

Gas-engine driven heat pump could avoid energy loss in the process of generation, transmission and distribution, and effectively reduce the electric power load at the peak time in summer. In the present study, a novel stand-alone gas engine heat pump system with energy storage is put forward, which combined with the energy storage system and the autonomous power supply system. The annual performance optimization model of the gas engine heat pump system with energy storage system is proposed, which is calculated based on apso algorithm. The simulation results were well agreed with experimental data, the average difference is 8.9%, 9.63% and 21.7% for the annual primary energy ratio of heating, cooling, transitional seasoh, respectively. Based on the simulation results, the autonomous generating capacity E and the speed of engine n have high effect on the objective function, and the ratio of electricity to heat/cool/domestic hot water should be no greater than 0.1. The annual primary energy ratio of the gas engine heat pump system with energy storage system in heating, cooling and transitional season was increased by 6.11, 19.11% and 34.83% compared with the gas-engine driven heat pump system, respectively. The gas engine heat pump system with energy storage system can be used indifferent climate regions and buildings, which could provide a more stable work mode and higher annual primary energy ratio than the gas-engine driven heat pump system with a little energy loss. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Stand-alone gas engine heat pump system Annual primary energy ratio Autonomous power supply system Energy storage system apso algorithm

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Research on personalized control strategy of EHB system for consistent braking feeling considering driving behaviors

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ENERGY 2024年 293卷

作者： Zhang, Ruijun Zhao, Wanzhong Wang, Chunyan Tai, Kang Nanjing Univ Aeronaut & Astronaut Coll Energy & Power Engn Nanjing 210016 Peoples R China Nanyang Technol Univ Sch Mech & Aerosp Engn Nanyang 639798 Singapore

Since the existing control strategy for electro-hydraulic composite braking (EHB) system is essentially "vehiclecentered", it is liable to cause incompatibility with current driving behavior, torque fluctuation and inconsistent braking feeling occur, which affects braking safety. In view of the above issue, a personalized MPC control strategy in accordance with the design methodology of characteristic E is presented. To do this, the data collection platform for characterizing driving behavior is constructed under typical vehicle-following conditions. Then, a generalized radial basis function (GRBF) neural network is adopted to accurately identify braking intensity of different driving behaviors. Next, an optimization model for the maximum energy recovery of EHB system is established in terms of required braking torque and motor speed, the distribution coefficient of braking torque is optimized by applying the adaptive particle swarm optimization (apso) algorithm. Finally, the proposed personalized MPC control strategy is verified under different driving behaviors, the results display that: (1) the personalized MPC controller possess superiority of acquiring stable braking feeling, the torque tracking error is decreased by 96.8 %;(2) energy recovery for EHB system with optimized torque distribution is increased by 34.47 % under FTP-75 cycle conditions, and the response amplitude of braking feeling is increased by 5.6 %.

关键词： EHB system system Braking feeling apso algorithm Torque distribution GRBF neural network Personalized MPC controller

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Novel online prediction model for thermal convexity of work rolls during hot steel rolling based on machine learning algorithms

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 254卷

作者： Lu, Jia Wang, Pengfei Huang, Huagui Hao, Luhan Li, Xu Peng, Qiuming Su, Lihong Deng, Guanyu Yanshan Univ Natl Engn Res Ctr Equipment & Technol Cold Strip R Qinhuangdao 066004 Peoples R China Northeastern Univ State Key Lab Rolling & Automat Shenyang 110819 Peoples R China State Key Lab Metastable Mat Sci & Technol Qinhuangdao 066004 Peoples R China Univ Wollongong Sch Mech Mat Mechatron & Biomed Engn Wollongong NSW 2522 Australia Univ Queensland Sch Mech & Min Engn St Lucia Qld 4072 Australia

In this study, an ML-based online prediction strategy is developed for the thermal convexity of work rolls in hot rolling. A finite volume method simulation was developed to establish the temperature field of the work rolls and validated by measurements. A thermal convexity simulation model was established on the basis of the temperature field model to supplement the thermal convexity data. The accelerated vector that departs from the global worst solution is introduced for the PSO algorithm, and the accelerated particle swarm optimization (apso) algorithm is proposed, which has higher optimization efficiency and better optimization effect than the pso algorithm. It is tested that apso-RF outperforms apso-SVM and RBF in predicting the thermal convexity of rolls, showing the best prediction accuracy and stability. In addition, the reduction of rolling has the greatest effect on the work roll convexity. The ML prediction results are very close to the industrial measurements, with small average and maximum differences. The proposed apso-RF in-line ML method has high accuracy and efficiency and is expected to improve the quality of hot rolling in a practical way.

