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International Symposium on system and Software Reliability (ISSSR)

作者： Ming Li Chengjun Shi Puzheng Ji Liyang Xie School of Mechatronics Engineering Shenyang Aerospace University Shenyang China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Shenyang China

ISBN: (数字)9798331501242

ISBN: (纸本)9798331501259

The manufacture of precision long life gears is characterized by high cost and long cycle. Moreover, the fatigue tests of gears are time consuming and labor intensive. In order to obtain the life information of gears accurately and conveniently, a model for predicting the probabilistic life of gears is established by using the concept of the minimum order statistic. Furthermore, the probabilistic life relationship among gears with different numbers of teeth is constructed. The life data of specific gears are taken as the input variables of the model, and through the transformation of the model, the probabilistic life of other gears can be obtained. Meanwhile, a gear bending fatigue test is carried out under a constant stress level, and during the test, the methods for monitoring and evaluating gear failures are expounded. Next, two analysis methods of gear failure mechanism and fracture are combined to present the failure mode, and test data are used to illustrate the guiding significance of the model. Finally, the model is verified by the statistical method of random censored data, which proves that the model has good prediction ability and the advantage of handling a small amount of data.

关键词： Analytical models Gears Predictive models Bending Probability Fatigue Probabilistic logic Data models Reliability Stress

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How Fast Can a Robotic Drummer Beat Using Dielectric Elastomer Actuators?

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IEEE Robotics and Automation Letters 2024年第3期9卷 2638-2645页

作者： Wakle, Sudhir Lin, Tse-Han Huang, Shu Basu, Sumit Lau, Gih-Keong National Yang Ming Chiao Tung University International College of Semiconductor Technology Hsinchu30010 Taiwan Indian Institute of Technology Kanpur Mechanical Engineering Department Kanpur208016 India National Yang Ming Chiao Tung University Department of Graduate Degree Program of Robotics Hsinchu30010 Taiwan Industrial Technology Research Institute Mechanical and Mechatronics System Research Labs Zhudong 31057 Taiwan National Yang Ming Chiao Tung University Department of Mechanical Engineering International College of Semiconductor Technology Hsinchu30010 Taiwan

Fast drumming presents a speed challenge to many robotic arms. To simultaneously meet the needs for speed, stroke, and force, we proposed and tested a new double-saddle dielectric elastomer actuator (DEA) as the artificial biceps for driving a lightweight robotic drummer. This work finds that fast force induction is instrumental to the fast drumming by a DEA-driven drumstick. While a pure-shear series of DEA under a large pre-stretch and lateral reinforcement can generate a large isotonic stroke, it is not fast in isometric force induction. Instead, this work found a double-saddle DEA, which is a degenerated two-segment pure-shear DEA with a middle laterally buckled beam, managed to induce a faster isometric force at a 0.5 s down time constant when its ultimate actuation tapered due to substantial strain stiffening effect. As such, this double-saddle DEA-driven drummer suffered less from the dynamic stroke decrement than the 8-segment DEA did. A 4.4 g DEA managed to swing freely a 7.8 g drumstick up to nearly 60° at 6 kV and a maximum tip speed of up to 0.45 m/s. The drumming frequency upon 5.5 kV activation was up to 2-2.5 Hz. In comparison, an 8-segment pure-shear DEA-driven drummer failed to reach the drum when pulsed at 2 Hz. Interestingly, a slower stroke excited multiple drumbeats due to secondary bounces. To achieve a faster drumming to match a human drummer, it is foreseen that a harder dielectric elastomer material will help drive a faster soft robot. © 2016 IEEE.

关键词： Dielectric materials

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Intelligent system for Classifying of Acoustic Endoscopic Images of the Pancreas Based the Analysis of Walsh Spectra of Local Windows 25

Intelligent System for Classifying of Acoustic Endoscopic Im...

