Pub Date : 2017-07-01DOI: 10.1109/EESMS.2017.8052678
M. Tesfaye, M. Nardello, D. Brunelli
Demand and cost of electricity is expected to grow in the next years. This has raised interest in monitoring energy usage to reduce losses, and to provide real-time feedback about the cost of the electrical power consumed. This paper focuses on the implementation of a stand-alone system capable of real-time tracking of the power used and that provides power consumption estimation for each device from a single point of measurement. The learning activity is done by detecting the possible state of the electrical devices using a clustering algorithm, which involves k-means technique to analyze and detect the state of an appliance.
{"title":"Residential electrical consumption disaggregation on a single low-cost meter","authors":"M. Tesfaye, M. Nardello, D. Brunelli","doi":"10.1109/EESMS.2017.8052678","DOIUrl":"https://doi.org/10.1109/EESMS.2017.8052678","url":null,"abstract":"Demand and cost of electricity is expected to grow in the next years. This has raised interest in monitoring energy usage to reduce losses, and to provide real-time feedback about the cost of the electrical power consumed. This paper focuses on the implementation of a stand-alone system capable of real-time tracking of the power used and that provides power consumption estimation for each device from a single point of measurement. The learning activity is done by detecting the possible state of the electrical devices using a clustering algorithm, which involves k-means technique to analyze and detect the state of an appliance.","PeriodicalId":285890,"journal":{"name":"2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128808373","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}
Pub Date : 2017-07-01DOI: 10.1109/EESMS.2017.8052680
Andre Yulian Atmojo, Khoerul Anwar, M. G. Andika, R. N. Wardhani
Wind-flow around a long-span bridge, as a bluff body, will generate an aerodynamic force that interacts with the flow, causing vibration to the bridge deck. This phenomenon can lead to structural fatigue or worst, the bridge collapse. A continuous and comprehensive measurement system is needed for early detection and maintenance reference of a long-span bridge. Another benefit this system is aiming at maintaining the bridge design validation and getting development recommendation for subsequent structure. A comprehensive structural health monitoring system can be built based on data from continuous measurement and analysis of other loads such as seismic activities, traffic load, waves, self-weight of structure, earth pressure, corrosion, temperature, and so on. Some experiments have been conducted by National Laboratory of Aerodynamic, Aeroelastic and Aeroacoustic Technology's research team, which resulted in a long-span bridges aeroelastic monitoring system prototype. The prototype, called BAMS x1, can acquire wind direction, wind speed and vertical acceleration (heaving) data of a long-span bridge. A National Instrument based embedded data acquisition hardware is used. A stand-alone measurement system in remote location (based on Lab VIEW Web Service) can be build, and it is sending the data package to the server every 10 s period. At the server side, some data management and processing are done to prepare the data to the next level of analysis processing. Further development will be conducted to supply advanced data, accessible to all over the world through web application.
大跨度桥梁周围的气流作为钝体，会产生与气流相互作用的气动力，使桥面产生振动。这种现象会导致结构疲劳，最严重的是桥梁倒塌。为大跨度桥梁的早期检测和维修提供参考，需要一个连续、全面的测量系统。该系统的另一个好处是旨在维护桥梁设计的有效性，并为后续结构提供开发建议。通过对地震活动、交通荷载、波浪、结构自重、土压力、腐蚀、温度等其他荷载的连续测量和分析，可以建立全面的结构健康监测系统。气动、气动弹性与气动声学技术国家实验室课题组进行了实验研究，研制出了大跨度桥梁气动弹性监测系统样机。该原型机名为BAMS x1，可以获取大跨度桥梁的风向、风速和垂直加速度(起伏)数据。采用了一种基于国家仪器的嵌入式数据采集硬件。可以建立一个独立的远程测量系统(基于Lab VIEW Web Service)，它每10 s周期向服务器发送数据包。在服务器端，完成一些数据管理和处理，以便为下一级分析处理准备数据。将进行进一步的开发，以提供先进的数据，通过网络应用程序访问世界各地。
{"title":"Aeroelastic monitoring system: A part of long-span bridge structural health monitoring system","authors":"Andre Yulian Atmojo, Khoerul Anwar, M. G. Andika, R. N. Wardhani","doi":"10.1109/EESMS.2017.8052680","DOIUrl":"https://doi.org/10.1109/EESMS.2017.8052680","url":null,"abstract":"Wind-flow around a long-span bridge, as a bluff body, will generate an aerodynamic force that interacts with the flow, causing vibration to the bridge deck. This phenomenon can lead to structural fatigue or worst, the bridge collapse. A continuous and comprehensive measurement system is needed for early detection and maintenance reference of a long-span bridge. Another benefit this system is aiming at maintaining the bridge design validation and getting development recommendation for subsequent structure. A comprehensive structural health monitoring system can be built based on data from continuous measurement and analysis of other loads such as seismic activities, traffic load, waves, self-weight of structure, earth pressure, corrosion, temperature, and so on. Some experiments have been conducted by National Laboratory of Aerodynamic, Aeroelastic and Aeroacoustic Technology's research team, which resulted in a long-span bridges aeroelastic monitoring system prototype. The prototype, called BAMS x1, can acquire wind direction, wind speed and vertical acceleration (heaving) data of a long-span bridge. A National Instrument based embedded data acquisition hardware is used. A stand-alone measurement system in remote location (based on Lab VIEW Web Service) can be build, and it is sending the data package to the server every 10 s period. At the server side, some data management and processing are done to prepare the data to the next level of analysis processing. Further development will be conducted to supply advanced data, accessible to all over the world through web application.","PeriodicalId":285890,"journal":{"name":"2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125178855","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}
