Pub Date : 2018-07-01DOI: 10.1109/MESA.2018.8449202
A. Athukorala, Nipuna Ranasinghe, Kosala Herath, P. Jayasekara, T. Lalitharatne
Personal and medium scale farming has been showing a downward trend throughout the past few decades. Individuals are demotivated to engage in farming activities, due to lack of time, and the higher efficiency in large-scale farming. However, there is a significant health concern arising from the consumption of these products, as they are grown using artificial fertilizers and contain residues of insecticides and pesticides. Automation can motivate personal and medium scale farming, through cutting down the time requirements for farming and by increasing the farming efficiency. Our solution - Scalable Autonomous Agronomical Smartbot (SAASbot) aims at automating farming activities (planting seeds, watering, fertilizing, weed removal) while providing a scalable robotic platform for personal to medium scale farming. In this paper, design and implementation of the SASSBot and testing and validation of the system are presented.
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Pub Date : 2018-07-01DOI: 10.1109/MESA.2018.8449179
Alexander C. Amies, C. Pretty, G. Rodgers, J. Chase
Structural Health Monitoring (SHM) is an active field of research concerned with the development of sensors to measure structural loading and deformation as a result of external loading. This paper details the testing of a new method of SHM, which uses frequency-modulated continuous wave (FMCW) radar to measure the displacement of a structure. This method avoids the integral drift errors incurred by contemporary accelerometer-based devices. In order to determine a structures interstorey drift ratio (IDR), an FMCW radar device measures the diagonal distance between two opposite corners of two adjacent floors. This distance can then be converted to an IDR using knowledge of the dimensions of the structure. A prototype FMCW radar unit was built to verify that such a method is able to achieve the precision necessary for SHM. The device was tested using a shake table driven with ground motion data taken from the 2011 Christchurch, New Zealand earthquakes. The distance between the radar transceiver and the target reflector was compared to linear variable differential transformer (LVDT) data to determine the error in target tracking. The mean distance error was found to be 0.0308%, which corresponded to a mean IDR error for an arbitrary structure of 0.00107. This value was half the required mean error determined to be suitable for SHM purposes, meaning that the results of this experimentation justify further research into the implementation of this method.
{"title":"Shake Table Testing of a Radar-Based Structural Health Monitoring Method","authors":"Alexander C. Amies, C. Pretty, G. Rodgers, J. Chase","doi":"10.1109/MESA.2018.8449179","DOIUrl":"https://doi.org/10.1109/MESA.2018.8449179","url":null,"abstract":"Structural Health Monitoring (SHM) is an active field of research concerned with the development of sensors to measure structural loading and deformation as a result of external loading. This paper details the testing of a new method of SHM, which uses frequency-modulated continuous wave (FMCW) radar to measure the displacement of a structure. This method avoids the integral drift errors incurred by contemporary accelerometer-based devices. In order to determine a structures interstorey drift ratio (IDR), an FMCW radar device measures the diagonal distance between two opposite corners of two adjacent floors. This distance can then be converted to an IDR using knowledge of the dimensions of the structure. A prototype FMCW radar unit was built to verify that such a method is able to achieve the precision necessary for SHM. The device was tested using a shake table driven with ground motion data taken from the 2011 Christchurch, New Zealand earthquakes. The distance between the radar transceiver and the target reflector was compared to linear variable differential transformer (LVDT) data to determine the error in target tracking. The mean distance error was found to be 0.0308%, which corresponded to a mean IDR error for an arbitrary structure of 0.00107. This value was half the required mean error determined to be suitable for SHM purposes, meaning that the results of this experimentation justify further research into the implementation of this method.","PeriodicalId":138936,"journal":{"name":"2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121630215","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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