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System Reliability and Safety engineering (SRSE), International Conference on

作者： Ruiqi Li Kai Wang Peng Zeng Jiwei Cao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Department of Electrical Engineering Harbin Institute of Technology China

Active magnetic bearings (AMBs) have many advantages over traditional oil bearings due to their non-contact characteristics. They are environmentally friendly solution and have been proven to be highly reliable and available. Electromagnetic coils are vital components of AMB and they are failure prone. In this paper, the failure mode of magnetic bearing coil and its corresponding failure mechanism are reviewed by FMMEA method, and the existing coil fault diagnosis methods are introduced. Future directions for coil insulation health monitoring aiming at the application characteristics of AMBs are also discussed.

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Possibilities of Changing the Transport Characteristics of the TEP70 Locomotive 27

Possibilities of Changing the Transport Characteristics of t...

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27th International Workshop on Electric Drives: MPEI department of Electric Drives 90th Anniversary, IWED 2020

作者： Rjabtsikov, Viktor Rassolkin, Anton Vaimann, Toomas Kallaste, Ants Lukichev, Dmitry V. Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia ITMO University Faculty of Control Systems and Robotics St. Petersburg Russia

ISBN: (纸本)9781728141589

The research concentrates on the modernization issues of diesel-electric passenger locomotives TEP70. There is number of TEP70 locomotives in Baltic region that are used very rarely by their direct application but may as well be usable as freight locomotives. The main goal of the study is to change the tractive force of a TEP70 locomotive to be able to transport cargo in the Baltic region. Analysis of TEP70 working principles and load characteristics are presented. Based on the analytical model of locomotive, suggestion to replace the gearbox to increase locomotive pulling capability is proposed. Moreover, the paper presents calculation of the traction effort of TEP70. That kind of calculations are very important for motion planning and it should be done in order to avoid overloading during the working mode of the locomotive. © 2020 IEEE.

关键词： Engines

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Knowledge-aware Graph Transformer for Pedestrian Trajectory Prediction

Knowledge-aware Graph Transformer for Pedestrian Trajectory ...

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International Conference on Intelligent Transportation

作者： Yu Liu Yuexin Zhang Kunming Li Yongliang Qiao Stewart Worrall You-Fu Li He Kong Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology (SUSTech) Shenzhen China Department of Mechanical Engineering City University of Hong Kong Hong Kong SAR China School of Automation Guangdong Polytechnic Normal University Guangzhou China Australian Centre for Field Robotics The University of Sydney NSW Australia Australian Institute for Machine Learning The University of Adelaide SA Australia Department of Mechanical Engineering City University of Hong Kong Hong Kong SAR China Shenzhen Key Laboratory of Control Theory and Intelligent Systems SUSTech Shenzhen China Guangdong Provincial Key Laboratory of Human-Augmentation Rehabilitation Robotics in Universities SUSTech Shenzhen China

Predicting pedestrian motion trajectories is crucial for path planning and motion control of autonomous vehicles. Accurately forecasting crowd trajectories is challenging due to the uncertain nature of human motions in different environments. For training, recent deep learning-based prediction approaches mainly utilize information like trajectory history and interactions between pedestrians, among others. This can limit the prediction performance across various scenarios since the discrepancies between training datasets have not been properly incorporated. To overcome this limitation, this paper proposes a graph transformer structure to improve prediction performance, capturing the differences between the various sites and scenarios contained in the datasets. In particular, a self-attention mechanism and a domain adaption module have been designed to improve the generalization ability of the model. Moreover, an additional metric considering cross-dataset sequences is introduced for training and performance evaluation purposes. The proposed framework is validated and compared against existing methods using popular public datasets, i.e., ETH and UCY. Experimental results demonstrate the improved performance of our proposed scheme.

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Main Faults and Diagnostic Possibilities of BLDC Motors 27

Main Faults and Diagnostic Possibilities of BLDC Motors

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27th International Workshop on Electric Drives: MPEI department of Electric Drives 90th Anniversary, IWED 2020

作者： Kudelina, Karolina Asad, Bilal Vaimann, Toomas Rassolkin, Anton Kallaste, Ants Lukichev, Dmitri V. Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia ITMO University Faculty of Control Systems and Robotics St. Petersburg Russia

ISBN: (纸本)9781728141589

This paper presents the main faults of brushless DC motors and their diagnostic possibilities. Due to the popularity gain of such devices in the past decade, the maintenance and diagnostic of such machines is getting more important. As the machines are used in various applications, they are often critical parts of devices. Due to this, the unexpected failures of such machines are undesired and are to be avoided. The main faults of the machines are listed, some possibilities of their monitoring and diagnostics have been addressed. The necessity of further study has been pointed out. © 2020 IEEE.

