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检索条件"任意字段=5th International Conference on Robotics and Automation Systems, Robotics 2010"

共 1360 条记录，以下是401-410 订阅

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Performance Evaluation of Main Steam Temperature Control System of thermal Power Unit Based on Mahalanobis Distance 5

Performance Evaluation of Main Steam Temperature Control Sys...

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5th international conference on automation, Control and robotics Engineering, CACRE 2020

作者： Hu, Boyong Xie, Jianbo He, Yusheng Wang, Yinsong Ma, Pingyan Ener. Saving and Pollutant Contr. Technol. for Thermal Pwr. Generation Zhejiang Ener. Technol. Res. Inst. Co. Ltd. Zhejiang Key Laboratory of High Efficiency Hangzhou China Zhejiang Energy Group Co. Ltd. Hangzhou China North China Electric Power University Automation Department Baoding China

ISBN: (纸本)9781728198880

As the main parameter of thermal power unit, the measurement and control of main steam temperature play an important role in the safe and economic operation of power plant. In order to improve the control quality of main steam temperature control system of thermal power unit, this paper presents a performance evaluation method of main steam temperature control system of thermal power unit based on Mahalanobis distance. this method is based on the output data of leading steam temperature and main steam temperature. Firstly, the data set representing the best performance of the system is selected according to Hurst index, and the benchmark of performance evaluation is established based on this data. then the calculation process of traditional Mahalanobis distance is improved, and the specific calculation method of performance evaluation index based on the combination of Hurst index and improved Mahalanobis distance is given. Finally, the performance evaluation index is classified by membership function. the simulation results show that the evaluation method is effective and reasonable and the calculation is simple. © 2020 IEEE.

关键词： Quality control

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An Incentive Mechanism for UAVs Crowdsensing Markets, a Negotiation Approach 20th

An Incentive Mechanism for UAVs Crowdsensing Markets, a Nego...

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20th IFAC conference on Technology, Culture, and international Stability (TECIS)

作者： Jaimes, Luis G. Kahr, Janar Calderon, Juan M. Florida Polytech Univ Dept Comp Sci Lakeland FL 33805 USA Bethune Cookman Univ Daytona Beach FL USA Univ Santo Tomas Bogota Colombia

In this paper, we present an incentive mechanism for Unmanned Aerial vehicles (UAVs) crowdsensing. In particular, we propose a solution to the problem of sensing coverage of lower regions of the atmosphere where a set of UAVs transverse it as part of their daily activities. We propose a UAV sensing market where data collection is an additional by-product that UAVs obtained while following their regular trajectories. In this model, participants use negotiation to compete and cooperate with each other while participating in data collection campaigns. Using the Virtual robotics Environment (VRep) and extensive simulations, we show that our algorithm performs well in terms of sensing coverage, and participants retention while using a limited budget. Copyright (C) 2021 the Authors.

关键词： Cost Oriented automation Intelligent systems and Applications Artificial intelligence and Applications Deep Learning

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Intelligent Labware Transportation Solution for the Hierarchical Life Science automation 14th

Intelligent Labware Transportation Solution for the Hierarch...

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14th international conference on Informatics in Control, automation and robotics (ICINCO)

作者： Neubert, S. Roddelkopf, T. Goede, B. Gu, X. Junginger, S. Stoll, N. thurow, K. Univ Rostock Inst Automat Friedrich Barnewitz Str 8 D-18119 Rostock Germany Automat Celisca Ctr Life Sci Friedrich Barnewitz Str 8 D-18119 Rostock Germany

ISBN: (纸本)9783030112929;9783030112912

In life science laboratories spatially distributed automation systems are increasingly applied to process complex professional tasks of an overall workflow. the transportation-logistic fusion of interacting automation systems is so far often the job of human operators who are parallel involved in regular laboratory tasks. this paper describes the integration of mobile robots and human operators in a hierarchical workflow management system (HWMS) to increase the degree of automation concerning complex process chains. Mobile robots combine distributed automation systems by labware-transportation processes and enable automated building-wide workflows. the necessity of laboratory assistance for transportation and assistance tasks in these workflows still remains and consequently the flexible integration of human operators, via mobile devices such as smartphones and/or tablet PCs, in the environment of life science automation (LSA) is pursued. Besides the infrastructure for the connection of automation systems (instruments, workstations, integrated systems) also a transportation infrastructure needs to be considered for the workflow control, which distributes and controls transportation and assistance tasks for mobile robots and human operators. the development of the transportation infrastructure is discussed in detail by three potential variants. the implementation and application of the favored variant is amplified in context with automation systems.

