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Hemodynamic Analysis and Diagnosis Based on Multi-Deep Learning Models

Fluid Dynamics & Materials Processing 2023年第6期19卷 1369-1383页

作者： Xing Deng Feipeng Da Haijian Shao School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Jiangsu University of Science and TechnologyZhenjiang212003China Department of Electrical and Computer Engineering University of NevadaLas Vegas89154USA

This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional *** work is intended to improve current methods for the assessment of human health through measurement of the distribution of four types of blood cells,namely,eosinophils,neutrophils,monocytes,and lymphocytes,known for their relationship with human body damage,inflammatory regions,and organ illnesses,in particular,and with the health of the immune system and other hazards,such as cardiovascular disease or infections,more in *** results of the experiments show that the deep learning models can automatically extract features from the blood cell images and properly classify them with an accuracy of 98%,97%,and 89%,respectively,with regard to the training,verification,and testing of the corresponding datasets.

关键词： Blood cell analysis deep learning models classification-detection

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Structure Design of Multi-DOF Motor with Stator Permanent Magnet based on Flux Switching

EEA - Electrotehnica, Electronica, Automatica

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EEA - Electrotehnica, Electronica, Automatica 2023年第1期71卷 41-52页

作者： Guo, Xiwen Fang, Zhaowei Zhou, Rui Wang, Qunjing Zhang, Ronglin School of Electrical Engineering and Automation Anhui University Anhui Hefei China National Engineering Laboratory of Energy-saving Motor & Control Technique Anhui University Anhui China Industrial Power Saving and Safety Laboratory Anhui University Anhui Hefei China Collaborative Innovation Centre of Industrial Energy-Saving and Power Quality Control Anhui University China

This paper aims at the problems of no core in the stator coil of a compact multi-degree-of-freedom (M-DOF) motor, i.e. small output torque and low power density. In order to increase the output torque, a stator permanent magnet spherical motor based on flux switching is proposed. Firstly, the principle of flux switching is introduced. The basic structure of the new motor is preliminarily designed, and the motion mechanism is analysed for spin motion and tilt motion respectively. Then the minimum model of a novel motor is established in ANSYS by using the virtual displacement method. The key parameters such as the ratio of stator pole tooth to permanent magnet size, different stator pole tooth end structures, different pole tooth surface shapes, different pole sizes, permanent magnet thickness, different magnetisation methods and different ampere-turn numbers are optimised within a reasonable parameter range. The simulation results are analysed and discussed, and the optimal results for each key parameter are thus given. Finally, considering the arrangement of the stator and rotor poles, the rationality of the three-DOF motion was verified by means of two energising strategies, spin motion and tilt motion, verified the reasonableness of the above optimal parameters and thus determined the structural parameters of the new spherical motor to accomplish the three-DOF motion and the maximum torque range. The simulation results show that the electromagnetic torque varies approximately linearly over a range of ampere-turns for the same position of the rotor pole teeth. It provides an opportunity for the M-DOF motor design of a high torque output and power density. © 2023, Editura ELECTRA. All rights reserved.

关键词： Torque

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Target Assignment in the Multi-UAV Combat Based on Distributed Compensation Auction Algorithm with Fixed-Time Consensus Protocol 7th

Target Assignment in the Multi-UAV Combat Based on Distri...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Chen, Yiyang Hua, Yongzhao Yu, Jianglong Dong, Xiwang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789819733231

This paper mainly focuses on the target assignment problems in the unmanned aerial vehicle (UAV) swarm combat. Firstly, the idea of the multi-UAV swarm combat is shown and the constraints and the benefit matrix of the target assignment task are modeled. Secondly, a fixed-time consensus protocol is utilized to estimate the state of all the other agents and its convergence is proved by Lyapunov method. Then, a distributed compensation auction algorithm is proposed. Finally, the proposed distributed compensation auction algorithm is simulated and the results demonstrate the successful completion of the assignment task with only neighboring information. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Lyapunov methods

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Infrared Thermal Image Fault Detection of Electric Motor Based on Improved VGG16 Network Model 6

Infrared Thermal Image Fault Detection of Electric Motor Bas...

