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Development of a Method for Detecting Cutting Points of Wilted Leaves Using 2D Image Keypoints and 3D Point Cloud

Journal of Institute of Control, Robotics and Systems 2024年第11期30卷 1237-1244页

作者： Kang, Byeong Chang Jung, Ho Won Kim, Jong Hyeong Department of Mechanical Design and Robot Engineering Seoul National University of Science and Technology Korea Republic of Department of Mechanical System and Design Engineering Seoul National University of Science and Technology Korea Republic of

In agriculture, removing withered leaves is crucial for maintaining crop quality and preventing pests and diseases. This paper proposes a method for estimating the pose of wilted leaves and removing wilted leaves. While estimating precisely 3D location and pose information is essential for this task, most of previous methods for pose estimation have difficulty in processing time due to the complexity of feature extraction from 3D point cloud. The proposed method utilizes the YOLOv8 keypoint detection model to obtain image information, and YOLOv7 instance segmentation to isolate the region of interest. We calculate the 3D coordinates of the cutting point and the 3D rotation of the wilted leaf by applying RANSAC plane fitting and projection on 3D point cloud, simplifying the information required for the task. The method was validated using five types of model plant pots, achieving an average processing time of 98.584 ms and an accuracy of 3.83 mm. Additionally, the method recorded a 78% success rate in the removal of withered leaves. © 2024, Institute of Control, Robotics and Systems. All rights reserved.

关键词： Machine vision

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Microstructure transformations and improving wear resistance of austenitic stainless steel additively fabricated by arc-based DED process

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Defence technology（防务技术） 2024年第8期38卷 194-204页

作者： Ashish Yadav Manu Srivastava Prashant K.Jain Sandeep Rathee Hybrid Additive Manufacturing Laboratory Mechanical Engineering DepartmentPDPM Indian Institute of Information TechnologyDesign&ManufacturingJabalpur482005Madhya PradeshIndia FFF Laboratory Mechanical Engineering DepartmentPDPM Indian Institute of Information TechnologyDesign&ManufacturingJabalpur482005Madhya PradeshIndia Department of Mechanical Engineering National Institute of TechnologySrinagarIndia

In this study, austenitic stainless steel(ASS) was additively fabricated by an arc-based direct energy deposition(DED) technique. Macrostructure, microstructure, mechanical characteristics at different spatial orientations(0°, 90°, and 45°), and wear characteristics were evaluated at the deposited structure top, middle, and bottom regions. Results show that austenite(γ) and delta-ferrite(δ) phases make up most of the microstructure of additively fabricated SS316LSi steel. Within γ matrix, δ phase is dispersed both(within and along) grain boundaries, exhibiting a fine vermicular morphology. The bottom, middle,and top regions of WAAM deposited ASS exhibit similar values to those of wrought SS316L in the tensile and impact test findings. Notably, a drop in hardness values is observed as build height increases. During SEM examinations of fractured surfaces from tensile specimen, closed dimples were observed, indicating good ductility of as-built structure. Wear test findings show signs of mild oxidation and usual adhesive wear. By depositing a mechanically mixed composite layer, an increase in the oxidation percentage was discovered to facilitate healing of worn surfaces. The findings of this study will help in design, production and renovation of products/components that are prone to wear. WAAM-deposited ASS has remarkable strength and ability to withstand impacts;it can be used in the production of armour plates for defence applications, mainly military vehicles and aircraft.

