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Design method of end worm gear drive,including tooth curve geometry and improved lubrication angle formula

Frontiers of Mechanical engineering 2024年第6期19卷 15-32页

作者： Jian CUI Yaping ZHAO Qingxiang MENG Zhiqiang HAO School of Mechanical Engineering and Automation Northeastern UniversityShenyang 110819China School of Mechanical Engineering Yanshan UniversityQinhuangdao 066004China Key Laboratory of Metallurgical Equipment and Control Technology of the Ministry of Education Wuhan University of Science and TechnologyWuhan 430081China

End worm gear drives are characterized by their multi-tooth contact,compact contour,and theoretical potential to overcome some inherent flaws of cylindrical worm ***,quantitative basic research on end worm gear drives is currently inadequate,which hinders the development of this *** work focuses on the computational design of end worm gear drives and proposes a new Niemann-type *** models of the proposed drive are established,and its engagement theory is deduced *** on the derived tooth surface equations,an innovative research methodology for the tooth curve geometry of the end worm gear is created,and the tooth curve in the worm gear reference plane is proved to be a *** improved formula for the lubrication angle is developed,which can provide more rational numerical results for the ***,the modified formula is universally applicable for line contact drives and can be used to quantitatively investigate the lubrication level between the teeth for the proposed *** outcomes demonstrate the favorable characteristics of the transmission,including broad conjugate areas,even contact lines,and fine global lubrication state.

关键词： end worm gear tooth curve geometry lubrication angle meshing characteristic nonlinear equation

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Automated Program for Estimation of Uncertainty in Medical Measurements

Automated Program for Estimation of Uncertainty in Medical M...

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2023 International Conference on Systems and Technologies of the Digital HealthCare, STDH 2023

作者： Khan, Svetlana Zhussupbekov, Sarsenbek Fedorenko, Igor NJSC Almaty University of Power Engineering and Telecommunications Department Automation and Control Almaty Kazakhstan

ISBN: (纸本)9798350315226

To estimate the uncertainty of measurement, analytical methods are widely used, a review and comparative analysis of which is given in the work. Among the existing methods for estimating the uncertainty in measurement, the most common is the classical method (GUM). The formula for the total standard uncertainty of the output quantity includes the values of partial derivatives (sensitivity coefficients), which, in the case of complex model equations that are often encountered in biological measurements, cause certain difficulties. In this paper, the main attention is paid to the numerical method of Kragten, which involves a modification of the law of propagation of uncertainties (the GUM method) with respect to the sensitivity coefficient. The paper presents the development of an automated program for calculating the uncertainty in measurement by the Kragten method, for which a Certificate was received on entering information into the State Register of Rights to Copyrighted Objects. © 2023 IEEE.

关键词： Numerical methods

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Predicting microbial extracellular electron transfer activity in paddy soils with soil physicochemical properties using machine learning

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Science China(Technological Sciences) 2024年第1期67卷 259-270页

作者： OU JiaJun LUO XiaoShan LIU JunYang HUANG LinYan ZHOU LiHua YUAN Yong School of Automation Guangdong University of TechnologyGuangzhou 510006China Guangdong Key Laboratory of Environmental Catalysis and Health Risk Control Guangzhou Key Laboratory Environmental Catalysis and Pollution ControlSchool of Environmental Science and EngineeringInstitute of Environmental Health and Pollution ControlGuangdong University of TechnologyGuangzhou 510006China School of Biomedical and Pharmaceutical Sciences Guangdong University of TechnologyGuangzhou 510006China

Soil extracellular electron transfer(EET)is a pivotal biological process within the realm of ***,EET suffers from a lack of predictive ***,an intricately crafted machine learning model has been developed for the purpose of predicting soil EET by using the physicochemical properties of soil as independent input variables and the EET capabilities in terms of current density(j_(max))and Coulombic charge(C_(out))as dependent output *** autoencoder ensemble stacking(AES)model was developed to address the aforementioned issue by integrating support vector machine,multilayer perceptron,extreme gradient boosting,and light gradient boosting machine algorithms as the stacking *** 10-fold crossvalidation,the AES model exhibited notable improvements in predicting j_(max)and C_(out),with average test R^(2)values of 0.83 and 0.84,respectively,surpassing those of single machine learning(ML)models and the basic ensemble *** utilizing partial correlation plots(PDPs),Shapley Additive explanations(SHAP)values,and SHAP decision plots,we quantitatively explained the impact and contribution of the input molecules on the AES model’s predictions of j_(max)and C_(out).In the context of the SHAP method for the AES model,total carbon(TC)was identified as the most correlated descriptor for j_(max),while total organic carbon(TOC)stood out as the most relevant descriptor for C_(out).In the prediction tasks of j_(max)and C_(out)within the AES model,employing a multitask ML approach allowed the model to benefit from the shared information of input variables,thereby enhancing its overall *** study provides a feasible tool for the prediction of soil EET from soil physiochemical properties and an advanced understanding of the relationship between soil physiochemical properties and EET capability.