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6th International Conference on Communications, Information System and Computer engineering, CISCE 2024

作者： Zhu, Xianghua Hu, Shan Bing, Zhigang Zhao, Di School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Key Laboratory of Information Sensing & Intelligent Control Tianjin China Engineering Teaching Practice Training Center of Tiangong University Tianjin China

ISBN: (纸本)9798350353174

As a core component of modern industry, electric motors are widely used in important fields such as electric power, machinery and national defense, and the fault detection of their thermal images faces problems such as diverse fault types, insufficient complex data processing capability and long training time. To address the above problems, this paper proposes a method for fault detection of infrared thermal images of electric motors based on an improved VGG16 network model. In the model construction and implementation, based on the VGG16 network model, the significant optimization of training time and accuracy is achieved by improving the structure of the latter layers of the model and introducing the migration learning strategy, as well as adding the callback function, the AdamW optimizer and the focal point loss function to the model. The experimental results show that the improved VGG16 model increases the average accuracy by 12.96%, reduces the average loss rate by about 23 times, and shortens the training time by half in infrared thermal image fault detection of induction motors. In the model performance evaluation, whether adjusting the test conditions or conventional model evaluation methods, the results reflect the superiority of the improved model in the realm of infrared thermal image anomaly identification of induction motors, which has practical application value. © 2024 IEEE.

关键词： Electric motors

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Robust H∞ Consensus control for Heterogeneous Multi-agent Systems Based on Time-delay and Switching Topology 4

Robust H∞ Consensus Control for Heterogeneous Multi-agent S...

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4th IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2024

作者： Du, Jiayi Liu, Jia Cao, Runxi Zhang, Yijing Zhang, Yunxi Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350363586

This study proposes a consensus control strategy for heterogeneous multi-agent systems characterized by uncertain parameters and external disturbances, to address the intricate robust control challenges posed by time-varying delays and dynamic network topologies. A distributed control protocol is design to make the states of the heterogeneous multi-agent system be consistent. Then the stability of the control protocol is analyzed by Lyapunov-Krasovskii stability theory and integral inequality techniques, and the sufficient conditions for the system to achieve robust H∞ consistency are obtained. Finally, the results of the simulations verify the accuracy of the theoretical analysis presented in this paper. © 2024 IEEE.

关键词： Multi agent systems

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Toward quantum unmanned systems

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Science China(Technological Sciences) 2024年第7期67卷 2277-2280页

作者： CHENG ShuMing QI HongSheng SUN Yue LIU LiJun XIE ShaoRong REN XiaoQiang Department of Control Science and Engineering Tongji UniversityShanghai 200092China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China Cipher Cloud Core Ltd. Beijing 100085China College of Mathematics and Computer Science Shanxi Normal UniversityLinfen 041081China School of Computer Engineering and Science Shanghai UniversityShanghai 200444China School of Mechatronic Engineering and Automation Shanghai UniversityShanghai 200444China

1 Quantum information technology Quantum information technology utilizes physical systems at the microscopic level, such as photon, atom, ion, and superconducting, to accomplish information-processing tasks that are impossible for the classical macroscopic world. During the past decade, significant process has been achieved in the pursuit of quantum technology into practical applications,generating great research interest from various domains, with the potential to radically change our information infrastructure [1–3].

关键词： quantum utilize generating

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State of Charge Estimation for Lithium Batteries Based on the Square Root Cubature Kalman Filter Algorithm 4

State of Charge Estimation for Lithium Batteries Based on th...

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4th International Conference on Energy engineering and Power Systems, EEPS 2024

作者： Liu, Hanhan Su, Jun School of Electrical Engineering and Automation Xiamen University of Technology Xiamen China Xiamen University of Technology Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen China

ISBN: (纸本)9798350366914

The State of Charge of lithium batteries is a crucial parameter for the battery management system in electric vehicles and energy storage applications. Accurate estimation of the State of Charge is of significant importance for the design of the battery management system. To address the problem of accurately estimating the State of Charge, this paper employs the square root cubature Kalman filter algorithm in conjunction with a second-order resistance-capacitance equivalent circuit model of lithium batteries for precise State of Charge estimation. This study utilizes the open-source experimental dataset of the Panasonic NCR18650PF lithium battery and identifies the parameters of the second-order resistance-capacitance equivalent circuit model through the forgetting factor recursive least squares method. To verify the estimation accuracy of the Square Root Cubature Kalman Filter algorithm, the algorithm is simulated and tested using the Urban Dynamometer Driving Schedule conditions within the experimental dataset. The estimation accuracy of the Square Root Cubature Kalman Filter algorithm is compared with that of the Extended Kalman Filter algorithm and the Unscented Kalman Filter algorithm under the same conditions. Simulation test results indicate that the Square Root Cubature Kalman Filter algorithm achieves higher accuracy in estimating the State of Charge of lithium batteries. © 2024 IEEE.