关键词： Metal additive deposition Defence applications Arc-based DED Characterization Wear behaviour Fractography

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Experimental study of 3D printed carbon fibre sandwich structures for lightweight applications

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Defence technology（防务技术） 2024年第6期36卷 71-77页

作者： Solaiprakash Vellaisamy Raguraman Munusamy Department of Mechanical Engineering Indian Institute of Information Technology Design and ManufacturingKancheepuramChennai600127India School of Interdisciplinary Design and Innovation Indian Institute of Information Technology Design and ManufacturingKancheepuramChennai600127India

Honeycomb sandwich structures are widely used in lightweight ***,these structures are subjected to extreme loading conditions,leading to potential failures due to delamination and debonding between the face sheet and the honeycomb ***,the present study is focused on the mechanical characterisation of honeycomb sandwich structures fabricated using advanced 3D printing *** continuous carbon fibres and ONYX-FR matrix materials have been used as raw materials for 3D printing of the specimens needed for various mechanical characterization testing;ONYX-FR is a commercial trade name for flame retardant short carbon fibre filled nylon filaments,used as a reinforcing material in Morkforged 3D *** and flatwise compression tests have been conducted for different configurations of honeycomb sandwich structures,fabricated by varying the face sheet thickness and core cell size,while keeping the core cell thickness and core height *** on these tests,the proposed structure with face sheet thickness of 3.2 mm and a core cell size of 12.7 mm exhibited the highest energy absorption and prevented delamination and debonding ***,3D printing technology can also be considered as an alternative method for sandwich structure ***,detailed parametric studies still need to be conducted to meet various other structural integrity criteria related to the lightweight applications.

关键词： 3D printed composite Honeycomb sandwich Edgewise compression Flatwise compression Lightweight

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Microstructure and mechanical behavior of AXM Mg alloy systems—A review

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Journal of Magnesium and Alloys 2024年第7期12卷 2624-2646页

作者： N.Thanabal R.Silambarasan P.Seenuvasaperumal Dudekula Althaf Basha A.Elayaperumal School of Mechanical Engineering Vellore Institute of TechnologyVellore 632014India Department of Metallurgical Engineering and Materials Science Indian Institute of Technology IndoreIndore 453552India Department of Mechanical Engineering Engineering Design DivisionCEG CampusAnna UniversityChennai 600025India

Automobiles are the inevitable mode of ***,increasing fuel prices and carbon dioxide emissions are posing a serious threat to automobile users and the ***,the development of new lightweight materials has been a key area of ***-based commercial alloys(AZ and ZK series alloys)are the lightest among all structural ***,there is still a question about the replacement of Aluminum-based alloys due to HCP crystal *** this connection,Mg-Al-Ca-Mn(AXM)Mg alloy can be a choice as an alternative to the existing Mg-based commercial alloys for structural *** contains(Al,Mg)_(2)Ca,Al_(2)Ca,Mg_(2)Ca,and Al_(8)Mn_(5)as the secondary phases,contributing to the microstructural refinement and property ***,the formation of those precipitates depends on the amount of Al,Ca,and Mn,especially,the Ca/Al *** addition,the secondary processes influence the grain refinement and property enhancement of texture ***,this review article focuses on elaborating on the significance of the Ca/Al ratio for the precipitate formation,secondary process,and texture *** co-segregation behavior of other micro-alloying elements like Cerium,Lanthanum,and Zinc in AXM Mg alloy systems has also been discussed for property enhancement.

关键词： AXM Mg alloy Rolling Extrusion Texture

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Microstructure and mechanical Properties of Friction Stir Welded Al–Mg–Si Alloys Under Variable Parameter Conditions

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Journal of The Institution of Engineers (India): Series D 2024年第2期105卷 1081-1092页

作者： Srivastava, Manu Khan, Nasir Nabi, Shazman Rathee, Sandeep Department of Mechanical Engineering PDPM Indian Institute of Information Technology Design and Manufacturing Jabalpur India Department of Mechanical Engineering Amity University Madhya Pradesh Gwalior India Department of Mechanical Engineering National Institute of Technology Srinagar Jammu and Kashmir India

