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Advances in powder coating of metal components: A case study for wire die springs

JOURNAL OF MANUFACTURING PROCESSES 2023年 101卷 1257-1274页

作者： Rubino, Gianluca Venettacci, Simone Univ Tuscia Dept Econ Engn Soc & Business Org I-01100 Viterbo Italy Univ Rome Niccolo Cusano Dept Engn Via Don Carlo Gnocchi 3 I-00166 Rome Italy

The subject of the present paper deals with the description of an innovative coating process, based on polymer powder fluidized bed technology, applied in combination with an adhesive silicone primer. This study aims to overcome the problems of traditional coating systems for mechanical complex-geometry components, for applications where high precision in thin film deposition and high coating uniformity, at a micrometer level, are required. In this context, the case study of wire die spring coating is here proposed, carrying out a validation of the proposed technical solution, compared to the traditional process based on electrostatic coating, through an aesthetic, morphological and mechanical experimental characterization. The results showed that the innovative deposition system ensures excellent aesthetic performance, depositing a homogeneous coating, with a constant thickness of -15-20 & mu;m, on the surface of the complex geometry component analyzed, as opposed to -25-90 & mu;m for the traditional process. The proposed technique also ensures an excellent coating uniformity both inside the coils and on the external surfaces, as well as a complete protective coverage of the springs and their uniform coloring, with significantly lower consumption of coating powder, thus verifying the full technological feasibility of the fluidized bed deposition process, which is applicable also on non-conductive surfaces. Finally, the surface morphology of the specimens coated with the advanced system showed a memory effect of the substrate, while the analysis of the mechanical behavior remarked a higher fragility in terms of scratch test resistance, typical of thin films, compared to the reference.

关键词： Fluidized bed Polymer powder Protective coating coverage problem Complex-geometry components Scratch test

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An improved parallel processing-based strawberry optimization algorithm for drone placement

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TELECOMMUNICATION SYSTEMS 2023年第2期82卷 245-275页

作者： Farrag, Tamer Ahmed Farag, M. A. Rizk-Allah, Rizk M. Hassanien, Aboul Ella Elhosseini, Mostafa A. MISR Higher Inst Engn & Technol Dept Comp Engn Mansoura Egypt Menoufia Univ Fac Engn Dept Basic Engn Sci Shibin Al Kawm Egypt Cairo Univ Fac Comp & Artificial Intelligence Giza Egypt Mansoura Univ Fac Engn Comp & Control Syst Engn Dept Mansoura Egypt Taibah Univ Coll Comp Sci & Engn Yanbu Saudi Arabia Sci Res Grp Egypt SRGE Giza Egypt

It is challenging to place drones in the best possible locations to monitor all sensor targets while keeping the number of drones to a minimum. Strawberry optimization (SBA) has been demonstrated to be more effective and superior to current methods in evaluating engineering functions in various engineering problems. Because the SBA is a new method, it has never been used to solve problems involving optimal drone placement. SBA is preferred for optimizing drone placement in this study due to its promising results for nonlinear, mixed, and multimodal problems. Based on the references listed below, no study has investigated the need to develop a parallelized strategy version. Several studies have been conducted on the use of drones for coverage. However, no optimization algorithms have been evaluated regarding time complexity or execution time. Despite what has been said thus far, no study has looked into the significance of a systematic framework for assessing drone coverage techniques using test suits. An optimized drone placement algorithm based on strawberry optimization is presented in the paper. The strawberry optimization algorithm will solve the drone placement problem through parallelization. In addition, the authors deploy test suits that vary in size from small to large. The dataset consists of four categories with three problems each. Results indicate that strawberry optimizers outperform Genetic algorithms (GA) and particle swarm optimization algorithms (PSO) in the number of drones, convergence, and computation time. Furthermore, the proposed approach achieves the best solution in a finite number of steps. In small-scale problems, the performance of all algorithms is convergent. As the size of the data set increases, the superiority of Strawberry optimization algorithms becomes evident. Overall, Strawberry comes out on top for eleven out of twelve comparisons.

关键词： Drone placement coverage problem Strawberry optimization algorithm Genetic algorithm Particle swarm optimization

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Constructing a wireless sensor network to fully cover critical grids by deploying minimum sensors on grid points is NP-complete

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IEEE TRANSACTIONS ON COMPUTERS 2007年第5期56卷 710-715页

作者： Ke, Wei-Chieh Liu, Bing-Hong Tsai, Ming-Jer Natl Tsing Hua Univ Dept Comp Sci Hsinchu 30013 Taiwan

This paper proves that deploying sensors on grid points to construct a wireless sensor network that fully covers critical grids using minimum sensors (Critical-Grid coverage problem) and that fully covers a maximum to... 详细信息

关键词： NP-complete wireless sensor networks coverage problem

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Dynamic Elliptical Shaping Control for Swarm Robots

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IEEE ACCESS 2023年 11卷 17454-17470页

作者： Hart, Shae T. Kamenetsky, Jake Kitts, Christopher A. Santa Clara Univ Dept Mech Engn Santa Clara CA 95053 USA Lockheed Martin Bethesda MD 20817 USA