Pub Date : 2017-07-01DOI: 10.1109/EESMS.2017.8052693
Leone Pasquato, Nicola Bonotto, Pietro Tosato, D. Brunelli
We present the design optimization of an energy harvesting device based on the aeroelastic flutter effect, developed for converting wind energy in electrical energy. Due to the aeroelastic mechanical principle, the energy harvester can be equipped with a system capable to follow the Maximum Power Point of the wind generator and then to sustain the energy demand of a sensor system used for pollution monitoring. The aeroelastic harvester consists of a tensioned ribbon coupled with an electromagnetic transducer and a power conditioning unit to guarantee the power supply for remote sensors deployed in hard-to-reach areas. This paper presents the characterization of the wind flutter generator and the design of a Maximum Power Point Tracking (MPPT) logic that controls the tension of the belt for the maximum energy extraction.
{"title":"An optimized wind energy harvester for remote pollution monitoring","authors":"Leone Pasquato, Nicola Bonotto, Pietro Tosato, D. Brunelli","doi":"10.1109/EESMS.2017.8052693","DOIUrl":"https://doi.org/10.1109/EESMS.2017.8052693","url":null,"abstract":"We present the design optimization of an energy harvesting device based on the aeroelastic flutter effect, developed for converting wind energy in electrical energy. Due to the aeroelastic mechanical principle, the energy harvester can be equipped with a system capable to follow the Maximum Power Point of the wind generator and then to sustain the energy demand of a sensor system used for pollution monitoring. The aeroelastic harvester consists of a tensioned ribbon coupled with an electromagnetic transducer and a power conditioning unit to guarantee the power supply for remote sensors deployed in hard-to-reach areas. This paper presents the characterization of the wind flutter generator and the design of a Maximum Power Point Tracking (MPPT) logic that controls the tension of the belt for the maximum energy extraction.","PeriodicalId":285890,"journal":{"name":"2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130528431","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}
Pub Date : 1900-01-01DOI: 10.1109/EESMS.2017.8052686
Alberto Girolami, D. Brunelli, L. Benini
In this paper we present a low-cost distributed embedded system for Structural Health Monitoring (SHM) that uses very cost-effective MEMS accelerometers, instead of more expensive piezoelectric analog transducers. The proposed platform provides online filtering and fusion of the collected data directly on-board. Data are transmitted after processing using a WiFi transceiver. Low-cost and synchronized devices permit to have more fine-grained measurements and a comprehensive assessment of the whole building, by evaluating their response to vibrations. The challenge addressed in this paper is to execute a quite computationally-demanding digital filtering on a low-cost microcontroller STM32, and to reduce the signal-to-noise ratio typical of MEMS devices with a spatial redundancy of the sensors. Our work poses the basis for low-cost methods for elaborating complex modal analysis of buildings and structures.
{"title":"Low-cost and distributed health monitoring system for critical buildings","authors":"Alberto Girolami, D. Brunelli, L. Benini","doi":"10.1109/EESMS.2017.8052686","DOIUrl":"https://doi.org/10.1109/EESMS.2017.8052686","url":null,"abstract":"In this paper we present a low-cost distributed embedded system for Structural Health Monitoring (SHM) that uses very cost-effective MEMS accelerometers, instead of more expensive piezoelectric analog transducers. The proposed platform provides online filtering and fusion of the collected data directly on-board. Data are transmitted after processing using a WiFi transceiver. Low-cost and synchronized devices permit to have more fine-grained measurements and a comprehensive assessment of the whole building, by evaluating their response to vibrations. The challenge addressed in this paper is to execute a quite computationally-demanding digital filtering on a low-cost microcontroller STM32, and to reduce the signal-to-noise ratio typical of MEMS devices with a spatial redundancy of the sensors. Our work poses the basis for low-cost methods for elaborating complex modal analysis of buildings and structures.","PeriodicalId":285890,"journal":{"name":"2017 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems (EESMS)","volume":"375 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123317328","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}
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