2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)最新文献_第8页

Digital Vehicle Radar Sensor Target Simulation 数字车辆雷达传感器目标仿真

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9129555

J. Sobotka, J. Novák

引用次数: 7

Doppler shift compensation technique for ultrasonic DSSS ranging system 超声DSSS测距系统的多普勒频移补偿技术

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9128367

T. Ishii, Yukiko Yoshikawa, S. Izumi, H. Kawaguchi

引用次数: 3

An LSPR Sensor based on a thin slab waveguide of bacterial cellulose 基于细菌纤维素薄板波导的LSPR传感器

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9129527

N. Cennamo, F. Arcadio, L. Zeni, G. Pasquale, C. Trigona, S. Graziani, A. Pollicino

引用次数: 1

Design and Validation of SVOM on Board TT&C System SVOM车载测控系统的设计与验证

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9128453

Yang Liu, Shunjing Yu, Haiying Hu, Zongde Li, Yuanyuan Dai, Xiaofeng Zhang

引用次数: 1

Impact of Measurement Uncertainties on Compressive Sensing-based Harmonic Source Estimation Algorithms 测量不确定性对基于压缩感知的谐波源估计算法的影响

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9129012

Daniele Carta, C. Muscas, P. Pegoraro, Antonio Vincenzo Solinas, S. Sulis

{"title":"Impact of Measurement Uncertainties on Compressive Sensing-based Harmonic Source Estimation Algorithms","authors":"Daniele Carta, C. Muscas, P. Pegoraro, Antonio Vincenzo Solinas, S. Sulis","doi":"10.1109/I2MTC43012.2020.9129012","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9129012","url":null,"abstract":"The harmonic pollution generated by non-linear loads and generators in distribution networks could lead to serious consequences for the customers. The identification of the polluting sources is thus necessary to act directly on the origin of the problems, in order to reduce the corresponding effects. As well as the other Power Quality phenomena, the harmonic analysis requires specific measurement devices, which are not widespread in distribution systems. Consequently, specific algorithms and methodologies are required, in order to overcome the lack of measurements. In this regard, Compressive Sensing (CS) represents a valid solution for the analysis under study, since it allows to recover sparse signals, when only few measurements are available.In this paper, two of the most common algorithms for CS applications, the Orthogonal Matching Pursuit and the ℓ1-minimization, implemented in the framework of Harmonic Source Estimation procedures, are tested under different measurement uncertainty conditions. The tests, performed on a small medium voltage network, underline the different impact brought by the measurement uncertainties, of both magnitude and phase angle, on the two algorithms.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125636526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Measuring Worker’s Performance in Augmented Reality-assisted Industry 4.0 Procedures 在增强现实辅助的工业4.0程序中测量工人的绩效

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9129320

F. Bonavolontã, D. Dallet, E. Erra, A. Grassi, Valentina Popolo, A. Tedesco, Silvestro Vespoli

{"title":"Measuring Worker’s Performance in Augmented Reality-assisted Industry 4.0 Procedures","authors":"F. Bonavolontã, D. Dallet, E. Erra, A. Grassi, Valentina Popolo, A. Tedesco, Silvestro Vespoli","doi":"10.1109/I2MTC43012.2020.9129320","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9129320","url":null,"abstract":"Augmented Reality (AR) is considered as one of the enabling technologies offering the largest potential to improve the way in which modern factories operate, thus becoming an integral part of the Industry 4.0 paradigm. However, there are still some aspects that hinder the widespread adoption of AR. In particular, one limitation is the lack of a measurement methodology of the impact that AR has on the worker's performance in a manufacturing environment. In this regard, the present work addresses the assessment of the performance of workers when they carry out a task, supported by an AR system. To this purpose, comparative experimental tests were carried out on two groups of volunteers who were given a specific assembly task (one group followed paper instructions, whereas the other followed AR-administered instructions). To measure the worker's performance and assess the impact of AR, two figures of merit were used: the processing time required to complete a task and the number of errors made. The experimental tests showed that, while the processing times were comparable between the two groups, administering instructions through AR resulted in a lower error rate and hence an improved quality of the product.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125621826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Measurement of Activities of Daily Living: a simulation tool for the optimisation of a Passive Infrared sensor network in a Smart Home environment 日常生活活动测量:智能家居环境中被动红外传感器网络优化的模拟工具

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9128409

S. Casaccia, Riccardo Rosati, L. Scalise, G. M. Revel

{"title":"Measurement of Activities of Daily Living: a simulation tool for the optimisation of a Passive Infrared sensor network in a Smart Home environment","authors":"S. Casaccia, Riccardo Rosati, L. Scalise, G. M. Revel","doi":"10.1109/I2MTC43012.2020.9128409","DOIUrl":"https://doi.org/10.1109/I2MTC43012.2020.9128409","url":null,"abstract":"In this paper, a tool for the simulation of home environment capable of representing human moving patterns, related to Activities of Daily Living (ADL), and modelling Passive Infrared (PIR) sensor networks is presented. PIR sensors have been chosen because they are non-intrusive, contactless and low-cost. The tool has been programmed in MATLAB and provides a graphic interface from which the developer can change key simulation parameters. It makes it possible to load and visualise the 2D map of the home environment used for simulation as well as add, customise and place ceiling or wall mounted PIR sensors, and regulate users’ trajectory parameters, such as walking speed, step length or path efficiency. The simulator is useful for quickly generating synthetic data to train machine learning (ML) algorithms able to recognize user behavior, without the necessity to perform long acquisition periods. In order to demonstrate its applicability, the tool has been used to create normal and wandering trajectories and their related sensor activations. These data were employed to develop a ML algorithm able to detect overnight wandering, a common behaviour in patients with dementia. The results show that a Decision Tree (DT) algorithm is reliable for the purpose of distinguishing normal trajectories from the wandering ones detected by PIR sensor activations, obtaining an accuracy level of over 95% using a cross-validation approach.","PeriodicalId":227967,"journal":{"name":"2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131098928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Combined Impact of Voltage Transformer and Estimation Algorithm on Harmonic Synchrophasors Measurements 电压互感器与估计算法对谐波同步量测量的综合影响

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9128813

C. Laurano, S. Toscani, M. Zanoni, P. Castello, C. Muscas, P. Pegoraro

引用次数: 2

I2MTC 2020 Cover Page I2MTC 2020封面

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/i2mtc43012.2020.9128402

引用次数: 0

A 1.8 V Gm-C Highly Tunable Low Pass Filter for Sensing Applications 用于传感应用的1.8 V Gm-C高可调低通滤波器

2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Pub Date : 2020-05-01 DOI: 10.1109/I2MTC43012.2020.9128692

J. Pérez-Bailón, B. Calvo, N. Medrano, J. Ramírez-Angulo

引用次数: 2