关键词： extracellular electron transfer paddy soil machine learning prediction autoencoder ensemble stacking model

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Coronary Artery Segmentation in X-ray Angiography Based on Deep Learning Approach 43

Coronary Artery Segmentation in X-ray Angiography Based on D...

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43rd Chinese control Conference, CCC 2024

作者： Li, Shanbin Fan, Yiting South China University of Technology School of Automation Science and Engineering Guangzhou China Changji University School of Energy and Control Engineering Xinjiang China

ISBN: (纸本)9789887581581

Segmenting coronary arteries from X-ray coronary angiography (XCA) images allows observation of coronary artery morphology and stenosis, which is of great significance for computer-aided diagnosis and coronary artery disease treatment. However, XCA images have low contrast and irregular lighting due to the limits of existing imaging techniques, making vascular segmentation challenging. Segmentation of coronary arteries using conventional U-shaped segmentation networks is challenging due to the problem of major differences in vascular morphology, size, and overlap. This paper proposes a network based on the U-shape structure for multiscale context information fusion with lightweight GhostNetV2 as the backbone feature extraction network to improve the model's feature extraction capabilities. Then a multi-scale context fusion module (MCF) is proposed to effectively capture the contextual information of blood vessels. Finally, we propose a feature re-extraction module (FRM) to achieve effective fine feature re-extraction in complex backgrounds. Experimental results show that the model we propose achieves more accurate coronary artery segmentation in complex backgrounds with fewer parameters, improves the segmentation of fine vessels at the end of coronary arteries, and performs well compared with other artery segmentation models. The F1 score, Intersection over Union (IOU), accuracy (ACC), and Sensitivity (Sen) of the model can reach 82.23 %, 69.83 %, 98.79 %, 81.93 %, respectively. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Deep learning

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Integrated Multimodal Fault Diagnosis of Industrial Gearboxes Using Vibration Signals and Infrared Thermal Imaging 15

Integrated Multimodal Fault Diagnosis of Industrial Gearboxe...

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15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024

作者： Cao, Xunqi Li, Yan Yu, Kun Zhang, Yongchao School of Information and Control Engineering China University of Mining and Technology Xuzhou China School of Mechanical Engineering and Automation Northeastern University Shenyang China

ISBN: (纸本)9798350354010

With the increasing demand for precision in fault diagnosis of gearboxes in complex systems, diagnostic methods based solely on vibration signal characteristics have shown limitations. Therefore, multimodal information fusion technology has become a new trend in the field of gearbox fault diagnosis. This article innovatively proposes a multimodal diagnostic method that combines vibration signals with thermal images, aiming to use thermal imaging technology to intuitively capture the thermal changes during gearbox operation and integrate vibration signals to comprehensively reflect fault characteristics. By introducing Convolutional Neural Networks (CNN) for feature depth extraction, this method effectively improves the parsing ability of fault information, thereby enhancing the accuracy and reliability of fault diagnosis. Experimental data confirms that compared to diagnostic methods using a single signal source, the method proposed in this paper performs well in fault detection of helical gearboxes, significantly improving diagnostic accuracy and precision. © 2024 IEEE.

关键词： Convolutional neural networks

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Research on modeling and self-excited vibration mechanism in magnetic levitation-collision interface coupling system

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Applied Mathematics and Mechanics(English Edition) 2024年第5期45卷 873-890页

作者： Jinghu TANG Chaofeng LI Jin ZHOU Zhiwei WU School of Mechanical Engineering&Automation Northeastern UniversityShenyang 110819China Key Laboratory of Vibration and Control of Aero-Propulsion Systems of Ministry of Education of China Northeastern UniversityShenyang 110819China School of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

The modeling and self-excited vibration mechanism in the magnetic levitation-collision interface coupling system are *** effects of the control and interface parameters on the system's stability are *** frequency range of self-excited vibrations is investigated from the energy point of *** phenomenon of self-excited vibrations is elaborated with the phase *** corresponding control strategies are briefly analyzed with respect to the vibration *** results show that when the levitation objects collide with the mechanical interface,the system's vibration frequency becomes larger with the decrease in the collision gap;when the vibration frequency exceeds the critical frequency,the electromagnetic system continues to provide energy to the system,and the collision interface continuously dissipates energy so that the system enters the self-excited vibration state.