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25th International Arab Conference on Information Technology, ACIT 2024

作者： Al-Kasasbeh, Riad Taha Filist, Sergey Shatalova, Olga Kondrashov, Dmitry Sergeevich Shaqadan, Ashraf Korenevskiy, Nikolay A. Al-Habahbeh, Osama M. Tarawneh, Emad Saleh Starkov, Evgeny The University of Jordan Mechatronics Engineering Department Amman Jordan Moscow Polytechnic University Department of Smart Technologies Moscow Russia Southwest State University Department of Biomedical Engineering Kursk Russia Zarqa University Civil Engineering Department Zarqa Jordan University of Business and Technology Jeddah21448 Saudi Arabia South-West State University Russia The University of Jordan Jordan Institute of System Programming The Russian Academy of Sciences Russia

ISBN: (纸本)9798331540012

The purpose of the work is to develop and study methods and algorithms for intelligent classification systems for digital medical images. A method for automatic classification of medical images was developed using neural networks and transparency masks obtained by preliminary image segmentation. This allows you to generate descriptors only for those pixels that are selected by the transparency mask. Also algorithmic and software for classifying medical images has been developed. Experimental testing was carried out on ultrasound images of the pancreas. Differential diagnostics was carried out on control samples. The classes "oncology"and "pancreatitis"were divided. The diagnostic sensitivity by class turned out to be at least 0.8, while the diagnostic specificity is at least 0.85. © 2024 IEEE.

关键词： Ultrasonic imaging

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Misophonia Sound Recognition Using Vision Transformer

Misophonia Sound Recognition Using Vision Transformer

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： B. Bahmei E. Birmingham S. Arzanpour School of Mechatronics System Engineering Simon Fraser University Surrey Canada Faculty of Education Simon Fraser University Burnaby Canada

Misophonia is a condition characterized by an abnormal emotional response to specific sounds, such as eating, breathing, and clock ticking noises. Sound classification for misophonia is an important area of research since it can benefit in the development of interventions and therapies for individuals affected by the condition. In the area of sound classification, deep learning algorithms such as Convolutional Neural Networks (CNNs) have achieved a high accuracy performance and proved their ability in feature extraction and modeling. Recently, transformer models have surpassed CNNs as the dominant technology in the field of audio classification. In this paper, a transformer-based deep learning algorithm is proposed to automatically identify trigger sounds and the characterization of these sounds using acoustic features. The experimental results demonstrate that the proposed algorithm can classify trigger sounds with high accuracy and specificity. These findings provide a foundation for future research on the development of interventions and therapies for misophonia.

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Optimization of High Aspect Ratio Through Glass Vias Void-Free Filling Using Complex system Response Platform 19

Optimization of High Aspect Ratio Through Glass Vias Void-Fr...

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19th International Microsystems, Packaging, Assembly and Circuits Technology Conference, IMPACT 2024

作者： Fu, Yu-Ting Chang, Yiu-Hsiang Ho, Chih-Ming Yao, Da-Jeng Institute of NanoEngineering and MicroSystems National Tsing Hua University Hsinchu30013 Taiwan Industrial Technology Research Institute Mechanical and Mechatronics System Research Lab Hsinchu310401 Taiwan National Tsing Hua University Department of Power Mechanical Engineering No. 101 Section 2 Guangfu Road Hsinchu City30013 Taiwan

ISBN: (纸本)9798331532246

In advanced packaging field, 3-D integrated circuits have extensive applications in high-density interconnection (HDI) since component arrangement on 2-D planar wafer faces saturation. Through Glass Via (TGV) technology stands out due to its advantageous electrical, optical, and mechanical properties as a substrate. The main challenge in TGV filling is how to form electroplated copper bridge at the high aspect ratio (HAR) TGV midpoint such as, butterfly mode, X-shaped mode, and so on.[1] Periodic pulse reverse (PPR) plating technique is an effective method using in HAR through hole filling, due to advantageous concentration gradient and mass transport profile.[2] However, it is a challenge to find a quantitative output measure of the butterfly or X mode. The other challenge is that N levels for each P parameter in a P parameter pool form a huge NP search space, which impedes to find the global optimal parameter-level combination.[3] To address this, we introduce AI Complex system Response (AI-CSR) platform, which offers insight into the system's response variations across the multidimensional parameter space.[4], [5] For a complex system having P parameters, the CSR function has coefficients. Only [(P2+3P+2)/2] «NP calibration tests are needed to identify the system response, which allow us to identify the optimal parameter combinations and obtain the global maximum. The optimization target is represented by a quantitative system response property, E. This measure, E, is defined as a dimensionless group, translating a two-dimensional geometric requirement into a scalar quantitative output. This crucial step facilitates the application of the AI-CSR platform to achieve butterfly-shaped electroplating. The AI-CSR platform successfully identify the appropriate parameter-level combinations, achieving desired butterfly-mode plating with 'I-shape' (Figure 1-a) as well as effectively preventing voids or seams formation during copper electroplating (Figure 1-b). The optimal

