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2023 Low-Cost Digital Solutions for Industrial automation, LoDiSA 2023

作者： Merino, Jorge Ikeuchi, Daiki Moretti, Nicola Mukerjee, Anandarup Li, Luning Karatzas, Stylianos Pattinson, Sebastian Parlikad, Ajith Distributed Information and Automation Laboratory Department of Engineering University of Cambridge Institute for Manufacturing Alan Reece Building 17 Babbage Road Cambridge United Kingdom Computer Aided Manufacturing Laboratory Department of Engineering University of Cambridge Trumpington Street CambridgeCB2 1PZ United Kingdom

Human exposure to poor air quality is a leading risk factor in the Global Burden of Disease (GBD) study, estimating 22,000 premature deaths related to indoor air pollution in 2019 in Europe. Diverse pollutants are found in manufacturing environments resulting from both combustion and non-combustion sources, including Particulate Matter and Volatile Organic Compound. Internet of Things (IoT) air quality monitoring can enhance awareness and support informed decision making towards better air quality. However, hardware sensors are not always capable of monitoring particular characteristics and behaviour of a pollutant, for instance, spatial limitations may impede deploying sensors close enough to the source of the pollutant. Virtual Sensors can extend hardware sensing options via signal processing and data integration. This paper presents an architecture for training and deploying virtual sensors. A virtual sensor is implemented using the architecture in the context of additive manufacturing to estimate the production of Volatile Organic Compounds (VOCs) of 3D printers and their transfer into the rest of the space. In the case study, the 3D printers are installed inside cabinets to limit the transfer of pollutants to the exterior. Several of these virtual sensors are deployed to monitor the VOCs produced by the 3D printers and the transfer rate out of the cabinets. The paper includes some early results and initial insights on the accuracy and usefulness of virtual sensors. Virtual Sensors can be cost-effective solutions when monitoring systems are escalated by reducing number of hardware sensors and complexity. © 2023 IET Conference Proceedings. All rights reserved.

关键词： 3D printing

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Interactive Navigation in Environments with Traversable Obstacles Using Large Language and Vision-Language Models

Interactive Navigation in Environments with Traversable Obst...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Zhen Zhang Anran Lin Chun Wai Wong Xiangyu Chu Qi Dou K. W. Samuel Au Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Multiscale Medical Robotics Centre Department of Computer Science and Engineering The Chinese University of Hong Kong Computer Aided Medical Procedures Technical University of Munich Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper proposes an interactive navigation framework by using large language and vision-language models, allowing robots to navigate in environments with traversable obstacles. We utilize the large language model (GPT-3.5) and the open-set Vision-language Model (Grounding DINO) to create an action-aware costmap to perform effective path planning without fine-tuning. With the large models, we can achieve an end-to-end system from textual instructions like "Can you pass through the curtains to deliver medicines to me?", to bounding boxes (e.g., curtains) with action-aware attributes. They can be used to segment LiDAR point clouds into two parts: traversable and untraversable parts, and then an action-aware costmap is constructed for generating a feasible path. The pre-trained large models have great generalization ability and do not require additional annotated data for training, allowing fast deployment in the interactive navigation tasks. We choose to use multiple traversable objects such as curtains and grasses for verification by instructing the robot to traverse them. Besides, traversing curtains in a medical scenario was tested. All experimental results demonstrated the proposed framework’s effectiveness and adaptability to diverse environments.

关键词： Training Point cloud compression Laser radar Navigation Grounding Large language models Path planning

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Experimental and Numerical Study of Airborne Contaminants Transmission in Hospital Isolation Rooms Equipped with Protected Zone Ventilation

SSRN

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SSRN 2024年

作者： Fečer, Tomáš Aganovic, Amar Bi, Yang Larkermani, Elyas Georges, Laurent Plášek, Josef Rekstad, Inge Håvard Mathisen, Hans Martin Cao, Guangyu Department of Energy and Process Engineering Norwegian University of Science and Technology - NTNU Trondheim Norway Department of Automation and Process Engineering UiT The Arctic University of Norway Tromsø Norway Institute of Computer Aided Engineering and Computer Science Brno University of Technology Brno Czech Republic

Experimental tests have been conducted in the small test chamber at the Norwegian University of Science and Technology. The purpose has been to examine air flow path and airborne pollutant distribution, in the case study of an airborne infection isolation room (AIIR) configuration. This configuration uses the concept of protected zone ventilation (PZV) including a combination of a localised air supply system and an air curtain at four air change rates per hour (6, 9, 12, 15) and two negative pressure differences between the outside and inside of the isolation room (2.5 Pa and 5 Pa). In this study, three scenarios, (a) without an air supply curtain, (b) with the 45° and (c) with the 90° air supply curtain, were investigated experimentally and numerically. The N2O tracer gas was employed to simulate airborne transmission of infectious agents throughout the experiment. In the CFD simulation, viscous effects have been included using the (RNG) k–Ε turbulence model with species transport model. The simulated domain has been meshed using the structured mesh with hexagonal cells and with a uniform resolution of 0.0175m, resulting in a total of over 6 million cells. The scenario with the 45° supply air curtain significantly decreased the gas concentration already at 6 air change rates per hour. At the same time, the negative pressure difference of 2.5 Pa had the lower gas concentration in two scenarios (a) and (b) while 5.0 Pa in scenario (c). © 2024, The Authors. All rights reserved.