关键词： Life science automation Laboratory execution system Mobile robot integration Dynamical scheduling Human machine interaction

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Design and Application of Pavement Structure Depth Calibration Device 5

Design and Application of Pavement Structure Depth Calibrati...

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5th international conference on automation, Control and robotics Engineering, CACRE 2020

作者： Du, Yongbo Liu, Chao Huang, Linfeng Chen, Jiahao Hou, Shuwen Zou, Yifeng Xu, Junhai Century College of Beijing University of Posts and Telecommunications Department of Automation Beijing China

ISBN: (纸本)9781728198880

the depth of pavement structure is an important indicator of pavement detection, which can evaluate the anti-skid performance and drainage performance of the pavement, and plays a decisive role in the safety of pavement traffic. the traditional pavement structure depth measurement method has problems such as poor measurement accuracy and unintuitive measurement results. the laser measurement pavement structure depth measurement method has been widely used. In the process of calibrating the laser structural depth instrument, a calibration device is urgently needed, which can provide a stable rotation speed and drive the rotation of the simulated road surface turntable. the turntable has standard values and different structural depths, thereby completing the verification of the structural depth instrument. A depth calibration device for pavement structure proposed in this paper meets the above requirements. the device prototype is composed of mechanical system and control system. the mechanical system consists of a control box and a turntable rotating base. this paper describes the structure of the turntable rotating base. the main controller of the control system is based on the Mitsubishi FX3U PLC design and controls the speed of the direct drive motor through the analog voltage. During the experiment on the system linearity, due to the poor linearity of the motor driver, it caused greater inconvenience to the speed design, so the program control logic designed the speed feedback loop, and the negative feedback logic was introduced to ensure the stability of the turntable speed and the system speed. the error is within ±15r/min. through system testing and actual industrial field experiments, the system performance meets the requirements. © 2020 IEEE.

关键词： Calibration

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COVID-Bot: UV-C Based Autonomous Sanitizing Robotic Platform for COVID-19 20th

COVID-Bot: UV-C Based Autonomous Sanitizing Robotic Platform...

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20th IFAC conference on Technology, Culture, and international Stability (TECIS)

作者： Camacho, Edgar C. Ospina, Nestor, I Calderon, Juan M. Univ Santo Tomas Fac Elect Engn Bogota Colombia Univ Nacl Colombia Dept Elect & Elect Bogota Colombia Bethune Cookman Univ Daytona Beach FL USA Univ Santo Tomas Bogota Colombia

this paper presents the design and implementation of COVID-Bot, an open-source robotic platform for sanitizing single plant environments such as offices, houses, apartments, among others. this development seeks to create a tool that contributes to the global fight against the COVID-19 pandemic, from a low-cost and easy-to-replicate robot, which disinfects surfaces through type C ultraviolet radiation. the platform is based on a differential robotic base, an RGB-D camera, a tracking camera, three UV-C lamps, and an embedded computer running the ROS-based control software. In addition, this paper presents the description of the hardware used, the software implemented, and the tests carried out to corroborate the operation of the integrated system. these tests demonstrated that the system is adequate to autonomously cover a one-floor apartment, based on the theoretical radiation distance of the used lamps. Copyright (C) 2021 the Authors.

关键词： Mechatronic systems and robotics Cost Oriented automation (COA) Biomedical systems Mobile Robots 3D Mapping Navigation ROS

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Electric Vehicle Charging Demand Prediction using Multiresolution Sinusoidal Neural Network Optimized with Addax Optimization

Electric Vehicle Charging Demand Prediction using Multiresol...