关键词： Brushless DC motors

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Simulation of Wind Turbine Vibrations 27

Simulation of Wind Turbine Vibrations

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27th International Workshop on Electric Drives: MPEI department of Electric Drives 90th Anniversary, IWED 2020

作者： Andriushchenko, Ekaterina Kallaste, Ants Vaimann, Toomas Rassolkin, Anton Heidari, Hamidreza Demidova, Galina L. Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia ITMO University Faculty of Control Systems and Robotics St. Petersburg Russia

ISBN: (纸本)9781728141589

In recent years, there has been an increasing interest in renewable energy. Particularly, wind energy is gaining more and more popularity in many countries. However, the main obstacles to wind turbines usage are the vibration and noise close to wind farms. Therefore, this paper is focused on developing a new method for mathematical simulation of vibrations of a wind turbine in order to find out and reduce the vibration level. Particularly, low-frequency vibration of a wind turbine, composed of a tower and rotor in the out-of-balance condition is considered. The proposed method of vibration simulation is based on the theory of elastic beams and the general vibration theory. The calculations are made for a wind turbine VTR 50 Arctic. The results of the calculations are the displacement of the tower top and the stress at the tower foundation. Furthermore, it is worth emphasizing that the method is quite flexible. It allows adding complexity into the system, for instance, external loads such as wind pressure, aerodynamic loads, seismic loads or operational loads. © 2020 IEEE.

关键词： Wind power

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Full-pose Trajectory Tracking of Overactuated Multi-Rotor Aerial Vehicles with Limited Actuation Abilities

TechRxiv

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TechRxiv 2023年

作者： Hamandi, Mahmoud Al-Ali, Ismail Seneviratne, Lakmal Franchi, Antonio Zweiri, Yahya The Department of Aerospace Engineering Khalifa University of Science and Technology Abu Dhabi United Arab Emirates The Department of Mechanical Engineering Khalifa University Abu Dhabi United Arab Emirates Khalifa University of Science and Technology Abu Dhabi United Arab Emirates The Robotics and Mechatronics Lab Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Enschede Netherlands The Department of Computer Control and Management Engineering Sapienza University of Rome Rome00185 Italy LAAS CNRS Université de Toulouse Toulouse31000 France Khalifa University Abu Dhabi United Arab Emirates Center for Artificial Intelligence and Robotics New York University Abu Dhabi Saadiyat Island Abu Dhabi129188 United Arab Emirates

This paper presents a novel optimization-based full-pose trajectory tracking method to control overactuated multirotor aerial vehicles with limited actuation abilities. The proposed method allocates feasible control inputs to track a reference trajectory, while ensuring the tracking of the reference position, and while tracking the closest feasible attitude. The optimization simultaneously searches for a feasible trajectory and corresponding feasible control inputs from the infinite possible solutions, while ensuring smooth control inputs. The proposed real-time algorithm is tested in extensive simulation on multiple platforms with fixed and actuated propellers. The simulation experiments show the ability of the proposed approach to exploit the complex set of feasible forces and moments of overactuated platforms while allocating smooth feasible control inputs. © 2023, CC BY.

关键词： Trajectories

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Automated Leukemia Screening and Sub-types Classification Using Deep Learning

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Computer Systems Science & engineering 2023年第9期46卷 3541-3558页

作者： Chaudhary Hassan Abbas Gondal Muhammad Irfan Sarmad Shafique Muhammad Salman Bashir Mansoor Ahmed Osama M.Alshehri Hassan H.Almasoudi Samar M.Alqhtani Mohammed M.Jalal Malik A.Altayar Khalaf F.Alsharif Department of Computer Science COMSATS University Islamabad44000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Control Automotive and Robotics LabNational Center of Robotics and Automation(NCRA HEC)MirpurPakistan Mirpur University of Science and Technology(MUST)MirpurPakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Clinical Laboratory Sciences College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of Medical Laboratory Technology Faculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia Department of Clinical Laboratory Sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human *** produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells(RBCs)and white blood cells(WBC),and *** can be diagnosed manually by taking a complete blood count test of the patient’s blood,from which medical professionals can investigate the signs of leukemia ***,two other methods,microscopic inspection of blood smears and bone marrow aspiration,are also utilized while examining the patient for ***,all these methods are labor-intensive,slow,inaccurate,and require a lot of human experience and *** authors have proposed automated detection systems for leukemia diagnosis to overcome these *** have deployed digital image processing and machine learning algorithms to classify the cells into normal and blast ***,these systems are more efficient,reliable,and fast than previous manual diagnosing ***,more work is required to classify leukemia-affected cells due to the complex characteristics of blood images and leukemia cells having much intra-class variability and inter-class *** this paper,we have proposed a robust automated system to diagnose leukemia and its *** have classified ALL into its sub-types based on FAB classification,i.e.,L1,L2,and L3 types with better *** have achieved 96.06%accuracy for subtypes classification,which is better when compared with the state-of-the-art methodologies.