关键词： Ventilation

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Manipulating Elasto-Plastic Objects With 3D Occupancy and Learning-Based Predictive Control

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IEEE Robotics and automation Letters 2025年第7期10卷 7222-7229页

作者： Zhen Zhang Xiangyu Chu Yunxi Tang Lulu Zhao Jing Huang Zhongliang Jiang K. W. Samuel Au Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China Multi-scale Medical Robotics Center Hong Kong SAR China School of Artificial Intelligence Beijing Normal University Beijing China Computer Aided Medical Procedures Technical University of Munich Munich Germany

Manipulating elasto-plastic objects remains a significant challenge due to severe self-occlusion, difficulties of representation, and complicated dynamics. This work proposes a novel framework for elasto-plastic object manipulation with a quasi-static assumption for motions, leveraging 3D occupancy to represent such objects, a learned dynamics model trained with 3D occupancy, and a learning-based predictive control algorithm to address these challenges effectively. We build a novel data collection platform to collect full spatial information and propose a pipeline for generating a 3D occupancy dataset. To infer the 3D occupancy during manipulation, an occupancy prediction network is trained with multiple RGB images supervised by the generated dataset. We design a deep neural network empowered by a 3D convolution neural network (CNN) and a graph neural network (GNN) to predict the complex deformation with the inferred 3D occupancy results. A learning-based predictive control algorithm is introduced to plan the robot's actions, incorporating a novel shape-based action initialization module specifically designed to improve the planner's efficiency. The proposed framework in this letter can successfully shape the elasto-plastic objects into a given goal shape and has been verified in various experiments both in simulation and the real world.

关键词： Three-dimensional displays Solid modeling Feature extraction Predictive control Shape Deformable models Predictive models Point cloud compression Deformation Manipulator dynamics

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Interactive Navigation in Environments with Traversable Obstacles Using Large Language and Vision-Language Models

arXiv

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arXiv 2023年

作者： Zhang, Zhen Lin, Anran Wong, Chun Wai Chu, Xiangyu Dou, Qi Samuel Au, K.W. Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong Multiscale Medical Robotics Centre Hong Kong Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Computer Aided Medical Procedures Technical University of Munich Germany

关键词： Motion planning

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Virtual sensor architecture for indoor air quality monitoring

Virtual sensor architecture for indoor air quality monitorin...

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Low-Cost Digital Solutions for Industrial automation (LoDiSA 2023)

作者： J. Merino D. Ikeuchi N. Moretti A. Mukerjee L. Li S. Karatzas S. Pattinson A. Parlikad Distributed Information and Automation Laboratory Department of Engineering University of Cambridge Institute for Manufacturing Alan Reece Building 17 Babbage Road Cambridge UK Computer Aided Manufacturing Laboratory Department of Engineering University of Cambridge Trumpington Street Cambridge CB2 1PZ UK

关键词：

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Application of binary classification of magnetic resonance therapy images to detect the threat of the disease due to COVID-19 3

Application of binary classification of magnetic resonance t...

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3rd IEEE KhPI Week on Advanced Technology, KhPI Week 2022

作者： Zalevska, Olga Vanin, Volodymyr Sydogenko, Julia Finogenov, Oleksii Demydenko, Olga Yablonskyi, Petro Ladogubets, Tetyana Oliinyk, Yurii Miroshnichenko, Ivan National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Automation of Power Processes and Systems Engineering Kyiv Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Descriptive Geometry Engineering and Computer Graphics Kyiv Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Department of Computer-Aided Science and Data Processing Systems Kyiv Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' The Department of Theory Practice and Translation of English Kyiv Ukraine National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Deprtament of Applied Mathematics Kyiv Ukraine

ISBN: (数字)9798350399202

ISBN: (纸本)9798350399202

The paper considers the use of a neural network for the binary classification of magnetic resonance imaging images to establish a possible disease of COVID-19. Processing of input data and their reduction to one format is provided, and neural network software for binary classification is developed and its training based on about 60,000 open patient images. The using of developed software is universal for medical doctors or ordinary Internet users and does not require additional training. © 2022 IEEE.