关键词： Aspect ratio

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Line laser measurement, evaluation and utilization of holistic gear deviations

Line laser measurement, evaluation and utilization of holist...

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作者： Shi, Zhaoyao Sun, Yanqiang Yu, Bo Wang, Xiaoyi Zhao, Baoya Beijing Engineering Research Center of Precision Measurement Technology and Instruments Beijing University of Technology Beijing China School of Construction Machinery Shandong Jiaotong University Shandong Jinan China Henan Key Laboratory of Mechanical Design and Transmission System Henan University of Science and Technology Luoyang China School of Mechatronics Engineering North China Institute of Aerospace Engineering Langfang China

The measurement of holistic gear deviations (HGD) is a fast-developing field of gear measurement technology in recent years. Line laser measurement is an effective approach to measure the HGD, and is beginning to be applied. However, compared with the mature conventional gear measurement based on “point” and “line” measurement, the holistic gear deviations measurement is imperfect, especially in acquisition, evaluation and utilization. This paper introduces the line laser measurement model of HGD and puts forward the solutions to the problems such as the determination of the position and attitude parameters of the laser sensor, the influence of the incident angle of the measuring light, and the occlusion of the adjacent gear teeth in the measurement. The representation method of the three-dimensional deviations of the tooth flank is illustrated. According to the HGD, a unified model for calculating the elemental deviations of the gear, such as the involute and helix, is found. The HGD evaluation system is established by means of the statistical analysis method. The full use of the HGD is explored from two aspects of gear process error analysis and gear performance prediction, including tooth flank twist analysis, calculation of gear integrated error (GIE) and transmission error (TE), matching method of large batch of gears, etc. The analysis system of HGD is built on the cloud platform. The measurement, evaluation and utilization of HGD are the key technologies of the next generation gear measurement. © 2025

关键词： Gear Holistic gear deviations Metrology

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A Trajectory Planning Algorithm of Spray Robot for Workpieces with Complex Geometric Features based on 3D Point Cloud 5

A Trajectory Planning Algorithm of Spray Robot for Workpiece...

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5th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2021

作者： Kong, Minxiu Li, Ang Gao, Feng Harbin Institute of Technology School of Mechatronics Engineering Harbin China State Key Laboratory of Robotics and System Harbin China

ISBN: (纸本)9781665415989

Trajectory planning of spray robot for workpieces with complex geometric features is always a challenging problem. Combined with the actual process requirements of surface spraying and edge spraying, a new spraying path design method based on 3D point cloud is proposed in this paper. During surface spraying, the automatic segmentation algorithm of spraying area based on the determination of hole ratio and Euclidean clustering is studied. For the area with dense features, the point cloud slicing algorithm is used to generate the spray path. For the narrow area, the flexible midline extraction algorithm is proposed. We also discussed the edge extraction algorithm to generate the edge spray path. According to the simulation results of coating thickness, this method can not only ensure the uniformity of coating thickness, but also ensure high spraying efficiency with low paint waste. © 2021 IEEE.

关键词： Clustering algorithms

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Mechanical Modelling and Dynamic Characterization of Multi-Rigid-Flexible Planetary systems: Multi-Rigid-Flexible Planetary systems

Mechanical Modelling and Dynamic Characterization of Multi-R...