关键词： Machine learning Finite volume simulation Steel manufacturing Hot rolling apso algorithm Thermal convexity

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Principle and control strategy of a novel wave-to-wire system embedded ocean energy storage optimization

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OCEAN ENGINEERING 2023年第1期271卷

作者： Yao, Ganzhou Luo, Zirong Lu, Zhongyue Wang, Mangkuan Shang, Jianzhong Guerrerob, Josep M. Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha Peoples R China Aalborg Univ Dept Energy Technol Aalborg Denmark

Fluctuation and unpredictability of wave power output affect the safe operation of the power grid, which greatly restricts the development of wave power generation. This paper firstly introduces the principle and control strategy of wave to wire (W2W) model, whose input is from wave energy conversion (WEC) system and output to the electrical power injected into grid for stable power. Then, an adapted particle swarm optimization (apso) algorithm-based maximum power point tracking technology (apso-MPPT) considering adaptive inertia weighting variables is presented for quick dynamic reaction. Comparisons are made with the traditional constant voltage method, INC method, P&Q method, and PSO algorithm, the apso-MPPT method can reduce the tracking time by 9.3% less than the quickest traditional. Secondly, a K-SOC curve algorithm-based hybrid energy storage system (KSC-HESS) optimization is conducted for smoothing the wave power output, with real time control performance. Simulations under output power fluctuation, load pulsation and load unbalancing situations are occupied for demonstrating high performance for the characteristics of the proposed KSC-HESS, in both reducing high-frequency burden for super-capacitors and protecting batteries from over voltage. Furthermore, results of prototype experiment verified the effectiveness with better efficiency by adapting the proposed apso-MPPT and KSC-HESS for the proposed W2W system. Analysis shows the proposed W2W approach has comparative advantages of control complexity and high reliability for renewable power output.

关键词： Maximum power point tracking (MPPT) Point absorber wave energy converter (PA WEC) Hybrid energy storage system (HESS) apso algorithm Wave to wire (W2W) system

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Magnetic Actuation for Wireless Capsule Endoscopy in a Large Workspace Using a Mobile-Coil System

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MICROMACHINES 2024年第11期15卷 1373-1373页

作者： Li, Xiao Zeng, Detian Xu, Han Zhang, Qi Liao, Bin Guilin Univ Elect Technol Sch Elect Engn & Automat Guilin 541004 Peoples R China Key Lab Intelligence Integrated Automat Guangxi Un Guilin 541004 Peoples R China Guilin Univ Elect Technol Sch Mech & Elect Engn Guilin 541004 Peoples R China

Current wireless capsule endoscopy (WCE) is limited in the long examination time and low flexibility since the capsule is passively moved by the natural peristalsis. Efforts have been made to facilitate the active locomotion of WCE using magnetic actuation and localization technologies. This work focuses on the motion control of the robotic capsule under magnetic actuation in a complex gastrointestinal (GI) tract environment in order to improve the efficiency and accuracy of its motion in dynamic, complex environments. Specifically, a magnetic actuation system based on a four-electromagnetic coil module is designed, and a control strategy for the system is proposed. In particular, the proportional-integral-derivative (PID) control parameters and current values are optimized online and in real time using the adaptive particle swarm optimization (apso) algorithm. In this paper, both simulations and real-world experiments were conducted using acrylic plates with irregular shapes to simulate the GI tract environment for evaluation. The results demonstrate the potential of the proposed control methods to realize the accurate and efficient inspection of the intestine using active WCE. The methods presented in this paper can be integrated with current WCE to improve the diagnostic accuracy and efficiency of the GI tract.

关键词： WCE magnetic actuation system magnetic field modeling apso algorithm

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The echo chirp signal amplification by the vibrational information fusion method

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INTERNATIONAL JOURNAL OF MODERN PHYSICS B 2020年第6期34卷

作者： Jia, Pengxiang Yang, Jianhua Tianjin Univ Sch Mech Engn Tianjin 300072 Peoples R China China Univ Min & Technol Sch Mechatron Engn Xuzhou 221116 Jiangsu Peoples R China

We use two traditional indices and propose a new fusion index to quantify the echo chirp signal amplification effectively. They are the cross-correlation coefficient, the spectral amplification factor and the fusion index. Through investigating different numerical examples, we verify the validation of the re-scaled vibrational resonance (VR) method for the echo chirp signal by using the two traditional indices. Besides, taking into account that a single index has its own shortness, we combine the advantages of the two traditional indices mentioned and propose a new fusion index based on the information fusion method. Then we verify the superiority of the fusion index. Furthermore, the effect of noise on VR is also investigated. Finally, with the help of the adaptive inertia weight particle swarm optimization (apso) algorithm, we propose the adaptive VR in noise background and verify its validity.

关键词： apso algorithm information fusion echo chirp signal noise adaptive vibrational resonance

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