关键词： State of charge

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Research on Speech Recognition Methods Based on Spectral Subtraction and Improved BP Neural Network Algorithm 7

Research on Speech Recognition Methods Based on Spectral Sub...

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7th IEEE Information Technology, Networking, Electronic and automation control Conference, ITNEC 2024

作者： Ma, Yuqi Zhang, Yunxi Wang, Zihan Zhao, Ya Liu, Jia School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350370782

This paper presents a speech recognition method combining spectral subtraction with improved BP neural network algorithm. The speech samples containing unstable noise are collected in the real environment. Firstly, the noise from speech signals is removed using spectral subtraction method, and the speech feature parameters after noise removal are extracted. Then the speech is recognized effectively by the improved BP neural network algorithm. Finally, some comparative experiments are given to verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Speech enhancement

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Deep learning-based digital twin for intelligent predictive maintenance of rapier loom

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Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 9409-9430页

作者： Xiao, Yanjun Li, Rui Zhao, Yue Wang, Xiaoliang Liu, Weiling Peng, Kai Wan, Feng School of Mechanical Engineering Hebei University of Technology Tianjin China Career Leader Intelligent Control Automation Company Jiangsu Province Suqian China Tianjin Key Lab Power Transmiss & Safety Technol Department State Key Lab Reliabil & Intellectual Elect Tianjin China

The rapier loom works in a complex environment and operates at high speeds. It is inevitable that its performance will deteriorate during the production process, which in turn will cause faults. The development of maintenance has undergone the transition from "regular maintenance" and "post-event maintenance" to "predictive maintenance". In order to achieve the synergistic optimization goal of ensuring operational safety and reducing operational costs, a predictive maintenance method driven by the fusion of digital twin and deep learning is proposed based on the idea of "combining the real with the virtual and controlling the real". Firstly, a digital twin system structure model of rapier weaving machine is constructed, and the overall architecture of digital twin is proposed according to the full operation cycle of rapier weaving machine. Then, the digital twin-driven process parameter evaluation and prediction and health state evaluation and prediction are investigated separately. In order to achieve the evaluation and prediction of process parameters to ensure the efficiency of weaving machine operation, the prediction method of IWOA optimized BP neural network driven by twin data is proposed and the model is updated and optimized based on the martingale distance approach. In order to achieve health state assessment and prediction, we use health index as an evaluation index to characterize the health condition of spindles, and use BiLSTM network to achieve prediction of remaining spindle life and then make maintenance decisions. The results show that there are greater advantages to combining deep learning and digital twin technology for intelligent predictive maintenance of rapier loom. © 2024 – IOS Press.

关键词： Forecasting

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Spin Hall Effect of Light (SHEL) Ellipsometry for surface measurement with different models of optical interface

Spin Hall Effect of Light (SHEL) Ellipsometry for surface me...

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Optics and Photonics International Congress 2024, OPIC 2024

作者： Zahra, Naila Mizutani, Yasuhiro Uenohara, Tsutomu Takaya, Yasuhiro Graduate School of Engineering Osaka University 2-1 Yamadaoka Osaka Suita Japan Instrumentation Control & Automation Research Group Institut Teknologi Bandung Ganesha 10 Bandung Indonesia

ISBN: (数字)9781510687646

ISBN: (纸本)9781510687639

The demonstration of the Spin Hall Effect of Light (SHEL) observation by weak measurement has enabled exploration of the phenomenon in various fields including its application for precision measurement. The sensitivity of SHEL to the optical properties of the medium opens the possibility for precision measurement. Previously, SHEL ellipsometry has shown its potential as surface measurement. In this paper, SHEL ellipsometry is utilized to reconstruct flat optical windows fabricated from different material. Two different models of optical interface are used to solve the SHEL ellipsometry formula, based on air-glass model to retrieve pseudo refractive index value and based on effective medium approximation model to retrieve roughness approximation as effective thickness. This paper further exhibits SHEL potential for surface measurement of smooth surface objects. © 2024 SPIE.

关键词： Surface measurement

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