Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/77540
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dc.contributor.authorTan, Alvin Chong Wei
dc.date.accessioned2019-05-31T01:53:49Z
dc.date.available2019-05-31T01:53:49Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/10356/77540
dc.description.abstractIn May 2016, Singapore Mass Rapid Transit (SMRT) collaborated with Nanyang Technological University, Singapore (NTU) and National Research Foundation (NRF) to set up and facilitate an interdisciplinary research laboratory. The focus of the SMRT-NTU is on research and development of new technologies relevant to urban rail transportation. Condition Monitoring of Train Door is one of the two corresponding research tracks in the development of ground-breaking urban rail solutions. This research track focuses on developing better detection methods and monitoring system to address potential issues quickly and accurately, even before they happen. In my Final Year Project, TensorFlow’s Faster Region Convolution Neural Network (Faster-RCNN) will be used to create a classifier for Human Detection. This Classifier is used in conjunction with Video Processing. This project aims to strengthen the current condition monitoring system capabilities and enhance the reliability of Singapore Train System allows engineers to save time on checking every door for the possibilities of failure.en_US
dc.format.extent53 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen_US
dc.titleCondition monitoring of a train door systemen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorLing Keck Voonen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineering (Electrical and Electronic Engineering)en_US
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Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)
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