Solving the robotic swarm coverage problem for an elliptical area has various applications for exploring novel environments. Solutions for this problem should cover a specified ellipse and seamlessly adapt to changing numbers of robots. Previous solutions used techniques such as formation control, vector fields, and neural networks. While these techniques were successful, they all lacked one or more of the three key tenants of swarm elliptical attraction: complete coverage of an ellipse with commandable parameters, simplicity for scaling in the number of robots, and adaptive sizing. Additionally, no previous work presented guidelines for ensuring that the swarms could successfully and safely converge to the commanded ellipse without collisions. In contrast, this work presents a novel swarm elliptical attraction behavior with all three key tenants with guidelines for ellipse and swarm parameter selection. First, a new Lyapunov stable elliptical attraction behavior for Reactive Particle Swarms is presented. The behavior commands robots to cover the entire ellipse area for a specific semimajor axis, eccentricity, and orientation. Additionally, dynamic interagent spacing naturally ensures coverage for different numbers of robots. Second, the work presents a novel adaptive sizing algorithm that varies the ellipse's semimajor axis based on the swarm state. The adaptive sizing algorithm specifies the eccentricity and orientation using time-varying functions. Third, guidelines for selecting the number of robots, commanded ellipse area, obstacle avoidance distance, and robot communication range that allow for successful aggregation to the commanded ellipse are presented. All three of the results are verified using simulation and hardware-in-the-loop trials.

关键词： Shape Behavioral sciences Collision avoidance Guidelines Computer architecture Particle swarm optimization Transmission line matrix methods coverage problem elliptical aggregation shape control swarm robotics

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Efficient Power Conservation Mechanism in Spline Function Defined WSN Terrain

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IEEE SENSORS JOURNAL 2014年第3期14卷 853-864页

作者： Tseng, Fan-Hsun Cho, Hsin-Hung Chou, Li-Der Chao, Han-Chieh Natl Cent Univ Dept Comp Sci & Informat Engn Tao Yuan 32001 Taiwan Natl Ilan Univ Dept Comp Sci & Informat Engn Ilan 26047 Taiwan Natl Ilan Univ Dept Elect Engn Ilan 26047 Taiwan Natl Dong Hwa Univ Dept Elect Engn Hualien 97401 Taiwan

coverage is a vital issue that ensures that basic functions are available in wireless sensor networks (WSNs). These functions provide communications during emergency rescue or in war environments. Sensor nodes must be dispersed and survive in place for a long time in order to accurately monitor all events. However, sensor nodes rely on limited battery energy restricted to the lifetime of the entire network. When few sensor nodes are awake during an epoch, the entire network lifetime becomes longer. This implies that the coverage problem must be solved based on the energy efficiency issue. In order to strengthen the coverage ratio with a limited number of sensor nodes, practical coverage algorithms were proposed in the existing researches but investigated in a 2-D plane, which is not suitable for a realistic environment. Few researchers have investigated the WSN coverage problem for a 3-D space. The actual terrain is rugged and bumpy that prevents deploying sensor nodes in three-dimension space. In this paper, we consider the field of interest as a complex surface but also use the spline function to obtain factual information about a complex surface. Furthermore, dynamic programming is utilized to optimize the sensing radius for reducing the power consumption.

关键词： Wireless sensor network coverage problem power consumption Spline function dynamic programming

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A THRESHOLD FOR THE SIZE OF RANDOM CAPS TO COVER A SPHERE

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ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS 1988年第4期40卷 665-670页

作者： MAEHARA, H RYUKYU UNIV NISHIHARAOKINAWAJAPAN

Consider a unit sphere on which are placed N random spherical caps of area 4πp(N). We prove that if % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGGipm0dc9vqaqpepu0xbbG8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaa0aaaeaaca% qGSbGaaeyAaiaab2gaaaWaaeWaaeaacaWGWbWaaeWaaeaacaWGobaa% caGLOaGaayzkaaGaai4Taiaad6eacaGGVaGaaeiBaiaab+gacaqGNb% Gaaeiiaiaad6eaaiaawIcacaGLPaaacqGH8aapcaaIXaaaaa!454E!\[\overline {{\rm{lim}}} \left( {p\left( N \right)\cdotN/{\rm{log }}N} \right) N caps tends to 0 as N → ∞, and if % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGGipm0dc9vqaqpepu0xbbG8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xb9adbaqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaWaaaeaaca% qGSbGaaeyAaiaab2gaaaWaaeWaaeaacaWGWbWaaeWaaeaacaWGobaa% caGLOaGaayzkaaGaai4Taiaad6eacaGGVaGaaeiBaiaab+gacaqGNb% Gaaeiiaiaad6eaaiaawIcacaGLPaaacqGH+aGpcaaIXaaaaa!4551!\[\underline {{\rm{lim}}} \left( {p\left( N \right)\cdotN/{\rm{log }}N} \right) > 1\], then for any integer n>0 the probability that each point of the sphere is covered more than n times tends to 1 as N → ∞.