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Trends in Material Science and Inventive Materials (ICTMIM), international conference on

作者： Rajesh Munirathnam Rohit P. Jadhav Nilesh M. Mahajan Amit Barve M. E. Shashi Kumar Natrayan L Data & Analytics Division TechnoGen Inc Hillsborough New Jersey USA Department of Robotics and Automation D.Y. Patil College of Engineering Akurdi Pune Maharashtra Department of Computer Science and Engineering Parul Institute of Technology Faculty of Engineering and Technology Parul University Limda Gujarat Department of Mechanical Engineering Amrita School of Engineering Amrita Vishwa Vidyapeetham Bengaluru Karnataka Department of Mechanical Engineering Saveetha School of Engineering SIMATS Chennai Tamil Nadu

ISBN: (数字)9798331501488

ISBN: (纸本)9798331501495

Electric Vehicle (EV) charging demand prediction, while essential for optimizing charging infrastructure and energy management, faces challenges such as data inaccuracies and uncertainties in user behavior patterns. these issues define inaccurate demand forecasts which cause the wrong placement of charging stations and distribution of energy. Also, as the pattern of the EV charging is not static may change due to many factors such as climate, time of day, price preference among others, the prediction models may not handle the dynamism and hence lower the reliability of the forecast results. To overcome these drawbacks, this manuscript proposes an efficient approach for EV charging demand prediction. the data is gathered from a dataset on EV charging. the data is then sent to pre-processing. Using the Maximum Correntropy Quaternion Kalman Filter (MCQKF), the pre-processing section eliminates missing values and normalizes the input. To forecast EV charging demand, the Multiresolution Sinusoidal Neural Network (MSNN) receives the results of the pre-processing data. MSNN’s weight parameter is optimized using Addax Optimization (AO). the proposed MSNN-AO is utilized within the MATLAB platform. the proposed MSNN-AO technique is compared with the existing techniques such as Long Short-Term Memory Neural Network (LSTMNN), Heterogeneous Spatial-Temporal Graph Convolutional Network (HSTGNN) and Artificial Neural Networks (ANN), respectively. the MSNN-AO method achieves an accuracy of 97%, precision of 95%, and a Root Mean Square Error (RMSE) of 2.2%, demonstrating its superior performance in predicting EV charging demand. this highlights the proposed method’s effectiveness in minimizing prediction errors, reducing RMSE by 22.36%, and improving precision by 14.89% compared to existing methods. the MSNN-AO method’s higher accuracy and precision, coupled with its robust performance, make it a reliable and efficient solution for EV charging demand forecasting.

关键词： Accuracy Uncertainty Quaternions Energy resolution Electric vehicle charging Reliability Kalman filters Spatial resolution Root mean square Optimization

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A Novel Energy Based Ground Movement Detection Technique using Seismic Signal

A Novel Energy Based Ground Movement Detection Technique usi...

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international conference on Information systems and Computer Networks (ISCON)

作者： Anisom Chakraborty Ankit Mallick Srinivasa Reddy Nemalidinne Siva Ram Krishna Vadali Srinivasan Aruchamy Vinayak Shriniwas Nageli Robotics & Automation CSIR-CMERI DurgapurIndia CAIR- DRDO BengaluruIndia

ISBN: (纸本)9781665447874

Event detection using seismic signals is a problem of great significance. though several techniques have been developed, achieving an acceptable event detection performance in an outdoor environment is difficult to accomplish. In this paper, a ground movement detection technique is proposed using the energy of acquired seismic signal in different spectral ranges. Performance of the proposed method is tested with an experimental setup including a geo-phone and a data acquisition system. Analysis of results from experimental data indicate that the proposed method renders significant (≈90%) reduction in false alarm probability besides providing ≈ 8% improvement in event detection accuracy, over amplitude and energy thresholding approaches.

关键词： Event detection Data acquisition Motion detection Computer networks Information systems

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Determining the carbon footprint of Russian residents depending on their food and movement patterns 4

Determining the carbon footprint of Russian residents depend...

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4th international Scientific conference on Agribusiness, Environmental Engineering and Biotechnologies, AGRITECH-IV 2020

作者： Abdullina, Leila Podolskiy, Aleksandr Deeva, Margarita Gorovko, Margarita Shulepova, Yuliya Theory of machines and Mechanisms Department Bauman Moscow State Technical University ul. Baumanskaya 2-ya 5/1 Moscow105005 Russia Hoisting and transport systems Department Bauman Moscow State Technical University ul. Baumanskaya 2-ya 5/1 Moscow105005 Russia Department of Robotics and Complex Automation Bauman Moscow State Technical University ul. Baumanskaya 2-ya 5/1 Moscow105005 Russia