关键词： Magnetic resonance imaging

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Surface Quality Control of p-type Silicon Chip during Edge Insulation with Wire Electric Dischaarge Machining

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Sensors and Materials 2023年第11期35卷 3697-3711页

作者： Lee, Hsin-Min Peng, Ta-Jen Chen, Tzung-Ming Peng, Kang-Feng Department of Mechanical and Computer-Aided Engineering Army Academy R. O. C. No. 750 Longdong Rd. Zhongli Dist. Taoyuan City320316 Taiwan Department of Intelligent Automation Engineering National Chin-Yi University of Technology No. 57 Sec. 2 Zhongshan Rd. Taiping Dist. Taichung City411030 Taiwan Department of Industrial Education and Technology National Changhua University of Education No. 2 Shi-Da Rd. Changhua City500208 Taiwan Department of Mechanical Engineering National Central University No. 300 Zhongda Rd. Zhongli Dist. Taoyuan City320317 Taiwan

Solar energy is one of the most widely used green energy sources, but the consumption of chemicals during the manufacturing of solar panels lowers the environmental value of this source. Therefore, in this study, we apply wire electrical discharge machining to the edge insulation process of solar cell chips to avoid the disadvantages of using chemical edge insulation and reduce the cost of waste liquid disposal. In addition, process parameters, such as servo voltage, feed rate, machining depth, discharge gap, droplet flow rate, and the concentration of abrasive powder added, are investigated to improve the surface roughness of specimens, as well as to remove the phosphorus layer and minimize cracks on the specimen surface. The experimental results indicate that the surface roughness of silicon chips can be reduced from 0.614 to 0.365 µm using deionized water with a droplet flow rate of 12 cc/min at the servo voltage of 30 V, which resulted in a 40% improvement in the surface roughness of silicon chips. The addition of 0.6 g/l SiC to deionized water further reduced the surface roughness to 0.304 µm, which represented a 10% improvement over the value achieved with pure deionized water. This means that the need for a chemical post-treatment process can be reduced while maintaining the surface quality of the specimen and ensuring environmental protection. At the same time, the removal of the phosphorus layer and cracks in one single process pass demonstrates that wire electric discharge machining can be used efficiently for wafer edge insulation. © MYU K.K.

关键词： Surface roughness

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Analysis of IIR Filters by Interval Response

Analysis of IIR Filters by Interval Response

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2020 Moscow Workshop on Electronic and Networking Technologies, MWENT 2020

作者： Borges, Vinicius Nepomuceno, Erivelton G. Tutueva, Aleksandra V. Karimov, Artur I. Duque, Carlos Karimov, Timur I. Federal University of São João Del-Rei Electrical Engineering Department São João del-Rei Brazil Petersburg Electrotechnical University Computer Aided Design Department Saint-Petersburg Russia Petersburg Electrotechnical University Youth Research Institute Saint-Petesburg Russia Federal University of Juiz de Fora Power Electronics and Automation Group Juiz de For a Brazil

ISBN: (纸本)9781728125718

The classical theory of signal processing assumes that the designed IIR filters are continuous and have infinitely accurate coefficients. However, when developing filters for real-world digital signal processing tasks, it is necessary to take into account the finite precision of the coefficients representation, especially considering the fixed-point arithmetic. In this paper, we propose a new approach, which we call the interval size approach, making it easy to evaluate the actual digital filter response for various fixed-point arithmetic parameters. We provide Illustrative examples to demonstrate the frequency response bounds evolution as an order, cutoff frequency, and signal frequency are varying. We show that the interval size can be used as a well-suited accuracy factor of a digital filter. © 2020 IEEE.

关键词： Fixed point arithmetic

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79 Mathematical model of adapted ultrasonic bonding process for MEMS packaging 15

79 Mathematical model of adapted ultrasonic bonding process ...

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15th IEEE International Conference on the Perspective Technologies and Methods in MEMS Design, MEMSTECH 2019

作者： Funkendorf, Anastasiia Bortnikova, Viktoriia Maksymova, Svitlana Melnyk, Mykhaylo Department of Software Engineering Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Computer-Integrated Technologies Automation and Mechatronics Kharkiv National University of Radio Electronics Kharkiv Ukraine Department of Computer-Aided Design Lviv Polytechnic National University Lviv Ukraine

ISBN: (纸本)9781728140308;9781728140292

In the paper, approach to adaptation ultrasonic bonding process for MEMS WLP is proposed. The results of the welded joint of dissimilar plates simulation are presented. Based on them, dependency between quality of the welded joint and the technological parameter of the welding speed is given. Mathematical Model of Adapted Ultrasonic Bonding Process for MEMS Packaging is developed. © 2019 IEEE.

关键词： MEMS

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