关键词： Healthcare cancer detection deep learning convolutional neural network

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Modem mechatronics and robotics education program: Border cooperation between estonia and Russia 11

Modem mechatronics and robotics education program: Border co...

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11th IEEE Global engineering Education Conference, EDUCON 2020

作者： Rassolkin, Anton Vaimann, Toomas Kudelina, Karolina Demidova, Galina L. Lukichev, Dmitry V. Perepelkina, Svetlana Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Itmo University Faculty of Control Systems and Robotics St. Petersburg Russia

ISBN: (纸本)9781728109305

The paper describes the interaction between Tallinn University of Technology (TalTech, Tallinn, Estonia) and ITMO University (St. Petersburg, Russia) based on recently signed agreement. The purpose of the agreement is to record the intention of TalTech and ITMO University to cooperate on implementing a double master's degree program, which involves confirmation of the master's educational level absorption and the award of master's degree and obtention of two diplomas, and to outline the organizational form, principles and terms of the implementation. The double degree Program is a two-year Master's program of 120 ECTS credit points. Its structure and content meets the requirements that both TalTech and ITMO University have established for their master's programs, in accordance with the government standards. Development and approval of the double degree Program is held by the Parties in accordance with the procedures established by them. This paper describes the procedure of implementation of a double-degree master program in mechatronics engineering. © 2020 IEEE.

关键词： engineering education

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A Generic Single-Source Domain Generalization Framework for Fault Diagnosis via Wavelet Packet Augmentation and Pseudo-Domain Generation

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IEEE Internet of Things Journal 2025年

作者： Sun, Yawei Tao, Hongfeng Ni, Yuanzhi Stojanovic, Vladimir Wuxi214122 China University of Kragujevac Faculty of Mechanical and Civil Engineering Department of Automatic Control Robotics and Fluid Technique Kraljevo36000 Serbia

During real-time production in industrial Internet of Things systems, equipment changes its operating speed due to changing operating conditions. And dynamic speed changes of rotating machinery under fluctuating workloads often lead to domain changes of vibration signals, which will directly lead to degradation of fault diagnostic model performance. Furthermore, the acquisition of data from multiple domains in real industrial scenarios is challenging due to the expense of collecting data from all possible working conditions. Consequently, applying diagnostic models trained using a single-source domain directly to an unknown target domain is a very challenging single domain generalization problem. Therefore, a generic single-source domain generalization framework via wavelet packet augmentation and pseudo-domain generation for fault diagnosis under unknown operating conditions is proposed in this paper. Pseudo-domain generation involves augmenting single-source domain by integrating data generetion model, thereby enhancing prediction accuracy. Furthermore, a wavelet packet augmentation method is proposed. Initially, the original signal is decomposed to obtain high and low frequency information. Subsequently, the high and low frequency information within the batch are linearly interpolated, respectively. Consequently, the interpolated high and low frequency information is then reconstructed to yield enhanced samples. The experimental results on four datasets show that the proposed framework can effectively improve the robustness of the generalization ability of fault diagnosis under unknown operating environments. © 2014 IEEE.

关键词： Wavelet analysis

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Quadrotor Autonomous Landing on Moving Platform

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Procedia Computer Science 2022年 209卷 40-49页

作者： Pengyu Wang Chaoqun Wang Jiankun Wang Max Q.-H. Meng Shenzhen Key Laboratory of Robotics Perception and Intelligence Shenzhen China Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China School of Control Science and Engineering Shandong University Jinan China Jiaxing Research Institute Southern University of Science and Technology Jiaxing China Department of Electronic Engineering The Chinese University of Hong Kong Hong Kong China Shenzhen Research Institute of the Chinese University of Hong Kong China

This paper introduces a quadrotor's autonomous take-off and landing system on a moving platform. The designed system addresses three challenging problems: fast pose estimation, restricted external localization, and effective obstacle avoidance. Specifically, first, we design a landing recognition and positioning system based on the AruCo marker to help the quadrotor quickly calculate the relative pose; second, we leverage a gradient-based local motion planner to generate collision-free reference trajectories rapidly for the quadrotor; third, we build an autonomous state machine that enables the quadrotor to complete its take-off, tracking and landing tasks in full autonomy; finally, we conduct experiments in simulated, real-world indoor and outdoor environments to verify the system's effectiveness and demonstrate its potential.

关键词： Autonomous landing Quadrotor Motion planning

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