The current study investigates the variation of mechanical properties and microstructural evolution with varying process parameters for Al–Mg–Si (AA6061-T6) alloys during friction stir welding (FSW) process. The experiments were designed using Taguchi’s technique, with three tool factors being examined—rotational speed (RST), traverse speed (TST), and shoulder diameter (SDT)—at three different levels each. L27 Orthogonal array has been utilized to analyze the effect of these parameters upon mechanical strength. Experimental results were analyzed both quantitatively and qualitatively, with statistical techniques being used for quantitative analysis, and microstructural evolution being used for qualitative analysis. The study found that traverse speed of tool had the most significant effect on ultimate tensile strength, with a contribution of 25.94%, followed by shoulder diameter of tool (25.86%) and rotational speed of tool (20.30%). Furthermore, the study found that the interactions between selected parameters had a significant impact on mechanical strength. Interaction between TST and SDT contributed 14.10%, that between RST*TST contributed 6.51% and the least contribution is between RST and SDT which is around 3.10%. Results of mechanical strength were found to agree with observations related to microstructural analysis for the FSW joints. © The Institution of Engineers (India) 2023.

关键词： Friction stir welding

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Guest Editorial: Generative AI Based Robotics

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Journal of Institute of Control, Robotics and Systems 2025年第5期31卷 461-462页

作者： Lee, Deok-Jin Oh, Hyondong Lim, Dong-Won School of Mechanical Design Engineering Jeonbuk National University Korea Republic of Department of Mechanical Engineering Ulsan National Institute of Science and Technology Korea Republic of Department of Mechanical Engineering The University of Suwon Korea Republic of

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Machine-learned wearable sensors for real-time hand-motion recognition: toward practical applications

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National Science Review 2024年第2期11卷 231-263页

作者： Kyung Rok Pyun Kangkyu Kwon Myung Jin Yoo Kyun Kyu Kim Dohyeon Gong Woon-Hong Yeo Seungyong Han Seung Hwan Ko Department of Mechanical Engineering Seoul National University IEN Center for Human-Centric Interfaces and Engineering Institute for Electronics and NanotechnologyGeorgia Institute of Technology School of Electrical and Computer Engineering Georgia Institute of Technology Department of Chemical Engineering Stanford University Department of Mechanical Engineering Ajou University George W.Woodruff School of Mechanical Engineering Georgia Institute of Technology Institute of Advanced Machinery and Design(SNU-IAMD) Seoul National University

Soft electromechanical sensors have led to a new paradigm of electronic devices for novel motion-based wearable applications in our daily lives. However, the vast amount of random and unidentified signals generated by complex body motions has hindered the precise recognition and practical application of this technology. Recent advancements in artificial-intelligence technology have enabled significant strides in extracting features from massive and intricate data sets, thereby presenting a breakthrough in utilizing wearable sensors for practical applications. Beyond traditional machine-learning techniques for classifying simple gestures, advanced machine-learning algorithms have been developed to handle more complex and nuanced motion-based tasks with restricted training data sets. Machine-learning techniques have improved the ability to perceive, and thus machine-learned wearable soft sensors have enabled accurate and rapid human-gesture recognition, providing real-time feedback to users. This forms a crucial component of future wearable electronics, contributing to a robust human–machine interface. In this review, we provide a comprehensive summary covering materials, structures and machine-learning algorithms for hand-gesture recognition and possible practical applications through machine-learned wearable electromechanical sensors.

关键词： wearable sensor soft electronics artificial intelligence machine learning human–machine interfaces gesture recognition

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Achieving high precision and productivity in laser machining of Ti6Al4V alloy: A comprehensive study using a n-predictor polynomial regression model and PSO algorithm

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International Journal of Lightweight Materials and Manufacture 2025年第1期8卷 127-140页

作者： Chetry, Avinash Phalke, Sandesh Sanjeev Nandy, Arup Department of Mechanical Engineering Indian Institute of Technology Guwahati Assam Guwahati India Department of Design Indian Institute of Technology Guwahati Assam Guwahati India