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Data-driven Optimization of Complex systems (DOCS), International Conference on

作者： Ming Li Bo Fan Wanyu Jiang Liyang Xie School of Mechatronics Engineering Shenyang Aerospace University Shenyang China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Shenyang China

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

Planetary transmission gears are widely used in the aerospace field, yet there is a scarcity of analysis and design tools specifically for planetary systems. In this paper, a three-dimensional dynamic gear tooth mesh load distribution model for planetary gear systems is proposed, which can take into account the influence of factors such as tooth side clearance, gear support stiffness, and tooth surface load distribution on the dynamic root stress of the system. A numerical integration strategy is combined with an elastic contact iteration algorithm to solve the multi-body dynamics solution problem. This approach inherently captures mesh stiffness fluctuations without the need for an empirical mesh stiffness formulation or transfer error excitation of the system. The dynamic root stress response of the parametrically excited system under different gear meshing phase conditions is investigated using this model. The results discussed not only demonstrate that the model in this paper can provide the necessary information for fatigue failure analysis and reliability prediction of planetary systems with multi-scale geometrical variables, but also reinforce the need for such computationally efficient models for design purposes.

关键词： Analytical models Solid modeling Gears Computational modeling Heuristic algorithms Predictive models Aerodynamics Reliability engineering Stress Optimization

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Load Characterization and Fatigue Reliability Prediction of Large Aerospace Planetary Gear

Load Characterization and Fatigue Reliability Prediction of ...

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Data-driven Optimization of Complex systems (DOCS), International Conference on

作者： Ming Li Wanyu Jiang Bo Fan Liyang Xie School of Mechatronics Engineering Shenyang Aerospace University Shenyang China Key Laboratory of Vibration and Control of Aero-Propulsion System Ministry of Education Northeastern University Shenyang China

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

The reliability level of large aviation planetary mechanisms, serving as the cornerstone and essential component for various heavy aircraft transmission systems, significantly impacts aircraft affordability and service safety. Before predicting the fatigue performance of the gear transmission system, it is necessary to develop a comprehensive simulation model of the gear system and calculate the stress values for failure modes such as tooth contact fatigue and tooth root bending fatigue. In addition, By using hierarchical finite element technology, the coupling effect of the global elastic behavior of the system on the fatigue load history of the gear teeth is analyzed in depth, and accurate calculations are carried out based on this to fit the probability fatigue strength of the gear teeth. This provides both economical and efficient load and strength input variables for the construction of the system reliability prediction model, and innovatively establishes a new series system reliability model. Finally, the computational findings from the new model is contrasted with the traditional one to show the superiority of the proposed model.

关键词： Gears Computational modeling Interference Predictive models Fatigue Finite element analysis Software reliability Reliability Stress Load modeling

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Optimizing Multi-Agent system Swarm Performance Through Explainable AI

Optimizing Multi-Agent System Swarm Performance Through Expl...

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mechatronics and Robotics engineering (ICMRE), International Conference on

作者： Shekhar Mahmud Mustafa Kutlu Alper Turan Alan System Engineering Department Military Technological College Muscat Oman Mechatronics Engineering Department Sakarya University of Applied Sciences Sakarya Turkey Computer Science & Cybersecurity Department International University of Kuwait Kuwait City Kuwait

ISBN: (数字)9798331509293

ISBN: (纸本)9798331509309

Advancements in multi-agent systems (MAS) have enabled swarm-based systems to perform decentralized decision-making and autonomous tasks. However, optimizing their performance while ensuring transparency and interpretability remains a challenge. This paper introduces a framework that combines Bayesian optimization with Explainable Artificial Intelligence (XAI) techniques to enhance both the efficiency and transparency of MAS swarms. The Bayesian optimization framework fine-tunes agent parameters to improve swarm metrics such as energy efficiency, task completion time, and coordination success. The experimental results show significant improvements: a 25% increase in the coordination success rate, a 15% increase in energy efficiency, and a 20 % reduction in task completion time. XAI techniques, including SHAP values, provide interpretable explanations for optimization decisions, improving user trust and understanding. This study demonstrates the efficacy of integrating Bayesian optimization with XAI to create transparent, efficient, and reliable MAS swarms. Future work should address scalability and implications in dynamic environments.

关键词： Measurement mechatronics Explainable AI Scalability Robot kinematics Energy efficiency Bayes methods Reliability Optimization Multi-agent systems

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