Due to climate change, all the inhabitants of the Earth are increasingly observing various natural anomalies. the consequences of global warming are particularly noticeable for Russia, where it is about 2.5 times faster than in the rest of the world (the Russian Federation almost does not experience the softening influence of the ocean due to geographical features, so the climate is particularly sensitive). In order to successfully forecast climate change and develop an adequate adaptation program, it is necessary to assess the volume of emissions of the main greenhouse gas CO2 in a timely manner. Since the final carbon footprint of the Russian Federation largely depends on the environmental awareness of the young generation and its contribution to the existing climate change problem, the subject of this article was the average carbon footprint of young people (18-25 years old) in the Russian Federation. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Carbon footprint

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Assessment of Upper Limb Tremors in Patients with Parkinson's Disease Based on Displacement and Acceleration Information 5

Assessment of Upper Limb Tremors in Patients with Parkinson'...

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5th international conference on automation, Control and robotics Engineering, CACRE 2020

作者： Wu, Haoran Zhang, Yanan Wu, Xi Yang, Fan Shanghai University School of Mechatronic Engineering and Automation Shanghai200072 China Changhai Hospital Shanghai200433 China

ISBN: (纸本)9781728198880

To examine the consistency between upper limb tremor scores for patients with Parkinson's disease (PD) obtained after comprehensively processing and modeling limb displacement and acceleration information and doctors' scores and to refine the scores. In this way, wearable devices can be used to assist doctors' treatment and improve their work efficiency. Seventeen PD patients wearing detection devices completed the standard movements stipulated in Part III of the Unified Parkinson's Disease Rating Scale for examining resting and postural tremors (RTs and PTs), during which the acceleration signals (ASs) of the patients' movements were collected. the AS and DS are denoised by using the designed wavelet automatic filtering process. A sliding window is used to select the most obvious period of tremor during detection. then extract the characteristic values from time domain, frequency domain and spectral domain respectively, and explore the most suitable model method for this study. In terms of reflecting the physical characteristics of tremors, the AS and DS eigenvalue sets each had their own advantages. For the RTs, there were stronger correlations between the AS eigenvalue set and doctors' scores. the average correlation coefficients (rs) of the AS and DS eigenvalue sets were 0.798 (0.630-0.895, at the 95% confidence interval) and 0.731 (0.522-0.857, at the 95% confidence interval), respectively. It was the opposite for the PTs, where the average rs of the AS and DS eigenvalue sets were 0.759 (0.566-0.873, at the 95% confidence interval) and 0.845 (0.709-0.920, at the 95% confidence interval), respectively. the results showed that compared to the support vector machine, random forest and multivariate linear regression models, the neural network model had higher accuracy (the accuracy for RT and PT scores were 0.953 and 0.912, respectively). Using a combination of ASs and DSs can effectively simulate doctors' scores for RTs and PTs in the upper limbs of PD patients. ©

关键词： Wearable technology

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Object Recognition for Autonomous Driving in Adverse Weather Condition Using Polarized Camera

Object Recognition for Autonomous Driving in Adverse Weather...

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international conference on Control, Mechatronics and automation (ICCMA)

作者： Min-Ho Ha Chan-Hoe Kim Tae-Hyoung Park Industrial AI Research Center Chungbuk National University Cheongju South Korea Dept. Control and Robot Engineering Chungbuk National University Cheongju South Korea Dept. Intelligent Systems and Robotics Chungbuk National University Cheongju South Korea

ISBN: (纸本)9781665490498

Autonomous driving refers to a vehicle driving by itself without human intervention. An autonomous vehicle must recognize the environment with an attached sensor, make judgments appropriate to the situation, and drive toward its destination. Although many studies have been conducted on autonomous driving in clear weather, the response to bad weather is insufficient because the sensor encounters difficulties recognizing the environment when it is backlight or raining. this study proposes a method for recognizing objects (e.g., vehicles, pedestrians, lanes) based on polarization cameras for safe autonomous driving in backlight conditions or rain. First, the camera’s light input is adjusted, altering its aperture backlight conditions. then, the polarized image from the camera is synthesized and inputted into the object recognition network. the object detection network used Yolo v5, while the lane detection network used an ultrafast lane detection network. By extracting features from the same backbone, the inference speed of the object recognition network increased. On average, a speed of 23 fps and an object recognition accuracy of over 90% were shown in the Xavier environment.

关键词： Rain Lane detection Roads Vehicle driving Cameras Feature extraction Reduced order systems

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