关键词： coverage problem random caps threshold function

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Many-objective optimisation-based optimal drone deployment for agricultural zone

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INTERNATIONAL JOURNAL OF COMMUNICATION NETWORKS AND DISTRIBUTED SYSTEMS 2021年第1期26卷 76-98页

作者： Issad, Hassina Ait Aoudjit, Rachida Belkadi, Malika Rodrigues, Joel J. P. C. Univ Mouloud Mammeri Tizi Ouzou LARI Lab Tizi Ouzou Algeria Univ Fed Piaui BR-36036900 Juiz De Fora Brazil Inst Telecomunicacoes P-1049001 Lisbon Portugal

Monitoring using drones is not just a civilian and military task, but it also concerns the agricultural sector, where it can play an important role in the context of smart agriculture. It seems to be a very valuable tool in the future. However, the optimal deployment of a set of monitoring drones is a very challenging problem;it is a NP-Hard problem. In this paper, the deployment problem has been modelled as a constrained many-objective optimisation problem. Powerful heuristics, namely multi-objective artificial bee colony (MOABC), multi-objective particle swarm optimisation (MOPSO), non-dominated sorting genetic algorithm II (NSGA II), strength Pareto evolutionary algorithm II (SPEA II) and non-dominated sorting genetic algorithm III (NSGA III) are used to find the optimal deployment strategy with four goals: minimising energy consumption, maximising total coverage, maintaining connectivity and minimising overlaps. A comparative study was carried out and the results showed that the SPEA II, NSGA III and NSGA II algorithms have better convergence and maintain good diversity than the other algorithms.

关键词： drones deployment coverage problem unmanned aerial vehicle UAV many-objective optimisation Pareto front

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Algorithms for computing Best coverage Path in the presence of obstacles in a sensor field

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JOURNAL OF DISCRETE ALGORITHMS 2012年 13卷 86-97页

作者： Roy, Senjuti Basu Das, Gautam Das, Sajal K. Univ Washington Inst Technol Tacoma WA 98402 USA Univ Texas Arlington Dept Comp Sci & Engn Arlington TX 76019 USA

We compute BCP(s, t), a Best coverage Path between two points s and t in the presence of m line segment obstacles in a 2D field under surveillance by n sensors. Based on nature of obstacles, we have studied two variants of the problem. For opaque obstacles, which obstruct paths and block sensing capabilities of sensors, we present algorithm ExOpaque for computation of BCP(s, t) that takes O((m(2)n(2) + n(4)) log(mn + n(2))) time and O(m(2)n(2) + n(4)) space. For transparent obstacles, which only obstruct paths but allow sensing, we present an exact as well as an approximation algorithm, where the exact algorithm ExTransparent takes O(n(m + n)(2)(logn + log(m+n))) time and O(n(m+n)(2)) space. On the other hand, the approximation algorithm ApproxTransparent takes O(n(m + n)(logn + log(m + n))) time and O(n(m + n)) space with an approximation factor of O(k), using k-spanners of visibility graph. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Sensor network coverage problem Voronoi diagram Visibility graph Spanner

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THE COMPLEXITY OF coverage

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INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE 2013年第2期24卷 165-185页

作者： De Alfaro, Luca Majumdar, Rupak Univ Calif Santa Cruz Santa Cruz CA 95064 USA

We study the problem of generating a test sequence that achieves maximal coverage for a reactive system under test. We formulate the problem as a repeated game between the tester and the system, where the system state space is partitioned according to some coverage criterion and the objective of the tester is to maximize the set of partitions (or coverage goals) visited during the game. We show the complexity of the maximal coverage problem for non-deterministic systems is PSPACE-complete, but is NP-complete for deterministic systems. For the special case of non-deterministic systems with a re-initializing "reset" action, which represent running a new test input on a re-initialized system, we show that the complexity is coNP-complete. Our proof technique for reset games uses randomized testing strategies that circumvent the exponentially large memory requirement of deterministic testing strategies. We also discuss the memory requirement for deterministic strategies and extensions of our results to other models, such as pushdown systems and timed systems.

关键词： coverage problem computational complexity graph games timed and pushdown systems

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ON INFERENCE IN A ONE-DIMENSIONAL MOSAIC AND AN M-G-INFINITY QUEUE

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ADVANCES IN APPLIED PROBABILITY 1985年第1期17卷 210-229页

作者： HALL, P AUSTRALIAN NATL UNIV FAC ECONDEPT STATGPO BOX 4CANBERRAACT 2601AUSTRALIA

Suppose segments are distributed at random along a line, their locations being determined by a Poisson process. In the case where segment length is fixed, we compare efficiencies of several different estimates of Poisson intensity. The case of random segment length is also considered, and there we study estimation procedures based on empiric properties. The one-dimensional mosaic may be viewed as an M/G/∞ queue.

关键词： CENTRAL LIMIT THEOREM coverage problem EFFICIENCY GEOMETRIC PROBABILITY M/G/∞ QUEUE MOSAIC PROCESS POISSON PROCESS

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