关键词： magnetic levitation coupling system self-excited vibration mechanical interface vibration frequency

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Object Helps U-Net Based Change Detectors

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 548-550页

作者： Lan Yan Qiang Li Kenli Li College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on ... 详细信息

关键词： Net computer networks

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Resilient time-varying formation optimal tracking for heterogeneous multi-agent systems with coupled constraints

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IEEE Transactions on automation Science and engineering 2025年 22卷 15274-15285页

作者： Su, Lingfei Lin, Zhi Hua, Yongzhao Shi, Zhexin Dong, Xiwang Lu, Jinhu Wang, Danwei Beihang University School of Artificial Intelligence Institute of Artificial Intelligence Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Shenyuan Honors College Beijing100191 China Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Zhongguancun Laboratory Beijing100094 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore

Formation constrained optimal tracking problems for heterogeneous multi-agent systems under Byzantine attacks are studied. The objective of the honest agents, unaffected by Byzantine attacks, is to find optimal trajectories that minimize the cumulative local cost functions of all honest agents, while simultaneously satisfying the cumulative local inequality constraints and maintaining the formation configuration. A distributed resilient formation tracking controller utilizing preview control and primal-dual strategy is proposed without requiring each agent to know which agents are affected by Byzantine attacks. The performance of the proposed algorithm is analyzed in terms of the upper bounds of dynamic regret and constraint violations. Numerical simulations and experiments, involving one unmanned aerial vehicle and four unmanned ground vehicles, are performed to verify the effectiveness of the obtained results. © 2004-2012 IEEE.

关键词： Cost functions

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Intelligent optimisation scheduling of raw material area in sausage production line

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International Journal of Simulation and Process Modelling 2023年第4期20卷 239-254页

作者： Han, Zhonghua Guan, Mingpeng Liu, Hangyu Chang, Daliang Sun, Liangliang School of Electrical and Control Engineering Shenyang Jianzhu University Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences Liaoning Shenyang110017 China School of Control Engineering Northeastern University at Qinhuangdao Hebei Qinhuangdao066099 China

The production process in the raw material area of the sausage production line needs to be further optimised to improve production efficiency and reduce the waiting time for suctioning of emulsifying fillings. In this study, we propose an improved Q-learning method for scheduling in raw material area (RMSPS-IQL). To overcome the problem of low learning efficiency caused by multi-operation and multi-tasking in the production line scheduling process, a priority stranding probability is added to the action selection method based on the epsilon-greedy strategy. In addition, to determine the execution time of the action during continuous working, a stranding action starting control method based on the probability of filling deterioration was designed. Comparative analysis of the results of multiple simulation schemes suggested that the RMSPS-IQL effectively reduces the waiting time for suctioning fillings from emulsifying pot, and improves the productivity of the production line. Copyright © 2023 Inderscience Enterprises Ltd.

关键词： Filling

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Multi‐objective particle swarm optimisation of complex product change plan considering service performance

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 1058-1076页

作者： Ruizhao Zheng Yong Zhang Xiaoyan Sun Faguang Wang Lei Yang Chen Peng Yulong Wang School of Information and Control Engineering China University of Mining and TechnologyXuzhouChina Shenzhen Skyworth RGB Electronics Co. LtdShenzhenChina School of Mechatronic Engineering and Automation Shanghai UniversityShanghaiChina

Design change is an inevitable part of the product development *** study proposes an improved binary multi‐objective PSO algorithm guided by problem char-acteristics(P‐BMOPSO)to solve the optimisation problem of complex product change plan considering service ***,a complex product multi‐layer network with service performance is established for the first time to reveal the impact of change effect propagation on the product service ***,the concept of service performance impact(SPI)is defined by decoupling the impact of strongly associated nodes on the service performance in the process of change affect ***,a triple‐objective selection model of change nodes is established,which includes the three indicators:SPI degree,change cost,and change ***,an integer multi‐objective particle swarm optimisation algorithm guided by problem characteristics is developed to solve the model *** results on the design change problem of a certain type of Skyworth TV verify the effectiveness of the established optimisation model and the proposed P‐BMOPSO algorithm.

关键词： multi‐objective particle swarm optimization product change service performance

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