Ti-6Al-4V, the Titanium alloy, has significant utilizations in aerospace, automotive, and marine sectors for its low density and high strength at elevated temperature. But its chemical activity and low thermal conductivity inhibits its machining by conventional method. Nd: YAG laser beam machining (LBM) finds extensive use in rapid and precise cutting of Ti6Al4V. This study has examined the influences of various LBM machining variables, including laser power, gas pressure and stand-off distance, in cutting 5 mm thick Ti-6Al-4V plate. In assessing the effectiveness and performance of the LBM process, three response functions—surface roughness, angle of kerf, and material removal rate—have been designated. From the experimental data, different regression models have been established to estimate these response functions in terms of the machining parameters. Based on R2 score and RMSE, multi-dimensional polynomial regression is decided as the most suitable regression model. Subsequently, the Particle Swarm Optimization technique has been applied to identify the optimal machining parameters for reducing angle of kerf and surface roughness, while increasing material removal rate. Three individual single-objective functions underwent optimization, along with a multi-objective function. Furthermore, experimental verification was conducted for the optimal input parameters in the single-objective as well as the multi-objective optimization scenarios, resulting in an accuracy of 97% and 98%, respectively. Such a close agreement emphasizes the accuracy of the developed regression model as well as it signifies the reliability and efficacy of the optimization technique. © 2024 The Authors

关键词： Titanium alloys

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Development of an Effective Chatter Control System for an End Mill Spindle Tool System

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Journal of The Institution of Engineers (India): Series C 2024年第5期105卷 1065-1081页

作者： Raju, C. Trivikrama Hussain, S. Jakeer Yedukondalu, G. Galal, Ahmed M. Department of Mechanical Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Guntur India Department of Mechanical Engineering Mother Teresa Institute of Science and Technology Sathupally India Production Engineering and Mechanical Design Department Faculty of Engineering Mansoura University Mansoura Egypt

Excessive chatter during the machining process reduces productivity and increases manufacturing costs. This disruption slows material removal, thereby decreasing operational efficiency and output. To increase the efficiency in cutting operations, dynamic stability, active structural control methods are the best way to get effective results. In the present paper integrated spindle tool systems are modelled using finite element methods by using the Timoshenko beam theory with shear and rotational deformation effects. To achieve the maximized average stable depth of cut for an end milling process while simultaneously minimizing chatter vibration levels, both semi-active and active control strategies have been investigated. Machining experiments performed on Al6061-alloy specimens and provide an empirical confirmation of the stability boundaries. Vibration levels and optical microscope images are considered, to identify chatter marks under various machining conditions, which helps to assure cutting process stability. A proportional derivative controller method is applied at the interface of the spindle tool to control the cutting forces at different cutting conditions. Stability lobe diagrams are plotted with these derived conditions and observed at an incremental level in the axial depths of cutting. The methodology presented in this paper improves the stability in machining of alloy materials with the reduction in the tool tip vibrations. © The Institution of Engineers (India) 2024.

关键词： Milling (machining)

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Integrated Walking Control Strategy With Model Predictive Control and Whole–body Control Using Deep Learning–based State Estimator

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Journal of Institute of Control, Robotics and Systems 2024年第10期30卷 1139-1146页

作者： Jeon, Sanghyeon Kwon, Na-Hyun Ha, Seong-Min Kim, Jung-Yup Department of Mechanical Design and Robot Engineering Seoul Nat’l Univ. of Science and Technology Korea Republic of

This paper proposes a walking strategy that integrates Model Predictive Control (MPC) and Whole-Body Control (WBC) based on a single rigid body model. Additionally, it develops and utilizes a novel state estimator based on LSTM deep learning instead of the commonly used Kalman filter–based state estimator. MPC and WBC are methods that enable walking robots to perform various tasks without falling. Therefore, this study uses MPC based on a single rigid body model to derive the optimal ground reaction force. Subsequently, in WBC, constraints are added to satisfy robot dynamics equations and track the optimal ground reaction force. Finally, through WBC, the optimal joint torque is computed considering whole-body floating dynamics and optimal ground reaction forces. All of these computations are performed based on the newly developed deep learning–based state estimator. The proposed control strategy is validated through Gazebo simulation using a quadruped walking robot, Go2. © ICROS 2024.

关键词： State estimation

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